datasetId stringlengths 2 117 | card stringlengths 19 1.01M |
|---|---|
autoevaluate/autoeval-eval-mathemakitten__winobias_antistereotype_test_cot_v1-math-6c03d1-1913164902 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- mathemakitten/winobias_antistereotype_test_cot_v1
eval_info:
task: text_zero_shot_classification
model: ArthurZ/opt-125m
metrics: []
dataset_name: mathemakitten/winobias_antistereotype_test_cot_v1
dataset_config: mathemakitten--winobias_antistereotype_test_cot_v1
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: ArthurZ/opt-125m
* Dataset: mathemakitten/winobias_antistereotype_test_cot_v1
* Config: mathemakitten--winobias_antistereotype_test_cot_v1
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@mathemakitten](https://huggingface.co/mathemakitten) for evaluating this model. |
sayakpaul/drawbench-sdxl-refiner | ---
dataset_info:
features:
- name: Prompt
dtype: string
- name: Image
dtype: image
- name: Upsampled_Prompt
dtype: string
- name: Image_With_Upsampled_Prompt
dtype: image
- name: model_name
dtype: string
- name: seed
dtype: int64
splits:
- name: train
num_bytes: 619027012.0
num_examples: 200
download_size: 619026117
dataset_size: 619027012.0
---
# Dataset Card for "drawbench-sdxl-refiner"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
open-llm-leaderboard/details_GeneZC__MiniChat-2-3B | ---
pretty_name: Evaluation run of GeneZC/MiniChat-2-3B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [GeneZC/MiniChat-2-3B](https://huggingface.co/GeneZC/MiniChat-2-3B) 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_GeneZC__MiniChat-2-3B\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-12-28T20:18:40.013082](https://huggingface.co/datasets/open-llm-leaderboard/details_GeneZC__MiniChat-2-3B/blob/main/results_2023-12-28T20-18-40.013082.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\": 0.4761716481666408,\n\
\ \"acc_stderr\": 0.034826726358070326,\n \"acc_norm\": 0.47887559448102573,\n\
\ \"acc_norm_stderr\": 0.03555951791292578,\n \"mc1\": 0.32068543451652387,\n\
\ \"mc1_stderr\": 0.0163391703732809,\n \"mc2\": 0.49642986843760467,\n\
\ \"mc2_stderr\": 0.015526476817027401\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.42406143344709896,\n \"acc_stderr\": 0.014441889627464394,\n\
\ \"acc_norm\": 0.44880546075085326,\n \"acc_norm_stderr\": 0.014534599585097669\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5030870344552878,\n\
\ \"acc_stderr\": 0.004989686307484557,\n \"acc_norm\": 0.6768571997610038,\n\
\ \"acc_norm_stderr\": 0.004667209383690235\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \
\ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.4444444444444444,\n\
\ \"acc_stderr\": 0.04292596718256981,\n \"acc_norm\": 0.4444444444444444,\n\
\ \"acc_norm_stderr\": 0.04292596718256981\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.48026315789473684,\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\": 0.04975698519562428,\n \"acc_norm\": 0.43,\n \
\ \"acc_norm_stderr\": 0.04975698519562428\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.4867924528301887,\n \"acc_stderr\": 0.030762134874500482,\n\
\ \"acc_norm\": 0.4867924528301887,\n \"acc_norm_stderr\": 0.030762134874500482\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5138888888888888,\n\
\ \"acc_stderr\": 0.04179596617581,\n \"acc_norm\": 0.5138888888888888,\n\
\ \"acc_norm_stderr\": 0.04179596617581\n },\n \"harness|hendrycksTest-college_chemistry|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_computer_science|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_mathematics|5\"\
: {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \
\ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.42196531791907516,\n\
\ \"acc_stderr\": 0.0376574669386515,\n \"acc_norm\": 0.42196531791907516,\n\
\ \"acc_norm_stderr\": 0.0376574669386515\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.38235294117647056,\n \"acc_stderr\": 0.04835503696107223,\n\
\ \"acc_norm\": 0.38235294117647056,\n \"acc_norm_stderr\": 0.04835503696107223\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.6,\n \"acc_stderr\": 0.04923659639173309,\n \"acc_norm\": 0.6,\n\
\ \"acc_norm_stderr\": 0.04923659639173309\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.39148936170212767,\n \"acc_stderr\": 0.031907012423268113,\n\
\ \"acc_norm\": 0.39148936170212767,\n \"acc_norm_stderr\": 0.031907012423268113\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.37719298245614036,\n\
\ \"acc_stderr\": 0.045595221419582166,\n \"acc_norm\": 0.37719298245614036,\n\
\ \"acc_norm_stderr\": 0.045595221419582166\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.43448275862068964,\n \"acc_stderr\": 0.04130740879555497,\n\
\ \"acc_norm\": 0.43448275862068964,\n \"acc_norm_stderr\": 0.04130740879555497\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.30423280423280424,\n \"acc_stderr\": 0.023695415009463087,\n \"\
acc_norm\": 0.30423280423280424,\n \"acc_norm_stderr\": 0.023695415009463087\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.35714285714285715,\n\
\ \"acc_stderr\": 0.04285714285714281,\n \"acc_norm\": 0.35714285714285715,\n\
\ \"acc_norm_stderr\": 0.04285714285714281\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.34,\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\": 0.5516129032258065,\n\
\ \"acc_stderr\": 0.028292056830112728,\n \"acc_norm\": 0.5516129032258065,\n\
\ \"acc_norm_stderr\": 0.028292056830112728\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.3694581280788177,\n \"acc_stderr\": 0.03395970381998575,\n\
\ \"acc_norm\": 0.3694581280788177,\n \"acc_norm_stderr\": 0.03395970381998575\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.47,\n \"acc_stderr\": 0.050161355804659205,\n \"acc_norm\"\
: 0.47,\n \"acc_norm_stderr\": 0.050161355804659205\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.6424242424242425,\n \"acc_stderr\": 0.03742597043806585,\n\
\ \"acc_norm\": 0.6424242424242425,\n \"acc_norm_stderr\": 0.03742597043806585\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.5707070707070707,\n \"acc_stderr\": 0.035265527246011986,\n \"\
acc_norm\": 0.5707070707070707,\n \"acc_norm_stderr\": 0.035265527246011986\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.6373056994818653,\n \"acc_stderr\": 0.034697137917043715,\n\
\ \"acc_norm\": 0.6373056994818653,\n \"acc_norm_stderr\": 0.034697137917043715\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.4358974358974359,\n \"acc_stderr\": 0.02514180151117749,\n \
\ \"acc_norm\": 0.4358974358974359,\n \"acc_norm_stderr\": 0.02514180151117749\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.2851851851851852,\n \"acc_stderr\": 0.027528599210340492,\n \
\ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.027528599210340492\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.47058823529411764,\n \"acc_stderr\": 0.032422250271150053,\n\
\ \"acc_norm\": 0.47058823529411764,\n \"acc_norm_stderr\": 0.032422250271150053\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\"\
: 0.6458715596330276,\n \"acc_stderr\": 0.02050472901382911,\n \"\
acc_norm\": 0.6458715596330276,\n \"acc_norm_stderr\": 0.02050472901382911\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.38425925925925924,\n \"acc_stderr\": 0.03317354514310742,\n \"\
acc_norm\": 0.38425925925925924,\n \"acc_norm_stderr\": 0.03317354514310742\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.6225490196078431,\n \"acc_stderr\": 0.03402272044340705,\n \"\
acc_norm\": 0.6225490196078431,\n \"acc_norm_stderr\": 0.03402272044340705\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.6582278481012658,\n \"acc_stderr\": 0.030874537537553617,\n \
\ \"acc_norm\": 0.6582278481012658,\n \"acc_norm_stderr\": 0.030874537537553617\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.47085201793721976,\n\
\ \"acc_stderr\": 0.03350073248773403,\n \"acc_norm\": 0.47085201793721976,\n\
\ \"acc_norm_stderr\": 0.03350073248773403\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.5343511450381679,\n \"acc_stderr\": 0.04374928560599738,\n\
\ \"acc_norm\": 0.5343511450381679,\n \"acc_norm_stderr\": 0.04374928560599738\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.6115702479338843,\n \"acc_stderr\": 0.044492703500683836,\n \"\
acc_norm\": 0.6115702479338843,\n \"acc_norm_stderr\": 0.044492703500683836\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.5185185185185185,\n\
\ \"acc_stderr\": 0.04830366024635331,\n \"acc_norm\": 0.5185185185185185,\n\
\ \"acc_norm_stderr\": 0.04830366024635331\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.5398773006134969,\n \"acc_stderr\": 0.0391585729143697,\n\
\ \"acc_norm\": 0.5398773006134969,\n \"acc_norm_stderr\": 0.0391585729143697\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.33035714285714285,\n\
\ \"acc_stderr\": 0.04464285714285714,\n \"acc_norm\": 0.33035714285714285,\n\
\ \"acc_norm_stderr\": 0.04464285714285714\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.6504854368932039,\n \"acc_stderr\": 0.047211885060971716,\n\
\ \"acc_norm\": 0.6504854368932039,\n \"acc_norm_stderr\": 0.047211885060971716\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.688034188034188,\n\
\ \"acc_stderr\": 0.03035152732334495,\n \"acc_norm\": 0.688034188034188,\n\
\ \"acc_norm_stderr\": 0.03035152732334495\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.55,\n \"acc_stderr\": 0.049999999999999996,\n \
\ \"acc_norm\": 0.55,\n \"acc_norm_stderr\": 0.049999999999999996\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.5504469987228607,\n\
\ \"acc_stderr\": 0.017788725283507337,\n \"acc_norm\": 0.5504469987228607,\n\
\ \"acc_norm_stderr\": 0.017788725283507337\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.5173410404624278,\n \"acc_stderr\": 0.02690290045866664,\n\
\ \"acc_norm\": 0.5173410404624278,\n \"acc_norm_stderr\": 0.02690290045866664\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2424581005586592,\n\
\ \"acc_stderr\": 0.014333522059217892,\n \"acc_norm\": 0.2424581005586592,\n\
\ \"acc_norm_stderr\": 0.014333522059217892\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.5163398692810458,\n \"acc_stderr\": 0.028614624752805434,\n\
\ \"acc_norm\": 0.5163398692810458,\n \"acc_norm_stderr\": 0.028614624752805434\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.5112540192926045,\n\
\ \"acc_stderr\": 0.028390897396863533,\n \"acc_norm\": 0.5112540192926045,\n\
\ \"acc_norm_stderr\": 0.028390897396863533\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.45987654320987653,\n \"acc_stderr\": 0.027731022753539274,\n\
\ \"acc_norm\": 0.45987654320987653,\n \"acc_norm_stderr\": 0.027731022753539274\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.3475177304964539,\n \"acc_stderr\": 0.02840662780959095,\n \
\ \"acc_norm\": 0.3475177304964539,\n \"acc_norm_stderr\": 0.02840662780959095\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.38852672750977835,\n\
\ \"acc_stderr\": 0.012448817838292374,\n \"acc_norm\": 0.38852672750977835,\n\
\ \"acc_norm_stderr\": 0.012448817838292374\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.35661764705882354,\n \"acc_stderr\": 0.029097209568411945,\n\
\ \"acc_norm\": 0.35661764705882354,\n \"acc_norm_stderr\": 0.029097209568411945\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.43790849673202614,\n \"acc_stderr\": 0.020071257886886518,\n \
\ \"acc_norm\": 0.43790849673202614,\n \"acc_norm_stderr\": 0.020071257886886518\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.509090909090909,\n\
\ \"acc_stderr\": 0.0478833976870286,\n \"acc_norm\": 0.509090909090909,\n\
\ \"acc_norm_stderr\": 0.0478833976870286\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.6040816326530613,\n \"acc_stderr\": 0.03130802899065685,\n\
\ \"acc_norm\": 0.6040816326530613,\n \"acc_norm_stderr\": 0.03130802899065685\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.6666666666666666,\n\
\ \"acc_stderr\": 0.033333333333333326,\n \"acc_norm\": 0.6666666666666666,\n\
\ \"acc_norm_stderr\": 0.033333333333333326\n },\n \"harness|hendrycksTest-us_foreign_policy|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-virology|5\": {\n \"acc\": 0.42771084337349397,\n\
\ \"acc_stderr\": 0.038515976837185335,\n \"acc_norm\": 0.42771084337349397,\n\
\ \"acc_norm_stderr\": 0.038515976837185335\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.5321637426900585,\n \"acc_stderr\": 0.03826882417660369,\n\
\ \"acc_norm\": 0.5321637426900585,\n \"acc_norm_stderr\": 0.03826882417660369\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.32068543451652387,\n\
\ \"mc1_stderr\": 0.0163391703732809,\n \"mc2\": 0.49642986843760467,\n\
\ \"mc2_stderr\": 0.015526476817027401\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.664561957379637,\n \"acc_stderr\": 0.013269575904851432\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.32676269901440486,\n \
\ \"acc_stderr\": 0.012919408108656435\n }\n}\n```"
repo_url: https://huggingface.co/GeneZC/MiniChat-2-3B
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|arc:challenge|25_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|gsm8k|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hellaswag|10_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-28T20-18-40.013082.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-28T20-18-40.013082.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- '**/details_harness|winogrande|5_2023-12-28T20-18-40.013082.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-28T20-18-40.013082.parquet'
- config_name: results
data_files:
- split: 2023_12_28T20_18_40.013082
path:
- results_2023-12-28T20-18-40.013082.parquet
- split: latest
path:
- results_2023-12-28T20-18-40.013082.parquet
---
# Dataset Card for Evaluation run of GeneZC/MiniChat-2-3B
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [GeneZC/MiniChat-2-3B](https://huggingface.co/GeneZC/MiniChat-2-3B) 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_GeneZC__MiniChat-2-3B",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-28T20:18:40.013082](https://huggingface.co/datasets/open-llm-leaderboard/details_GeneZC__MiniChat-2-3B/blob/main/results_2023-12-28T20-18-40.013082.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": 0.4761716481666408,
"acc_stderr": 0.034826726358070326,
"acc_norm": 0.47887559448102573,
"acc_norm_stderr": 0.03555951791292578,
"mc1": 0.32068543451652387,
"mc1_stderr": 0.0163391703732809,
"mc2": 0.49642986843760467,
"mc2_stderr": 0.015526476817027401
},
"harness|arc:challenge|25": {
"acc": 0.42406143344709896,
"acc_stderr": 0.014441889627464394,
"acc_norm": 0.44880546075085326,
"acc_norm_stderr": 0.014534599585097669
},
"harness|hellaswag|10": {
"acc": 0.5030870344552878,
"acc_stderr": 0.004989686307484557,
"acc_norm": 0.6768571997610038,
"acc_norm_stderr": 0.004667209383690235
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.29,
"acc_stderr": 0.04560480215720684,
"acc_norm": 0.29,
"acc_norm_stderr": 0.04560480215720684
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.4444444444444444,
"acc_stderr": 0.04292596718256981,
"acc_norm": 0.4444444444444444,
"acc_norm_stderr": 0.04292596718256981
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.48026315789473684,
"acc_stderr": 0.040657710025626036,
"acc_norm": 0.48026315789473684,
"acc_norm_stderr": 0.040657710025626036
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.43,
"acc_stderr": 0.04975698519562428,
"acc_norm": 0.43,
"acc_norm_stderr": 0.04975698519562428
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.4867924528301887,
"acc_stderr": 0.030762134874500482,
"acc_norm": 0.4867924528301887,
"acc_norm_stderr": 0.030762134874500482
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.5138888888888888,
"acc_stderr": 0.04179596617581,
"acc_norm": 0.5138888888888888,
"acc_norm_stderr": 0.04179596617581
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.39,
"acc_stderr": 0.04902071300001975,
"acc_norm": 0.39,
"acc_norm_stderr": 0.04902071300001975
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.46,
"acc_stderr": 0.05009082659620333,
"acc_norm": 0.46,
"acc_norm_stderr": 0.05009082659620333
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.29,
"acc_stderr": 0.04560480215720684,
"acc_norm": 0.29,
"acc_norm_stderr": 0.04560480215720684
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.42196531791907516,
"acc_stderr": 0.0376574669386515,
"acc_norm": 0.42196531791907516,
"acc_norm_stderr": 0.0376574669386515
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.38235294117647056,
"acc_stderr": 0.04835503696107223,
"acc_norm": 0.38235294117647056,
"acc_norm_stderr": 0.04835503696107223
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.6,
"acc_stderr": 0.04923659639173309,
"acc_norm": 0.6,
"acc_norm_stderr": 0.04923659639173309
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.39148936170212767,
"acc_stderr": 0.031907012423268113,
"acc_norm": 0.39148936170212767,
"acc_norm_stderr": 0.031907012423268113
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.37719298245614036,
"acc_stderr": 0.045595221419582166,
"acc_norm": 0.37719298245614036,
"acc_norm_stderr": 0.045595221419582166
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.43448275862068964,
"acc_stderr": 0.04130740879555497,
"acc_norm": 0.43448275862068964,
"acc_norm_stderr": 0.04130740879555497
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.30423280423280424,
"acc_stderr": 0.023695415009463087,
"acc_norm": 0.30423280423280424,
"acc_norm_stderr": 0.023695415009463087
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.35714285714285715,
"acc_stderr": 0.04285714285714281,
"acc_norm": 0.35714285714285715,
"acc_norm_stderr": 0.04285714285714281
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.34,
"acc_stderr": 0.04760952285695235,
"acc_norm": 0.34,
"acc_norm_stderr": 0.04760952285695235
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.5516129032258065,
"acc_stderr": 0.028292056830112728,
"acc_norm": 0.5516129032258065,
"acc_norm_stderr": 0.028292056830112728
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.3694581280788177,
"acc_stderr": 0.03395970381998575,
"acc_norm": 0.3694581280788177,
"acc_norm_stderr": 0.03395970381998575
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.47,
"acc_stderr": 0.050161355804659205,
"acc_norm": 0.47,
"acc_norm_stderr": 0.050161355804659205
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.6424242424242425,
"acc_stderr": 0.03742597043806585,
"acc_norm": 0.6424242424242425,
"acc_norm_stderr": 0.03742597043806585
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.5707070707070707,
"acc_stderr": 0.035265527246011986,
"acc_norm": 0.5707070707070707,
"acc_norm_stderr": 0.035265527246011986
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.6373056994818653,
"acc_stderr": 0.034697137917043715,
"acc_norm": 0.6373056994818653,
"acc_norm_stderr": 0.034697137917043715
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.4358974358974359,
"acc_stderr": 0.02514180151117749,
"acc_norm": 0.4358974358974359,
"acc_norm_stderr": 0.02514180151117749
},
"harness|hendrycksTest-high_school_mathematics|5": {
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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]
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### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
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## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
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### Out-of-Scope Use
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## 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. -->
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## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
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### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
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#### Who are the source data producers?
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### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
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#### Who are the annotators?
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#### Personal and Sensitive Information
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## Bias, Risks, and Limitations
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### Recommendations
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## Citation [optional]
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Dahoas/fno-cifar10-32 | ---
dataset_info:
features:
- name: images
sequence:
sequence:
sequence: float32
splits:
- name: train
num_bytes: 635009024
num_examples: 50048
download_size: 647482139
dataset_size: 635009024
---
# Dataset Card for "fno-cifar10-32"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
james-burton/OrientalMuseum_min3-mat-text | ---
dataset_info:
features:
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dtype: string
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dtype: string
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dtype: image
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dtype: string
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dtype: string
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dtype: string
- name: label
dtype:
class_label:
names:
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'4': Gouache on Paper
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'6': Ink and Colour on Paper
'7': Ink and Colours on Silk
'8': Ink and Opaque Watercolour on Paper
'9': Ink on Paper
'10': Japanese paper
'11': Mortar
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'13': Opaque Watercolour on Paper
'14': Opaque Watercolour or Gouache on Mica
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'18': Resin/Plastic
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'23': agate
'24': alabaster
'25': aluminum
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'27': amethyst
'28': artificial stone
'29': bamboo
'30': basalt
'31': bone
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'33': brass
'34': bronze
'35': burnt jade
'36': canvas
'37': cardboard
'38': cards
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'40': ceramic
'41': clay
'42': copper
'43': copper alloy
'44': coral
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- name: production.period
dtype: string
- name: production.place
dtype: string
splits:
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num_bytes: 895992895.1885473
num_examples: 7454
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num_examples: 1754
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num_bytes: 271127037.06082916
num_examples: 1755
download_size: 1267043351
dataset_size: 1362107938.09
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
|
luna-code/beatnum-subset | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: completion
dtype: string
- name: api
dtype: string
splits:
- name: train
num_bytes: 15522111
num_examples: 1166
download_size: 5490279
dataset_size: 15522111
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
donggook/tttt | ---
language:
- ko
dataset_info:
features:
- name: symbol
dtype: string
- name: name
dtype: string
- name: last
dtype: string
- name: change
dtype: string
- name: volume
dtype: string
- name: type
dtype: string
- name: region
dtype: string
--- |
arieg/8000_large_4 | ---
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dtype: image
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splits:
- name: train
num_bytes: 2172280929.935
num_examples: 39985
download_size: 2117534227
dataset_size: 2172280929.935
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
freshpearYoon/vr_val_free_3 | ---
dataset_info:
features:
- name: audio
struct:
- name: array
sequence: float64
- name: path
dtype: string
- name: sampling_rate
dtype: int64
- name: filename
dtype: string
- name: NumOfUtterance
dtype: int64
- name: text
dtype: string
- name: samplingrate
dtype: int64
- name: begin_time
dtype: float64
- name: end_time
dtype: float64
- name: speaker_id
dtype: string
- name: directory
dtype: string
splits:
- name: train
num_bytes: 7210576443
num_examples: 10000
download_size: 1221213925
dataset_size: 7210576443
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
sam2ai/hindi_hellaswag_mini | ---
configs:
- config_name: default
data_files:
- split: validation
path: data/validation-*
dataset_info:
features:
- name: gold
dtype: int64
- name: query
dtype: string
- name: choices
sequence: string
splits:
- name: validation
num_bytes: 52876
num_examples: 50
download_size: 24335
dataset_size: 52876
---
# Dataset Card for "hindi_hellaswag_mini"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
huggingface/autotrain-data-dgx-test | Invalid username or password. |
AnilKamat/Ducks | ---
license: apache-2.0
---
|
datahrvoje/twitter_dataset_1713018419 | ---
dataset_info:
features:
- name: id
dtype: string
- name: tweet_content
dtype: string
- name: user_name
dtype: string
- name: user_id
dtype: string
- name: created_at
dtype: string
- name: url
dtype: string
- name: favourite_count
dtype: int64
- name: scraped_at
dtype: string
- name: image_urls
dtype: string
splits:
- name: train
num_bytes: 23107
num_examples: 54
download_size: 13611
dataset_size: 23107
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
Salama1429/tarteel-ai-EA-DI | ---
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: duration
dtype: float64
- name: transcription
dtype: string
splits:
- name: train
num_bytes: 134530727598.282
num_examples: 245093
download_size: 5374089950
dataset_size: 134530727598.282
---
# Dataset Card for "tarteel-ai-EA-DI"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
alzoubi36/title_generation | ---
dataset_info:
features:
- name: text
dtype: string
- name: summary
dtype: string
- name: id
dtype: int64
splits:
- name: validation
num_bytes: 1753243
num_examples: 2000
- name: test
num_bytes: 1682435
num_examples: 2000
- name: train
num_bytes: 17556737
num_examples: 20000
download_size: 10393931
dataset_size: 20992415
---
# Dataset Card for "title_generation"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Nicolas-BZRD/LEGI_opendata | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 4054244489
num_examples: 2373798
download_size: 1112659274
dataset_size: 4054244489
license: odc-by
language:
- fr
tags:
- legal
pretty_name: Codes, Lois et Réglements Consolidés
size_categories:
- 1M<n<10M
---
# LEGI (CODES, LAWS AND REGULATIONS)
[The full consolidated text of national legislation and regulations.](https://echanges.dila.gouv.fr/OPENDATA/LEGI/)<br>
It consists essentially of :
- official codes
- laws
- decree-laws
- ordinances
- decrees
- a selection of decrees
Consolidation of texts involves rewriting an article of a text (or code) to incorporate the change made. Amended or repealed versions are included in the document collection in the same way as current versions. |
thercyl/LLY | ---
dataset_info:
features:
- name: 'Unnamed: 0'
dtype: float64
- name: Ticker
dtype: string
- name: Year
dtype: string
- name: Text
dtype: string
- name: Embedding
dtype: string
splits:
- name: train
num_bytes: 78586543
num_examples: 2258
download_size: 44685787
dataset_size: 78586543
---
# Dataset Card for "LLY"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Hashif/sunoaiaudio1 | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: Audio Data
sequence: float32
splits:
- name: train
num_bytes: 24973173.987341773
num_examples: 55
- name: test
num_bytes: 10897385.012658227
num_examples: 24
download_size: 37125060
dataset_size: 35870559.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
|
nesuri/sorsolingo-tts-bsl | ---
dataset_info:
features:
- name: audio
dtype: audio
- name: transcription
dtype: string
splits:
- name: train
num_bytes: 82617979.0
num_examples: 153
download_size: 79264687
dataset_size: 82617979.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
DearTanishq/CustomDataSetByTan | ---
license: apache-2.0
---
|
xbgoose/ravdess | ---
dataset_info:
features:
- name: audio
dtype: audio
- name: modality
dtype: string
- name: vocal_channel
dtype: string
- name: emotion
dtype: string
- name: emotional_intensity
dtype: string
- name: statement
dtype: string
- name: repetition
dtype: string
- name: actor
dtype: int64
- name: gender
dtype: string
splits:
- name: train
num_bytes: 595474115.04
num_examples: 1440
download_size: 324920159
dataset_size: 595474115.04
---
# Dataset Card for "ravdess"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
TankuVie/vie_sent_segment_unpunctual_text | ---
license: other
---
|
luminoussg/NIH_X-RAY_2017 | ---
license: apache-2.0
---
|
botmaster/mother-2-battle-sprites | ---
annotations_creators: []
language:
- en
language_creators:
- found
license:
- other
multilinguality:
- monolingual
pretty_name: Mother 2 sprites
size_categories:
- n<1K
source_datasets: []
tags: []
task_categories:
- text-to-image
task_ids: []
--- |
CyberHarem/fang_arknights | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of fang/フェン/芬 (Arknights)
This is the dataset of fang/フェン/芬 (Arknights), containing 99 images and their tags.
The core tags of this character are `animal_ears, long_hair, blue_hair, blue_eyes, horse_ears, glasses, semi-rimless_eyewear, under-rim_eyewear, black-framed_eyewear, very_long_hair, horse_girl`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:----------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 99 | 134.35 MiB | [Download](https://huggingface.co/datasets/CyberHarem/fang_arknights/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 1200 | 99 | 113.95 MiB | [Download](https://huggingface.co/datasets/CyberHarem/fang_arknights/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 243 | 230.65 MiB | [Download](https://huggingface.co/datasets/CyberHarem/fang_arknights/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/fang_arknights',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 46 |  |  |  |  |  | 1girl, blue_jacket, long_sleeves, black_scarf, solo, looking_at_viewer, holding_cup, smile, coffee_cup, upper_body, closed_mouth, nail_polish, fur-trimmed_jacket, simple_background, white_background, official_alternate_costume |
| 1 | 7 |  |  |  |  |  | 1girl, black_choker, black_jacket, looking_at_viewer, open_jacket, solo, white_background, collarbone, shirt, simple_background, closed_mouth, upper_body, gloves, hood, long_sleeves, smile, holding |
| 2 | 7 |  |  |  |  |  | 1girl, black_jacket, id_card, long_sleeves, looking_at_viewer, smile, solo, closed_mouth, open_jacket, black_choker, blue_gloves, simple_background, white_background, collarbone, horse_tail, blue_dress, boots, brown_footwear, cowboy_shot, full_body, hair_between_eyes, holding_polearm, spear, standing |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | blue_jacket | long_sleeves | black_scarf | solo | looking_at_viewer | holding_cup | smile | coffee_cup | upper_body | closed_mouth | nail_polish | fur-trimmed_jacket | simple_background | white_background | official_alternate_costume | black_choker | black_jacket | open_jacket | collarbone | shirt | gloves | hood | holding | id_card | blue_gloves | horse_tail | blue_dress | boots | brown_footwear | cowboy_shot | full_body | hair_between_eyes | holding_polearm | spear | standing |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------|:---------------|:--------------|:-------|:--------------------|:--------------|:--------|:-------------|:-------------|:---------------|:--------------|:---------------------|:--------------------|:-------------------|:-----------------------------|:---------------|:---------------|:--------------|:-------------|:--------|:---------|:-------|:----------|:----------|:--------------|:-------------|:-------------|:--------|:-----------------|:--------------|:------------|:--------------------|:------------------|:--------|:-----------|
| 0 | 46 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | |
| 1 | 7 |  |  |  |  |  | X | | X | | X | X | | X | | X | X | | | X | X | | X | X | X | X | X | X | X | X | | | | | | | | | | | | |
| 2 | 7 |  |  |  |  |  | X | | X | | X | X | | X | | | X | | | X | X | | X | X | X | X | | | | | X | X | X | X | X | X | X | X | X | X | X | X |
|
gguichard/wsd_myriade_synth_data_gpt4turbo_1_bge | ---
dataset_info:
features:
- name: tokens
sequence: string
- name: wn_sens
sequence: int64
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 28388539
num_examples: 39518
download_size: 5497364
dataset_size: 28388539
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
tonne/trader | ---
license: apache-2.0
---
|
AlexPlus/cpis | ---
license: mit
---
|
BreetheRun/Prompts | ---
license: apache-2.0
task_categories:
- text-generation
language:
- en
tags:
- not-for-all-audiences
--- |
pawkanarek/poke_test | ---
language:
- en
dataset_info:
features:
- name: prompt
dtype: string
- name: completion
dtype: string
splits:
- name: train
num_bytes: 222347.109375
num_examples: 460
- name: test
num_bytes: 25134.890625
num_examples: 52
download_size: 27996
dataset_size: 247482.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
|
jlh/uci-bank | ---
dataset_info:
features:
- name: age
dtype: int64
- name: job
dtype: string
- name: marital
dtype: string
- name: education
dtype: string
- name: default
dtype: string
- name: balance
dtype: int64
- name: housing
dtype: string
- name: loan
dtype: string
- name: contact
dtype: string
- name: day
dtype: int64
- name: month
dtype: string
- name: duration
dtype: int64
- name: campaign
dtype: int64
- name: pdays
dtype: int64
- name: previous
dtype: int64
- name: poutcome
dtype: string
- name: y
dtype:
class_label:
names:
'0': 'no'
'1': 'yes'
splits:
- name: train
num_bytes: 674228
num_examples: 4521
download_size: 92171
dataset_size: 674228
---
# Dataset Card for "uci-bank"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
marup/PoronChanRVC150Epochs | ---
license: openrail
---
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/6d8774d1 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 178
num_examples: 10
download_size: 1341
dataset_size: 178
---
# Dataset Card for "6d8774d1"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
drewtray/instructpix2pix-spatial | ---
dataset_info:
features:
- name: original_image
dtype: image
- name: edit_prompt
dtype: string
- name: transformed_image
dtype: image
splits:
- name: train
num_bytes: 11378934045.176
num_examples: 11557
download_size: 11039896281
dataset_size: 11378934045.176
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
Shakib75/playtus-dataset-ahs | ---
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-*
---
|
CyberHarem/tomoe_bluearchive | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of tomoe/佐城トモエ/巴 (Blue Archive)
This is the dataset of tomoe/佐城トモエ/巴 (Blue Archive), containing 33 images and their tags.
The core tags of this character are `long_hair, breasts, pink_hair, halo, large_breasts, braid, pink_eyes, very_long_hair`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:----------|:-------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 33 | 55.23 MiB | [Download](https://huggingface.co/datasets/CyberHarem/tomoe_bluearchive/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 1200 | 33 | 48.40 MiB | [Download](https://huggingface.co/datasets/CyberHarem/tomoe_bluearchive/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 82 | 99.77 MiB | [Download](https://huggingface.co/datasets/CyberHarem/tomoe_bluearchive/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/tomoe_bluearchive',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 17 |  |  |  |  |  | looking_at_viewer, 1girl, blush, smile, long_sleeves, solo, black_shirt, closed_mouth, collared_shirt, simple_background, white_background, white_skirt, black_thighhighs, hair_between_eyes, jacket, necktie, gloves, purple_hair, shirt_tucked_in, thighs |
| 1 | 6 |  |  |  |  |  | black_gloves, 1girl, holding, necktie, ushanka, white_headwear, fur_trim, long_sleeves, looking_at_viewer, solo, winter_clothes, black_pantyhose, full_body, purple_hair, twin_braids, white_coat |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | looking_at_viewer | 1girl | blush | smile | long_sleeves | solo | black_shirt | closed_mouth | collared_shirt | simple_background | white_background | white_skirt | black_thighhighs | hair_between_eyes | jacket | necktie | gloves | purple_hair | shirt_tucked_in | thighs | black_gloves | holding | ushanka | white_headwear | fur_trim | winter_clothes | black_pantyhose | full_body | twin_braids | white_coat |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------|:--------|:--------|:--------|:---------------|:-------|:--------------|:---------------|:-----------------|:--------------------|:-------------------|:--------------|:-------------------|:--------------------|:---------|:----------|:---------|:--------------|:------------------|:---------|:---------------|:----------|:----------|:-----------------|:-----------|:-----------------|:------------------|:------------|:--------------|:-------------|
| 0 | 17 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | |
| 1 | 6 |  |  |  |  |  | X | X | | | X | X | | | | | | | | | | X | | X | | | X | X | X | X | X | X | X | X | X | X |
|
winniealita/indio | ---
license: openrail
---
|
NetherlandsForensicInstitute/wiki-atomic-edits-translated-nl | ---
license: cc-by-sa-4.0
task_categories:
- sentence-similarity
size_categories:
- 1M<n<10M
language:
- nl
---
This is a Dutch version of the [Wiki Atomic Edits](https://github.com/google-research-datasets/wiki-atomic-edits) dataset. Which we have auto-translated from English into Dutch using Meta's [No Language Left Behind](https://ai.facebook.com/research/no-language-left-behind/) model, specifically the [huggingface implementation](https://huggingface.co/facebook/nllb-200-distilled-600M). |
manojpreveen/Orca | ---
license: mit
language:
- en
---
**Orca Dataset**
**1. orca_1m_gpt4.csv** - ~1M Orca Data generated by using GPT-4
**2. orca_3.5m_gpt3.5.csv** - ~3.5M Orca Data generated by using GPT-3.5 |
iamshnoo/alpaca-cleaned-hindi | ---
dataset_info:
features:
- name: input
dtype: string
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 86237527
num_examples: 51760
download_size: 31323200
dataset_size: 86237527
---
Translated from yahma/alpaca-cleaned using NLLB-1.3B
# Dataset Card for "alpaca-cleaned-hindi"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
SatCat/github-issues | ---
dataset_info:
features:
- name: url
dtype: string
- name: repository_url
dtype: string
- name: labels_url
dtype: string
- name: comments_url
dtype: string
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dtype: string
- name: html_url
dtype: string
- name: id
dtype: int64
- name: node_id
dtype: string
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dtype: int64
- name: title
dtype: string
- name: user
struct:
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dtype: string
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dtype: string
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dtype: string
- name: following_url
dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: int64
- name: login
dtype: string
- name: node_id
dtype: string
- name: organizations_url
dtype: string
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dtype: string
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dtype: string
- name: site_admin
dtype: bool
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dtype: string
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dtype: string
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- name: state
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- name: locked
dtype: bool
- name: assignee
struct:
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dtype: string
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dtype: string
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dtype: string
- name: following_url
dtype: string
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dtype: string
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dtype: string
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dtype: int64
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dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: bool
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dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: bool
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dtype: string
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dtype: string
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- name: milestone
struct:
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struct:
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dtype: string
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- name: login
dtype: string
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dtype: string
- name: repos_url
dtype: string
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- name: html_url
dtype: string
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dtype: string
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dtype: int64
- name: open_issues
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dtype: string
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- name: comments
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- name: author_association
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- name: active_lock_reason
dtype: 'null'
- name: draft
dtype: bool
- name: pull_request
struct:
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dtype: string
- name: html_url
dtype: string
- name: merged_at
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- name: patch_url
dtype: string
- name: url
dtype: string
- name: body
dtype: string
- name: reactions
struct:
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dtype: int64
- name: '-1'
dtype: int64
- name: confused
dtype: int64
- name: eyes
dtype: int64
- name: heart
dtype: int64
- name: hooray
dtype: int64
- name: laugh
dtype: int64
- name: rocket
dtype: int64
- name: total_count
dtype: int64
- name: url
dtype: string
- name: timeline_url
dtype: string
- name: performed_via_github_app
dtype: 'null'
- name: state_reason
dtype: string
- name: is_pull_request
dtype: bool
splits:
- name: train
num_bytes: 20549193
num_examples: 5345
download_size: 5891736
dataset_size: 20549193
---
# Dataset Card for "github-issues"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
autoevaluate/autoeval-eval-inverse-scaling__redefine-math-inverse-scaling__redefin-f7efd9-1695359598 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- inverse-scaling/redefine-math
eval_info:
task: text_zero_shot_classification
model: inverse-scaling/opt-125m_eval
metrics: []
dataset_name: inverse-scaling/redefine-math
dataset_config: inverse-scaling--redefine-math
dataset_split: train
col_mapping:
text: prompt
classes: classes
target: answer_index
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: inverse-scaling/opt-125m_eval
* Dataset: inverse-scaling/redefine-math
* Config: inverse-scaling--redefine-math
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@MicPie](https://huggingface.co/MicPie) for evaluating this model. |
yuntian-deng/iclr-decisions | ---
dataset_info:
features:
- name: conference
dtype: string
- name: title
dtype: string
- name: abstract
dtype: string
- name: decision
dtype: string
splits:
- name: train
num_bytes: 18028359
num_examples: 13585
download_size: 9595768
dataset_size: 18028359
---
# Dataset Card for "iclr-decisions"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
liuyanchen1015/MULTI_VALUE_mrpc_medial_object_perfect | ---
dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: label
dtype: int64
- name: idx
dtype: int64
- name: value_score
dtype: int64
splits:
- name: test
num_bytes: 20194
num_examples: 68
- name: train
num_bytes: 51827
num_examples: 186
- name: validation
num_bytes: 5344
num_examples: 18
download_size: 64625
dataset_size: 77365
---
# Dataset Card for "MULTI_VALUE_mrpc_medial_object_perfect"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
ppxscal/academic_embeddings_cosimrank_test_bfs | ---
dataset_info:
features:
- name: Query Text
dtype: string
- name: Ranking 1
dtype: string
- name: Ranking 2
dtype: string
- name: Ranking 3
dtype: string
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dtype: string
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dtype: string
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dtype: float64
splits:
- name: train
num_bytes: 1903302961
num_examples: 134482
download_size: 343156022
dataset_size: 1903302961
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
nestymeee/filtered-imaterialist | ---
license: mit
---
## Dataset for clothes segmentation
Based on [iMaterialist Dataset](https://www.kaggle.com/c/imaterialist-fashion-2019-FGVC6/data) with several adjustments:
1. Filtered images with more than 1 person with no labeled clothes
2. Compressed number of classes to 8: `'background', 'upperbody', 'upperbody_up', 'lowerbody', 'wholebody', 'wholebody_up', 'shoes', 'accesories'`
3. Simple structure with 2 folders: images 512x512 in `.jpg` and corresponding segmaps 512x512 in `.npy`
4. You can find example class and data vizualisation in `dataset.ipynb`
If you find any bugs, please contact me on: nestymeee@gmail.com |
zeio/auto-batch | ---
dataset_info:
- config_name: spoken
features:
- name: title
dtype: string
- name: speech
dtype:
audio:
sampling_rate: 48000
- name: topics
list:
- name: posts
list:
- name: text
dtype: string
splits:
- name: train
num_bytes: 4378815049786.86
num_examples: 875140
download_size: 58030117749
dataset_size: 4378815049786.86
- config_name: written
features:
- name: title
dtype: string
- name: topics
list:
- name: posts
list:
- name: text
dtype: string
splits:
- name: train
num_bytes: 23170678001
num_examples: 875140
download_size: 11291624575
dataset_size: 23170678001
configs:
- config_name: spoken
data_files:
- split: train
path: spoken/train-*
- config_name: written
data_files:
- split: train
path: written/train-*
---
# Dataset Card for "auto-batch"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
ohhhchank3/20133118_8_12 | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 10704174
num_examples: 23522
download_size: 5401665
dataset_size: 10704174
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
ixarchakos/test | ---
dataset_info:
features:
- name: input_image
struct:
- name: bytes
dtype: binary
- name: path
dtype: string
- name: edit_prompt
dtype: string
- name: edited_image
struct:
- name: bytes
dtype: binary
- name: path
dtype: string
splits:
- name: train
num_bytes: 2702702
num_examples: 63
download_size: 2560460
dataset_size: 2702702
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
theoracle/commodore64 | ---
language:
- en
license: apache-2.0
size_categories:
- 1K<n<10K
task_categories:
- table-question-answering
- text-generation
pretty_name: Commodore 64 Dataset based on Commodore 64 Programmer's Reference Guide
dataset_info:
features:
- name: chunks
dtype: string
- name: summary
dtype: string
- name: question
dtype: string
splits:
- name: train
num_bytes: 1511321
num_examples: 1832
download_size: 719434
dataset_size: 1511321
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
tags:
- commodore64
- c64
- 8bitcomputers
---
# Dataset Card for Commodore 64 Dataset
## Dataset Details
### Dataset Description
- **Curated by:** [Curator's Name or Institution]
- **Language(s) (NLP):** English
- **License:** Apache-2.0
This dataset is derived from the "Commodore 64 Programmer's Reference Guide," encompassing text chunks from the book, their summarized versions, and questions derived from the summaries. It aims to facilitate research and development in natural language processing tasks such as text summarization, question generation, and question answering, particularly in the context of programming and computer science historical texts.
### Dataset Sources
- **Repository:** [Link to the dataset repository on Hugging Face]
## Uses
### Direct Use
This dataset is intended for:
- Training and evaluating text summarization models.
- Developing and testing question answering systems.
- Generating questions from technical text summaries.
### Out-of-Scope Use
This dataset might not be suitable for:
- Tasks requiring modern computing concepts not covered in the Commodore 64 reference guide.
- Non-English language NLP tasks.
## Dataset Structure
### Features
The dataset comprises three main features:
- `chunks`: Text excerpts from the "Commodore 64 Programmer's Reference Guide."
- `summary`: Summarized versions of the chunks.
- `question`: Questions formulated based on the summaries.
### Splits
Currently, the dataset includes only a `train` split with 1,832 examples.
## Dataset Creation
### Curation Rationale
The dataset was created to provide a unique resource for exploring NLP tasks related to technical text processing, summarization, and question generation/answering, leveraging the historical and technical significance of the Commodore 64 programming domain.
### Source Data
#### Data Collection and Processing
The data was extracted from the "Commodore 64 Programmer's Reference Guide," summarized, and used to formulate questions. [Details on the processing methods, tools used, or any transformations applied should be added here.]
## Bias, Risks, and Limitations
The dataset is based on a specific historical computing context and may contain biases inherent to the original text. Users should be aware of its historical nature and the potential for outdated or context-specific information that may not generalize well to modern computing contexts.
## Citation
**APA:** [Citation in APA format]
**BibTeX:** [Citation in BibTeX format]
## Dataset Card Authors
- [Author Name or Institution]
## Dataset Card Contact
- [Contact Information]
|
maximoss/sick-fr-mt | ---
license: cc-by-nc-sa-4.0
task_categories:
- text-classification
task_ids:
- natural-language-inference
- multi-input-text-classification
language:
- fr
size_categories:
- 1K<n<10K
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This repository contains a machine-translated French version of [SICK](https://huggingface.co/datasets/sick) (Sentences Involving Compositional Knowldedge) dataset. The goal is to predict textual entailment (does sentence A
imply/contradict/neither sentence B), which is a classification task (given two sentences, predict one of three labels). Apart from machine translating the sentence pairs, the rest of information (pair ID, labels, source dataset of each sentence, train/dev/test subset partition) has been left intact as in the original English dataset.
The dataset is here formatted in a similar manner (TSV format) as the widely used [XNLI](https://huggingface.co/datasets/xnli) dataset for convenience.
The machine translation produced in the present repository should be of pretty decent quality, given the average short length of the sentences in SICK dataset.
### Supported Tasks and Leaderboards
This dataset can be used for the task of Natural Language Inference (NLI), also known as Recognizing Textual Entailment (RTE), which is a sentence-pair classification task.
## Dataset Structure
### Data Fields
- `pair_ID`: Sentence pair ID.
- `sentence_A`: Sentence A, also known as premise in other NLI datasets.
- `sentence_B`: Sentence B, also known as hypothesis in other NLI datasets.
- `entailment_label`: textual entailment gold label (NEUTRAL, ENTAILMENT, or CONTRADICTION).
- `entailment_AB`: Entailment label for the A-B order (A_neutral_B, A_entails_B, or A_contradicts_B).
- `entailment_BA`: Entailment label for the B-A order (B_neutral_A, B_entails_A, or B_contradicts_A).
- `original_SICK_sentence_A`: The original premise from the English source dataset.
- `original_SICK_sentence_B`: The original hypothesis from the English source dataset.
- `sentence_A_dataset`: The dataset from which the original sentence A was extracted (FLICKR vs. SEMEVAL).
- `sentence_B_dataset`: The dataset from which the original sentence B was extracted (FLICKR vs. SEMEVAL).
### Data Splits
| name |Entailment|Neutral|Contradiction|Total|
|--------|---------:|------:|------------:|------------:|
|train | 1274 | 2524 | 641 | 4439 |
|validation | 143 | 281 | 71 | 495 |
|test | 1404 | 2790 | 712 | 4906 |
For the A-B order:
| name |A_entails_B|A_neutral_B|A_contradicts_B|
|--------|---------:|------:|------------:|
|train | 1274 | 2381 | 784 |
|validation | 143 | 266 | 86 |
|test | 1404 | 2621 | 881 |
For the B-A order:
| name |B_entails_A|B_neutral_A|B_contradicts_A|
|--------|---------:|------:|------------:|
|train | 606 | 3072 | 761 |
|validation | 84 | 329 | 82 |
|test | 610 | 3431 | 865 |
## Dataset Creation
The dataset was machine translated from English to French using the latest neural machine translation [opus-mt-tc-big](https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-en-fr) model available for French.
The translation of the sentences was carried out on November 26th, 2023.
## Additional Information
### Citation Information
**BibTeX:**
````BibTeX
@inproceedings{marelli-etal-2014-sick,
title = "A {SICK} cure for the evaluation of compositional distributional semantic models",
author = "Marelli, Marco and
Menini, Stefano and
Baroni, Marco and
Bentivogli, Luisa and
Bernardi, Raffaella and
Zamparelli, Roberto",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/363_Paper.pdf",
pages = "216--223",
abstract = "Shared and internationally recognized benchmarks are fundamental for the development of any computational system. We aim to help the research community working on compositional distributional semantic models (CDSMs) by providing SICK (Sentences Involving Compositional Knowldedge), a large size English benchmark tailored for them. SICK consists of about 10,000 English sentence pairs that include many examples of the lexical, syntactic and semantic phenomena that CDSMs are expected to account for, but do not require dealing with other aspects of existing sentential data sets (idiomatic multiword expressions, named entities, telegraphic language) that are not within the scope of CDSMs. By means of crowdsourcing techniques, each pair was annotated for two crucial semantic tasks: relatedness in meaning (with a 5-point rating scale as gold score) and entailment relation between the two elements (with three possible gold labels: entailment, contradiction, and neutral). The SICK data set was used in SemEval-2014 Task 1, and it freely available for research purposes.",
}
@inproceedings{tiedemann-thottingal-2020-opus,
title = "{OPUS}-{MT} {--} Building open translation services for the World",
author = {Tiedemann, J{\"o}rg and
Thottingal, Santhosh},
booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
month = nov,
year = "2020",
address = "Lisboa, Portugal",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/2020.eamt-1.61",
pages = "479--480",
abstract = "This paper presents OPUS-MT a project that focuses on the development of free resources and tools for machine translation. The current status is a repository of over 1,000 pre-trained neural machine translation models that are ready to be launched in on-line translation services. For this we also provide open source implementations of web applications that can run efficiently on average desktop hardware with a straightforward setup and installation.",
}
````
**ACL:**
Marco Marelli, Stefano Menini, Marco Baroni, Luisa Bentivogli, Raffaella Bernardi, and Roberto Zamparelli. 2014. [A SICK cure for the evaluation of compositional distributional semantic models](http://www.lrec-conf.org/proceedings/lrec2014/pdf/363_Paper.pdf). In *Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)*, pages 216–223, Reykjavik, Iceland. European Language Resources Association (ELRA).
Jörg Tiedemann and Santhosh Thottingal. 2020. [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61). In *Proceedings of the 22nd Annual Conference of the European Association for Machine Translation*, pages 479–480, Lisboa, Portugal. European Association for Machine Translation.
### Acknowledgements
This translation of the original dataset was done as part of a research project supported by the Defence Innovation Agency (AID) of the Directorate General of Armament (DGA) of the French Ministry of Armed Forces, and by the ICO, _Institut Cybersécurité Occitanie_, funded by Région Occitanie, France. |
akoukas/DFD | ---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': Generated
'1': Human
splits:
- name: train
num_bytes: 395653890.0
num_examples: 319071
download_size: 242403509
dataset_size: 395653890.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
heliosprime/twitter_dataset_1713202348 | ---
dataset_info:
features:
- name: id
dtype: string
- name: tweet_content
dtype: string
- name: user_name
dtype: string
- name: user_id
dtype: string
- name: created_at
dtype: string
- name: url
dtype: string
- name: favourite_count
dtype: int64
- name: scraped_at
dtype: string
- name: image_urls
dtype: string
splits:
- name: train
num_bytes: 23320
num_examples: 60
download_size: 20660
dataset_size: 23320
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "twitter_dataset_1713202348"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Roge2024/Luciano | ---
license: openrail
---
|
havens2/strategyQA_test | ---
dataset_info:
features:
- name: qid
dtype: string
- name: question
dtype: string
splits:
- name: train
num_bytes: 41161
num_examples: 490
download_size: 0
dataset_size: 41161
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "strategyQA_test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Richardol1219/RSNA-PE-Training | ---
license: openrail
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
StudyInstanceUID, SeriesInstanceUID, SOPInstanceUID, pe_present_on_image, negative_exam_for_pe, qa_motion, qa_contrast, flow_artifact
### 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] |
jungledude23/llama-subtitle-hallucinations | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 36236776
num_examples: 16528
download_size: 6499965
dataset_size: 36236776
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
AdapterOcean/langchain-standardized_cluster_0_std | ---
dataset_info:
features:
- name: message
dtype: string
- name: message_type
dtype: string
- name: message_id
dtype: int64
- name: conversation_id
dtype: int64
- name: cluster
dtype: float64
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 4052132
num_examples: 1986
download_size: 1803542
dataset_size: 4052132
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "langchain-standardized_cluster_0_std"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
ai4bharat/kathbath | ---
annotations_creators:
- expert-generated
language_bcp47:
- bn,gu,kn,hi,ml,mr,or,pa,sn,ta,te,ur
language_creators:
- machine-generated
license:
- mit
multilinguality:
- multilingual
pretty_name: Kathbath
size_categories:
- 100K<n<1M
source_datasets:
- original
tags: []
task_categories:
- automatic-speech-recognition
task_ids: []
---
# Dataset Card for Kathbath
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:https://ai4bharat.org/indic-superb**
- **Repository:https://github.com/AI4Bharat/IndicSUPERB**
- **Paper:https://arxiv.org/pdf/2208.11761.pdf**
- **Point of Contact:tahirjmakhdoomi@gmail.com**
### Dataset Summary
Kathbath is an human-labeled ASR dataset containing 1,684 hours of labelled speech data across 12 Indian languages from 1,218 contributors located in 203 districts in India
### Languages
- Bengali
- Gujarati
- Kannada
- Hindi
- Malayalam
- Marathi
- Odia
- Punjabi
- Sanskrit
- Tamil
- Telugu
- Urdu
## Dataset Structure
```
Audio Data
data
├── bengali
│ ├── <split_name>
│ │ ├── 844424931537866-594-f.m4a
│ │ ├── 844424931029859-973-f.m4a
│ │ ├── ...
├── gujarati
├── ...
Transcripts
data
├── bengali
│ ├── <split_name>
│ │ ├── transcription_n2w.txt
├── gujarati
├── ...
```
### Licensing Information
The IndicSUPERB dataset is released under this licensing scheme:
- We do not own any of the raw text used in creating this dataset.
- The text data comes from the IndicCorp dataset which is a crawl of publicly available websites.
- The audio transcriptions of the raw text and labelled annotations of the datasets have been created by us.
- We license the actual packaging of all this data under the Creative Commons CC0 license (“no rights reserved”).
- To the extent possible under law, AI4Bharat has waived all copyright and related or neighboring rights to the IndicSUPERB dataset.
- This work is published from: India.
### Citation Information
```
@misc{https://doi.org/10.48550/arxiv.2208.11761,
doi = {10.48550/ARXIV.2208.11761},
url = {https://arxiv.org/abs/2208.11761},
author = {Javed, Tahir and Bhogale, Kaushal Santosh and Raman, Abhigyan and Kunchukuttan, Anoop and Kumar, Pratyush and Khapra, Mitesh M.},
title = {IndicSUPERB: A Speech Processing Universal Performance Benchmark for Indian languages},
publisher = {arXiv},
year = {2022},
copyright = {arXiv.org perpetual, non-exclusive license}
}
```
### Contributions
We would like to thank the Ministry of Electronics and Information Technology (MeitY) of the Government of India and the Centre for Development of Advanced Computing (C-DAC), Pune for generously supporting this work and providing us access to multiple GPU nodes on the Param Siddhi Supercomputer. We would like to thank the EkStep Foundation and Nilekani Philanthropies for their generous grant which went into hiring human resources as well as cloud resources needed for this work. We would like to thank DesiCrew for connecting us to native speakers for collecting data. We would like to thank Vivek Seshadri from Karya Inc. for helping setup the data collection infrastructure on the Karya platform. We would like to thank all the members of AI4Bharat team in helping create the Query by Example dataset. |
ZelaAI/minipile_512_tiny | ---
dataset_info:
features:
- name: tokens
sequence: int64
splits:
- name: train
num_bytes: 11229400
num_examples: 2738
download_size: 3003789
dataset_size: 11229400
---
# Dataset Card for "minipile_512_tiny"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
seonglae/wiki_dpr_token | ---
dataset_info:
config_name: gpt-4
features:
- name: id
dtype: string
- name: title
dtype: string
- name: text
dtype: string
- name: token_length
dtype: int64
- name: text_length
dtype: int64
splits:
- name: train
num_bytes: 14112430156
num_examples: 21015300
download_size: 7635924562
dataset_size: 14112430156
configs:
- config_name: gpt-4
data_files:
- split: train
path: gpt-4/train-*
---
# Dataset Card for "wiki_dpr_token"
## Distribution
```ts
[
{ // Token length
'~128': 2625007,
'128~256': 18370607,
'256~512': 19066,
'512~1024': 571,
'1024~2048': 47,
'2048~4096': 2,
'4096~8192': 0,
'8192~16384': 0,
'16384~32768': 0,
'32768~65536': 0,
'65536~128000': 0,
'128000~': 0,
},
{ // Text length
'~512': 86519,
'512~1024': 20927180,
'1024~2048': 1557,
'2048~4096': 43,
'4096~8192': 1,
'8192~16384': 0,
'16384~32768': 0,
'32768~65536': 0,
'65536~': 0,
},
{ // Token distribution
'~128': '12.49%',
'128~256': '87.42%',
'256~512': '0.09%',
'512~1024': '0.00%',
'1024~2048': '0.00%',
'2048~4096': '0.00%',
'4096~8192': '0.00%',
'8192~16384': '0.00%',
'16384~32768': '0.00%',
'32768~65536': '0.00%',
'65536~128000': '0.00%',
'128000~': '0.00%',
},
{ // Text distribution
'~512': '0.41%',
'512~1024': '99.58%',
'1024~2048': '0.01%',
'2048~4096': '0.00%',
'4096~8192': '0.00%',
'8192~16384': '0.00%',
'16384~32768': '0.00%',
'32768~65536': '0.00%',
'65536~': '0.00%',
}
]
``` |
TashaSkyUp/random_midpoint_displacement_fractal | ---
license: mit
pretty_name: random midpoint displacement fractal images 1024x1024 png
size_categories:
- n<1K
---
1024x1024px PNG encoded, scale=0.1, roughness=1.0
each map was then processed with 100 iterations of rain erosion simulation (e99 directory)
for further explanation please see https://en.wikipedia.org/wiki/Diamond-square_algorithm
The idea was first introduced by Fournier, Fussell and Carpenter at SIGGRAPH in 1982
|
alayaran/bodo-pos-conll | ---
license: mit
---
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/1d41603d | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 186
num_examples: 10
download_size: 1334
dataset_size: 186
---
# Dataset Card for "1d41603d"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Seanxh/twitter_dataset_1713010899 | ---
dataset_info:
features:
- name: id
dtype: string
- name: tweet_content
dtype: string
- name: user_name
dtype: string
- name: user_id
dtype: string
- name: created_at
dtype: string
- name: url
dtype: string
- name: favourite_count
dtype: int64
- name: scraped_at
dtype: string
- name: image_urls
dtype: string
splits:
- name: train
num_bytes: 168158
num_examples: 420
download_size: 58513
dataset_size: 168158
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
autoevaluate/autoeval-staging-eval-project-90bfb636-8600-4a27-9171-c297c5e7f496-3331 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. |
sayakpaul/coco-30-val-2014 | ---
dataset_info:
features:
- name: image
dtype: image
- name: caption
dtype: string
splits:
- name: train
num_bytes: 4993980142.0
num_examples: 30000
download_size: 4898811398
dataset_size: 4993980142.0
---
# Dataset Card for "coco-30-val-2014"
This is 30k randomly sampled image-captioned pairs from the [COCO](https://cocodataset.org/) 2014 `val` split. This is useful for image generation benchmarks (FID, CLIPScore, etc.).
Refer to the gist to know how the dataset was created: https://gist.github.com/sayakpaul/0c4435a1df6eb6193f824f9198cabaa5. |
irds/neuclir_1_fa | ---
pretty_name: '`neuclir/1/fa`'
viewer: false
source_datasets: []
task_categories:
- text-retrieval
---
# Dataset Card for `neuclir/1/fa`
The `neuclir/1/fa` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/neuclir#neuclir/1/fa).
# Data
This dataset provides:
- `docs` (documents, i.e., the corpus); count=2,232,016
## Usage
```python
from datasets import load_dataset
docs = load_dataset('irds/neuclir_1_fa', 'docs')
for record in docs:
record # {'doc_id': ..., 'title': ..., 'text': ..., 'url': ..., 'time': ..., 'cc_file': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
|
bigscience/P3 | ---
annotations_creators:
- crowdsourced
- expert-generated
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
size_categories:
- 100M<n<1B
task_categories:
- other
pretty_name: P3
dataset_info:
- config_name: adversarial_qa_dbert_answer_the_following_q
features:
- name: inputs
sequence: int32
- name: inputs_pretokenized
dtype: string
- name: targets
sequence: int32
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dtype: string
splits:
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num_examples: 10000
- name: validation
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num_examples: 1000
download_size: 6288641
dataset_size: 20104787
- config_name: adversarial_qa_dbert_based_on
features:
- name: inputs
sequence: int32
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dtype: string
- name: targets
sequence: int32
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dtype: string
splits:
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num_examples: 10000
- name: validation
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num_examples: 1000
download_size: 6206744
dataset_size: 19298119
- config_name: adversarial_qa_dbert_generate_question
features:
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sequence: int32
- name: inputs_pretokenized
dtype: string
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sequence: int32
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dtype: string
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num_examples: 10000
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num_examples: 1000
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num_examples: 1000
download_size: 5882604
dataset_size: 22331993
- config_name: adversarial_qa_dbert_question_context_answer
features:
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sequence: int32
- name: inputs_pretokenized
dtype: string
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sequence: int32
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dtype: string
splits:
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num_examples: 1000
download_size: 6180363
dataset_size: 18505803
- config_name: adversarial_qa_dbert_tell_what_it_is
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sequence: int32
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download_size: 6276720
dataset_size: 19532695
- config_name: adversarial_qa_dbidaf_answer_the_following_q
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- config_name: adversarial_qa_dbidaf_based_on
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num_examples: 1000
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dataset_size: 19264354
- config_name: adversarial_qa_dbidaf_generate_question
features:
- name: inputs
sequence: int32
- name: inputs_pretokenized
dtype: string
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sequence: int32
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dtype: string
splits:
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num_examples: 10000
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num_examples: 1000
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num_examples: 1000
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dataset_size: 22265275
- config_name: adversarial_qa_dbidaf_question_context_answer
features:
- name: inputs
sequence: int32
- name: inputs_pretokenized
dtype: string
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- config_name: xsum_DOC_boils_down_to_simple_idea_that
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- config_name: yelp_review_full_based_on_that
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- config_name: yelp_review_full_format_rating
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configs:
- config_name: adversarial_qa_dbert_answer_the_following_q
data_files:
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path: adversarial_qa_dbert_answer_the_following_q/train-*
- split: validation
path: adversarial_qa_dbert_answer_the_following_q/validation-*
- config_name: adversarial_qa_dbert_based_on
data_files:
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path: adversarial_qa_dbert_based_on/train-*
- split: validation
path: adversarial_qa_dbert_based_on/validation-*
- config_name: adversarial_qa_dbert_generate_question
data_files:
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path: adversarial_qa_dbert_generate_question/train-*
- split: validation
path: adversarial_qa_dbert_generate_question/validation-*
- split: test
path: adversarial_qa_dbert_generate_question/test-*
- config_name: adversarial_qa_dbert_question_context_answer
data_files:
- split: train
path: adversarial_qa_dbert_question_context_answer/train-*
- split: validation
path: adversarial_qa_dbert_question_context_answer/validation-*
- config_name: adversarial_qa_dbert_tell_what_it_is
data_files:
- split: train
path: adversarial_qa_dbert_tell_what_it_is/train-*
- split: validation
path: adversarial_qa_dbert_tell_what_it_is/validation-*
- config_name: adversarial_qa_dbidaf_answer_the_following_q
data_files:
- split: train
path: adversarial_qa_dbidaf_answer_the_following_q/train-*
- split: validation
path: adversarial_qa_dbidaf_answer_the_following_q/validation-*
- config_name: adversarial_qa_dbidaf_based_on
data_files:
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path: adversarial_qa_dbidaf_based_on/train-*
- split: validation
path: adversarial_qa_dbidaf_based_on/validation-*
- config_name: adversarial_qa_dbidaf_generate_question
data_files:
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path: adversarial_qa_dbidaf_generate_question/train-*
- split: validation
path: adversarial_qa_dbidaf_generate_question/validation-*
- split: test
path: adversarial_qa_dbidaf_generate_question/test-*
- config_name: adversarial_qa_dbidaf_question_context_answer
data_files:
- split: train
path: adversarial_qa_dbidaf_question_context_answer/train-*
- split: validation
path: adversarial_qa_dbidaf_question_context_answer/validation-*
- config_name: adversarial_qa_dbidaf_tell_what_it_is
data_files:
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path: adversarial_qa_dbidaf_tell_what_it_is/train-*
- split: validation
path: adversarial_qa_dbidaf_tell_what_it_is/validation-*
- config_name: adversarial_qa_droberta_answer_the_following_q
data_files:
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path: adversarial_qa_droberta_answer_the_following_q/train-*
- split: validation
path: adversarial_qa_droberta_answer_the_following_q/validation-*
- config_name: adversarial_qa_droberta_based_on
data_files:
- split: train
path: adversarial_qa_droberta_based_on/train-*
- split: validation
path: adversarial_qa_droberta_based_on/validation-*
- config_name: adversarial_qa_droberta_generate_question
data_files:
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path: adversarial_qa_droberta_generate_question/train-*
- split: validation
path: adversarial_qa_droberta_generate_question/validation-*
- split: test
path: adversarial_qa_droberta_generate_question/test-*
- config_name: adversarial_qa_droberta_question_context_answer
data_files:
- split: train
path: adversarial_qa_droberta_question_context_answer/train-*
- split: validation
path: adversarial_qa_droberta_question_context_answer/validation-*
- config_name: adversarial_qa_droberta_tell_what_it_is
data_files:
- split: train
path: adversarial_qa_droberta_tell_what_it_is/train-*
- split: validation
path: adversarial_qa_droberta_tell_what_it_is/validation-*
- config_name: ag_news_classify
data_files:
- split: train
path: ag_news_classify/train-*
- split: test
path: ag_news_classify/test-*
- config_name: ag_news_classify_question_first
data_files:
- split: train
path: ag_news_classify_question_first/train-*
- split: test
path: ag_news_classify_question_first/test-*
- config_name: ag_news_classify_with_choices
data_files:
- split: train
path: ag_news_classify_with_choices/train-*
- split: test
path: ag_news_classify_with_choices/test-*
- config_name: ag_news_classify_with_choices_question_first
data_files:
- split: train
path: ag_news_classify_with_choices_question_first/train-*
- split: test
path: ag_news_classify_with_choices_question_first/test-*
- config_name: ag_news_recommend
data_files:
- split: train
path: ag_news_recommend/train-*
- split: test
path: ag_news_recommend/test-*
- config_name: ag_news_which_section
data_files:
- split: train
path: ag_news_which_section/train-*
- split: test
path: ag_news_which_section/test-*
- config_name: ag_news_which_section_choices
data_files:
- split: train
path: ag_news_which_section_choices/train-*
- split: test
path: ag_news_which_section_choices/test-*
- config_name: ai2_arc_ARC_Challenge_heres_a_problem
data_files:
- split: train
path: ai2_arc_ARC_Challenge_heres_a_problem/train-*
- split: validation
path: ai2_arc_ARC_Challenge_heres_a_problem/validation-*
- split: test
path: ai2_arc_ARC_Challenge_heres_a_problem/test-*
- config_name: ai2_arc_ARC_Challenge_i_am_hesitating
data_files:
- split: train
path: ai2_arc_ARC_Challenge_i_am_hesitating/train-*
- split: validation
path: ai2_arc_ARC_Challenge_i_am_hesitating/validation-*
- split: test
path: ai2_arc_ARC_Challenge_i_am_hesitating/test-*
- config_name: ai2_arc_ARC_Challenge_multiple_choice
data_files:
- split: train
path: ai2_arc_ARC_Challenge_multiple_choice/train-*
- split: validation
path: ai2_arc_ARC_Challenge_multiple_choice/validation-*
- split: test
path: ai2_arc_ARC_Challenge_multiple_choice/test-*
- config_name: ai2_arc_ARC_Challenge_pick_false_options
data_files:
- split: train
path: ai2_arc_ARC_Challenge_pick_false_options/train-*
- split: validation
path: ai2_arc_ARC_Challenge_pick_false_options/validation-*
- split: test
path: ai2_arc_ARC_Challenge_pick_false_options/test-*
- config_name: ai2_arc_ARC_Challenge_pick_the_most_correct_option
data_files:
- split: train
path: ai2_arc_ARC_Challenge_pick_the_most_correct_option/train-*
- split: validation
path: ai2_arc_ARC_Challenge_pick_the_most_correct_option/validation-*
- split: test
path: ai2_arc_ARC_Challenge_pick_the_most_correct_option/test-*
- config_name: ai2_arc_ARC_Challenge_qa_options
data_files:
- split: train
path: ai2_arc_ARC_Challenge_qa_options/train-*
- split: validation
path: ai2_arc_ARC_Challenge_qa_options/validation-*
- split: test
path: ai2_arc_ARC_Challenge_qa_options/test-*
- config_name: ai2_arc_ARC_Easy_heres_a_problem
data_files:
- split: train
path: ai2_arc_ARC_Easy_heres_a_problem/train-*
- split: validation
path: ai2_arc_ARC_Easy_heres_a_problem/validation-*
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path: ai2_arc_ARC_Easy_heres_a_problem/test-*
- config_name: ai2_arc_ARC_Easy_i_am_hesitating
data_files:
- split: train
path: ai2_arc_ARC_Easy_i_am_hesitating/train-*
- split: validation
path: ai2_arc_ARC_Easy_i_am_hesitating/validation-*
- split: test
path: ai2_arc_ARC_Easy_i_am_hesitating/test-*
- config_name: ai2_arc_ARC_Easy_multiple_choice
data_files:
- split: train
path: ai2_arc_ARC_Easy_multiple_choice/train-*
- split: validation
path: ai2_arc_ARC_Easy_multiple_choice/validation-*
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path: ai2_arc_ARC_Easy_multiple_choice/test-*
- config_name: ai2_arc_ARC_Easy_pick_false_options
data_files:
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path: ai2_arc_ARC_Easy_pick_false_options/train-*
- split: validation
path: ai2_arc_ARC_Easy_pick_false_options/validation-*
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path: ai2_arc_ARC_Easy_pick_false_options/test-*
- config_name: ai2_arc_ARC_Easy_pick_the_most_correct_option
data_files:
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path: ai2_arc_ARC_Easy_pick_the_most_correct_option/train-*
- split: validation
path: ai2_arc_ARC_Easy_pick_the_most_correct_option/validation-*
- split: test
path: ai2_arc_ARC_Easy_pick_the_most_correct_option/test-*
- config_name: ai2_arc_ARC_Easy_qa_options
data_files:
- split: train
path: ai2_arc_ARC_Easy_qa_options/train-*
- split: validation
path: ai2_arc_ARC_Easy_qa_options/validation-*
- split: test
path: ai2_arc_ARC_Easy_qa_options/test-*
- config_name: amazon_polarity_Is_this_product_review_positive
data_files:
- split: train
path: amazon_polarity_Is_this_product_review_positive/train-*
- split: test
path: amazon_polarity_Is_this_product_review_positive/test-*
- config_name: amazon_polarity_Is_this_review
data_files:
- split: train
path: amazon_polarity_Is_this_review/train-*
- split: test
path: amazon_polarity_Is_this_review/test-*
- config_name: amazon_polarity_Is_this_review_negative
data_files:
- split: train
path: amazon_polarity_Is_this_review_negative/train-*
- split: test
path: amazon_polarity_Is_this_review_negative/test-*
- config_name: amazon_polarity_User_recommend_this_product
data_files:
- split: train
path: amazon_polarity_User_recommend_this_product/train-*
- split: test
path: amazon_polarity_User_recommend_this_product/test-*
- config_name: amazon_polarity_convey_negative_or_positive_sentiment
data_files:
- split: train
path: amazon_polarity_convey_negative_or_positive_sentiment/train-*
- split: test
path: amazon_polarity_convey_negative_or_positive_sentiment/test-*
- config_name: amazon_polarity_flattering_or_not
data_files:
- split: train
path: amazon_polarity_flattering_or_not/train-*
- split: test
path: amazon_polarity_flattering_or_not/test-*
- config_name: amazon_polarity_negative_or_positive_tone
data_files:
- split: train
path: amazon_polarity_negative_or_positive_tone/train-*
- split: test
path: amazon_polarity_negative_or_positive_tone/test-*
- config_name: amazon_polarity_user_satisfied
data_files:
- split: train
path: amazon_polarity_user_satisfied/train-*
- split: test
path: amazon_polarity_user_satisfied/test-*
- config_name: amazon_polarity_would_you_buy
data_files:
- split: train
path: amazon_polarity_would_you_buy/train-*
- split: test
path: amazon_polarity_would_you_buy/test-*
- config_name: anli_GPT_3_style_r1
data_files:
- split: train
path: anli_GPT_3_style_r1/train-*
- split: validation
path: anli_GPT_3_style_r1/validation-*
- split: test
path: anli_GPT_3_style_r1/test-*
- config_name: anli_GPT_3_style_r1_score_eval
data_files:
- split: train
path: anli_GPT_3_style_r1_score_eval/train-*
- split: validation
path: anli_GPT_3_style_r1_score_eval/validation-*
- split: test
path: anli_GPT_3_style_r1_score_eval/test-*
- config_name: anli_GPT_3_style_r2
data_files:
- split: train
path: anli_GPT_3_style_r2/train-*
- split: validation
path: anli_GPT_3_style_r2/validation-*
- split: test
path: anli_GPT_3_style_r2/test-*
- config_name: anli_GPT_3_style_r2_score_eval
data_files:
- split: train
path: anli_GPT_3_style_r2_score_eval/train-*
- split: validation
path: anli_GPT_3_style_r2_score_eval/validation-*
- split: test
path: anli_GPT_3_style_r2_score_eval/test-*
- config_name: anli_GPT_3_style_r3
data_files:
- split: train
path: anli_GPT_3_style_r3/train-*
- split: validation
path: anli_GPT_3_style_r3/validation-*
- split: test
path: anli_GPT_3_style_r3/test-*
- config_name: anli_GPT_3_style_r3_score_eval
data_files:
- split: train
path: anli_GPT_3_style_r3_score_eval/train-*
- split: validation
path: anli_GPT_3_style_r3_score_eval/validation-*
- split: test
path: anli_GPT_3_style_r3_score_eval/test-*
- config_name: anli_MNLI_crowdsource_r1
data_files:
- split: train
path: anli_MNLI_crowdsource_r1/train-*
- split: validation
path: anli_MNLI_crowdsource_r1/validation-*
- split: test
path: anli_MNLI_crowdsource_r1/test-*
- config_name: anli_MNLI_crowdsource_r1_score_eval
data_files:
- split: train
path: anli_MNLI_crowdsource_r1_score_eval/train-*
- split: validation
path: anli_MNLI_crowdsource_r1_score_eval/validation-*
- split: test
path: anli_MNLI_crowdsource_r1_score_eval/test-*
- config_name: anli_MNLI_crowdsource_r2
data_files:
- split: train
path: anli_MNLI_crowdsource_r2/train-*
- split: validation
path: anli_MNLI_crowdsource_r2/validation-*
- split: test
path: anli_MNLI_crowdsource_r2/test-*
- config_name: anli_MNLI_crowdsource_r2_score_eval
data_files:
- split: train
path: anli_MNLI_crowdsource_r2_score_eval/train-*
- split: validation
path: anli_MNLI_crowdsource_r2_score_eval/validation-*
- split: test
path: anli_MNLI_crowdsource_r2_score_eval/test-*
- config_name: anli_MNLI_crowdsource_r3
data_files:
- split: train
path: anli_MNLI_crowdsource_r3/train-*
- split: validation
path: anli_MNLI_crowdsource_r3/validation-*
- split: test
path: anli_MNLI_crowdsource_r3/test-*
- config_name: anli_MNLI_crowdsource_r3_score_eval
data_files:
- split: train
path: anli_MNLI_crowdsource_r3_score_eval/train-*
- split: validation
path: anli_MNLI_crowdsource_r3_score_eval/validation-*
- split: test
path: anli_MNLI_crowdsource_r3_score_eval/test-*
- config_name: anli_always_sometimes_never_r1
data_files:
- split: train
path: anli_always_sometimes_never_r1/train-*
- split: validation
path: anli_always_sometimes_never_r1/validation-*
- split: test
path: anli_always_sometimes_never_r1/test-*
- config_name: anli_always_sometimes_never_r1_score_eval
data_files:
- split: train
path: anli_always_sometimes_never_r1_score_eval/train-*
- split: validation
path: anli_always_sometimes_never_r1_score_eval/validation-*
- split: test
path: anli_always_sometimes_never_r1_score_eval/test-*
- config_name: anli_always_sometimes_never_r2
data_files:
- split: train
path: anli_always_sometimes_never_r2/train-*
- split: validation
path: anli_always_sometimes_never_r2/validation-*
- split: test
path: anli_always_sometimes_never_r2/test-*
- config_name: anli_always_sometimes_never_r2_score_eval
data_files:
- split: train
path: anli_always_sometimes_never_r2_score_eval/train-*
- split: validation
path: anli_always_sometimes_never_r2_score_eval/validation-*
- split: test
path: anli_always_sometimes_never_r2_score_eval/test-*
- config_name: anli_always_sometimes_never_r3
data_files:
- split: train
path: anli_always_sometimes_never_r3/train-*
- split: validation
path: anli_always_sometimes_never_r3/validation-*
- split: test
path: anli_always_sometimes_never_r3/test-*
- config_name: anli_always_sometimes_never_r3_score_eval
data_files:
- split: train
path: anli_always_sometimes_never_r3_score_eval/train-*
- split: validation
path: anli_always_sometimes_never_r3_score_eval/validation-*
- split: test
path: anli_always_sometimes_never_r3_score_eval/test-*
- config_name: anli_based_on_the_previous_passage_r1
data_files:
- split: train
path: anli_based_on_the_previous_passage_r1/train-*
- split: validation
path: anli_based_on_the_previous_passage_r1/validation-*
- split: test
path: anli_based_on_the_previous_passage_r1/test-*
- config_name: anli_based_on_the_previous_passage_r1_score_eval
data_files:
- split: train
path: anli_based_on_the_previous_passage_r1_score_eval/train-*
- split: validation
path: anli_based_on_the_previous_passage_r1_score_eval/validation-*
- split: test
path: anli_based_on_the_previous_passage_r1_score_eval/test-*
- config_name: anli_based_on_the_previous_passage_r2
data_files:
- split: train
path: anli_based_on_the_previous_passage_r2/train-*
- split: validation
path: anli_based_on_the_previous_passage_r2/validation-*
- split: test
path: anli_based_on_the_previous_passage_r2/test-*
- config_name: anli_based_on_the_previous_passage_r2_score_eval
data_files:
- split: train
path: anli_based_on_the_previous_passage_r2_score_eval/train-*
- split: validation
path: anli_based_on_the_previous_passage_r2_score_eval/validation-*
- split: test
path: anli_based_on_the_previous_passage_r2_score_eval/test-*
- config_name: anli_based_on_the_previous_passage_r3
data_files:
- split: train
path: anli_based_on_the_previous_passage_r3/train-*
- split: validation
path: anli_based_on_the_previous_passage_r3/validation-*
- split: test
path: anli_based_on_the_previous_passage_r3/test-*
- config_name: anli_based_on_the_previous_passage_r3_score_eval
data_files:
- split: train
path: anli_based_on_the_previous_passage_r3_score_eval/train-*
- split: validation
path: anli_based_on_the_previous_passage_r3_score_eval/validation-*
- split: test
path: anli_based_on_the_previous_passage_r3_score_eval/test-*
- config_name: anli_can_we_infer_r1
data_files:
- split: train
path: anli_can_we_infer_r1/train-*
- split: validation
path: anli_can_we_infer_r1/validation-*
- split: test
path: anli_can_we_infer_r1/test-*
- config_name: anli_can_we_infer_r1_score_eval
data_files:
- split: train
path: anli_can_we_infer_r1_score_eval/train-*
- split: validation
path: anli_can_we_infer_r1_score_eval/validation-*
- split: test
path: anli_can_we_infer_r1_score_eval/test-*
- config_name: anli_can_we_infer_r2
data_files:
- split: train
path: anli_can_we_infer_r2/train-*
- split: validation
path: anli_can_we_infer_r2/validation-*
- split: test
path: anli_can_we_infer_r2/test-*
- config_name: anli_can_we_infer_r2_score_eval
data_files:
- split: train
path: anli_can_we_infer_r2_score_eval/train-*
- split: validation
path: anli_can_we_infer_r2_score_eval/validation-*
- split: test
path: anli_can_we_infer_r2_score_eval/test-*
- config_name: anli_can_we_infer_r3
data_files:
- split: train
path: anli_can_we_infer_r3/train-*
- split: validation
path: anli_can_we_infer_r3/validation-*
- split: test
path: anli_can_we_infer_r3/test-*
- config_name: anli_can_we_infer_r3_score_eval
data_files:
- split: train
path: anli_can_we_infer_r3_score_eval/train-*
- split: validation
path: anli_can_we_infer_r3_score_eval/validation-*
- split: test
path: anli_can_we_infer_r3_score_eval/test-*
- config_name: anli_claim_true_false_inconclusive_r1
data_files:
- split: train
path: anli_claim_true_false_inconclusive_r1/train-*
- split: validation
path: anli_claim_true_false_inconclusive_r1/validation-*
- split: test
path: anli_claim_true_false_inconclusive_r1/test-*
- config_name: anli_claim_true_false_inconclusive_r1_score_eval
data_files:
- split: train
path: anli_claim_true_false_inconclusive_r1_score_eval/train-*
- split: validation
path: anli_claim_true_false_inconclusive_r1_score_eval/validation-*
- split: test
path: anli_claim_true_false_inconclusive_r1_score_eval/test-*
- config_name: anli_claim_true_false_inconclusive_r2
data_files:
- split: train
path: anli_claim_true_false_inconclusive_r2/train-*
- split: validation
path: anli_claim_true_false_inconclusive_r2/validation-*
- split: test
path: anli_claim_true_false_inconclusive_r2/test-*
- config_name: anli_claim_true_false_inconclusive_r2_score_eval
data_files:
- split: train
path: anli_claim_true_false_inconclusive_r2_score_eval/train-*
- split: validation
path: anli_claim_true_false_inconclusive_r2_score_eval/validation-*
- split: test
path: anli_claim_true_false_inconclusive_r2_score_eval/test-*
- config_name: anli_claim_true_false_inconclusive_r3
data_files:
- split: train
path: anli_claim_true_false_inconclusive_r3/train-*
- split: validation
path: anli_claim_true_false_inconclusive_r3/validation-*
- split: test
path: anli_claim_true_false_inconclusive_r3/test-*
- config_name: anli_claim_true_false_inconclusive_r3_score_eval
data_files:
- split: train
path: anli_claim_true_false_inconclusive_r3_score_eval/train-*
- split: validation
path: anli_claim_true_false_inconclusive_r3_score_eval/validation-*
- split: test
path: anli_claim_true_false_inconclusive_r3_score_eval/test-*
- config_name: anli_consider_always_sometimes_never_r1
data_files:
- split: train
path: anli_consider_always_sometimes_never_r1/train-*
- split: validation
path: anli_consider_always_sometimes_never_r1/validation-*
- split: test
path: anli_consider_always_sometimes_never_r1/test-*
- config_name: anli_consider_always_sometimes_never_r1_score_eval
data_files:
- split: train
path: anli_consider_always_sometimes_never_r1_score_eval/train-*
- split: validation
path: anli_consider_always_sometimes_never_r1_score_eval/validation-*
- split: test
path: anli_consider_always_sometimes_never_r1_score_eval/test-*
- config_name: anli_consider_always_sometimes_never_r2
data_files:
- split: train
path: anli_consider_always_sometimes_never_r2/train-*
- split: validation
path: anli_consider_always_sometimes_never_r2/validation-*
- split: test
path: anli_consider_always_sometimes_never_r2/test-*
- config_name: anli_consider_always_sometimes_never_r2_score_eval
data_files:
- split: train
path: anli_consider_always_sometimes_never_r2_score_eval/train-*
- split: validation
path: anli_consider_always_sometimes_never_r2_score_eval/validation-*
- split: test
path: anli_consider_always_sometimes_never_r2_score_eval/test-*
- config_name: anli_consider_always_sometimes_never_r3
data_files:
- split: train
path: anli_consider_always_sometimes_never_r3/train-*
- split: validation
path: anli_consider_always_sometimes_never_r3/validation-*
- split: test
path: anli_consider_always_sometimes_never_r3/test-*
- config_name: anli_consider_always_sometimes_never_r3_score_eval
data_files:
- split: train
path: anli_consider_always_sometimes_never_r3_score_eval/train-*
- split: validation
path: anli_consider_always_sometimes_never_r3_score_eval/validation-*
- split: test
path: anli_consider_always_sometimes_never_r3_score_eval/test-*
- config_name: anli_does_it_follow_that_r1
data_files:
- split: train
path: anli_does_it_follow_that_r1/train-*
- split: validation
path: anli_does_it_follow_that_r1/validation-*
- split: test
path: anli_does_it_follow_that_r1/test-*
- config_name: anli_does_it_follow_that_r1_score_eval
data_files:
- split: train
path: anli_does_it_follow_that_r1_score_eval/train-*
- split: validation
path: anli_does_it_follow_that_r1_score_eval/validation-*
- split: test
path: anli_does_it_follow_that_r1_score_eval/test-*
- config_name: anli_does_it_follow_that_r2
data_files:
- split: train
path: anli_does_it_follow_that_r2/train-*
- split: validation
path: anli_does_it_follow_that_r2/validation-*
- split: test
path: anli_does_it_follow_that_r2/test-*
- config_name: anli_does_it_follow_that_r2_score_eval
data_files:
- split: train
path: anli_does_it_follow_that_r2_score_eval/train-*
- split: validation
path: anli_does_it_follow_that_r2_score_eval/validation-*
- split: test
path: anli_does_it_follow_that_r2_score_eval/test-*
- config_name: anli_does_it_follow_that_r3
data_files:
- split: train
path: anli_does_it_follow_that_r3/train-*
- split: validation
path: anli_does_it_follow_that_r3/validation-*
- split: test
path: anli_does_it_follow_that_r3/test-*
- config_name: anli_does_it_follow_that_r3_score_eval
data_files:
- split: train
path: anli_does_it_follow_that_r3_score_eval/train-*
- split: validation
path: anli_does_it_follow_that_r3_score_eval/validation-*
- split: test
path: anli_does_it_follow_that_r3_score_eval/test-*
- config_name: anli_does_this_imply_r1
data_files:
- split: train
path: anli_does_this_imply_r1/train-*
- split: validation
path: anli_does_this_imply_r1/validation-*
- split: test
path: anli_does_this_imply_r1/test-*
- config_name: anli_does_this_imply_r1_score_eval
data_files:
- split: train
path: anli_does_this_imply_r1_score_eval/train-*
- split: validation
path: anli_does_this_imply_r1_score_eval/validation-*
- split: test
path: anli_does_this_imply_r1_score_eval/test-*
- config_name: anli_does_this_imply_r2
data_files:
- split: train
path: anli_does_this_imply_r2/train-*
- split: validation
path: anli_does_this_imply_r2/validation-*
- split: test
path: anli_does_this_imply_r2/test-*
- config_name: anli_does_this_imply_r2_score_eval
data_files:
- split: train
path: anli_does_this_imply_r2_score_eval/train-*
- split: validation
path: anli_does_this_imply_r2_score_eval/validation-*
- split: test
path: anli_does_this_imply_r2_score_eval/test-*
- config_name: anli_does_this_imply_r3
data_files:
- split: train
path: anli_does_this_imply_r3/train-*
- split: validation
path: anli_does_this_imply_r3/validation-*
- split: test
path: anli_does_this_imply_r3/test-*
- config_name: anli_does_this_imply_r3_score_eval
data_files:
- split: train
path: anli_does_this_imply_r3_score_eval/train-*
- split: validation
path: anli_does_this_imply_r3_score_eval/validation-*
- split: test
path: anli_does_this_imply_r3_score_eval/test-*
- config_name: anli_guaranteed_possible_impossible_r1
data_files:
- split: train
path: anli_guaranteed_possible_impossible_r1/train-*
- split: validation
path: anli_guaranteed_possible_impossible_r1/validation-*
- split: test
path: anli_guaranteed_possible_impossible_r1/test-*
- config_name: anli_guaranteed_possible_impossible_r1_score_eval
data_files:
- split: train
path: anli_guaranteed_possible_impossible_r1_score_eval/train-*
- split: validation
path: anli_guaranteed_possible_impossible_r1_score_eval/validation-*
- split: test
path: anli_guaranteed_possible_impossible_r1_score_eval/test-*
- config_name: anli_guaranteed_possible_impossible_r2
data_files:
- split: train
path: anli_guaranteed_possible_impossible_r2/train-*
- split: validation
path: anli_guaranteed_possible_impossible_r2/validation-*
- split: test
path: anli_guaranteed_possible_impossible_r2/test-*
- config_name: anli_guaranteed_possible_impossible_r2_score_eval
data_files:
- split: train
path: anli_guaranteed_possible_impossible_r2_score_eval/train-*
- split: validation
path: anli_guaranteed_possible_impossible_r2_score_eval/validation-*
- split: test
path: anli_guaranteed_possible_impossible_r2_score_eval/test-*
- config_name: anli_guaranteed_possible_impossible_r3
data_files:
- split: train
path: anli_guaranteed_possible_impossible_r3/train-*
- split: validation
path: anli_guaranteed_possible_impossible_r3/validation-*
- split: test
path: anli_guaranteed_possible_impossible_r3/test-*
- config_name: anli_guaranteed_possible_impossible_r3_score_eval
data_files:
- split: train
path: anli_guaranteed_possible_impossible_r3_score_eval/train-*
- split: validation
path: anli_guaranteed_possible_impossible_r3_score_eval/validation-*
- split: test
path: anli_guaranteed_possible_impossible_r3_score_eval/test-*
- config_name: anli_guaranteed_true_r1
data_files:
- split: train
path: anli_guaranteed_true_r1/train-*
- split: validation
path: anli_guaranteed_true_r1/validation-*
- split: test
path: anli_guaranteed_true_r1/test-*
- config_name: anli_guaranteed_true_r1_score_eval
data_files:
- split: train
path: anli_guaranteed_true_r1_score_eval/train-*
- split: validation
path: anli_guaranteed_true_r1_score_eval/validation-*
- split: test
path: anli_guaranteed_true_r1_score_eval/test-*
- config_name: anli_guaranteed_true_r2
data_files:
- split: train
path: anli_guaranteed_true_r2/train-*
- split: validation
path: anli_guaranteed_true_r2/validation-*
- split: test
path: anli_guaranteed_true_r2/test-*
- config_name: anli_guaranteed_true_r2_score_eval
data_files:
- split: train
path: anli_guaranteed_true_r2_score_eval/train-*
- split: validation
path: anli_guaranteed_true_r2_score_eval/validation-*
- split: test
path: anli_guaranteed_true_r2_score_eval/test-*
- config_name: anli_guaranteed_true_r3
data_files:
- split: train
path: anli_guaranteed_true_r3/train-*
- split: validation
path: anli_guaranteed_true_r3/validation-*
- split: test
path: anli_guaranteed_true_r3/test-*
- config_name: anli_guaranteed_true_r3_score_eval
data_files:
- split: train
path: anli_guaranteed_true_r3_score_eval/train-*
- split: validation
path: anli_guaranteed_true_r3_score_eval/validation-*
- split: test
path: anli_guaranteed_true_r3_score_eval/test-*
- config_name: anli_justified_in_saying_r1
data_files:
- split: train
path: anli_justified_in_saying_r1/train-*
- split: validation
path: anli_justified_in_saying_r1/validation-*
- split: test
path: anli_justified_in_saying_r1/test-*
- config_name: anli_justified_in_saying_r1_score_eval
data_files:
- split: train
path: anli_justified_in_saying_r1_score_eval/train-*
- split: validation
path: anli_justified_in_saying_r1_score_eval/validation-*
- split: test
path: anli_justified_in_saying_r1_score_eval/test-*
- config_name: anli_justified_in_saying_r2
data_files:
- split: train
path: anli_justified_in_saying_r2/train-*
- split: validation
path: anli_justified_in_saying_r2/validation-*
- split: test
path: anli_justified_in_saying_r2/test-*
- config_name: anli_justified_in_saying_r2_score_eval
data_files:
- split: train
path: anli_justified_in_saying_r2_score_eval/train-*
- split: validation
path: anli_justified_in_saying_r2_score_eval/validation-*
- split: test
path: anli_justified_in_saying_r2_score_eval/test-*
- config_name: anli_justified_in_saying_r3
data_files:
- split: train
path: anli_justified_in_saying_r3/train-*
- split: validation
path: anli_justified_in_saying_r3/validation-*
- split: test
path: anli_justified_in_saying_r3/test-*
- config_name: anli_justified_in_saying_r3_score_eval
data_files:
- split: train
path: anli_justified_in_saying_r3_score_eval/train-*
- split: validation
path: anli_justified_in_saying_r3_score_eval/validation-*
- split: test
path: anli_justified_in_saying_r3_score_eval/test-*
- config_name: anli_must_be_true_r1
data_files:
- split: train
path: anli_must_be_true_r1/train-*
- split: validation
path: anli_must_be_true_r1/validation-*
- split: test
path: anli_must_be_true_r1/test-*
- config_name: anli_must_be_true_r1_score_eval
data_files:
- split: train
path: anli_must_be_true_r1_score_eval/train-*
- split: validation
path: anli_must_be_true_r1_score_eval/validation-*
- split: test
path: anli_must_be_true_r1_score_eval/test-*
- config_name: anli_must_be_true_r2
data_files:
- split: train
path: anli_must_be_true_r2/train-*
- split: validation
path: anli_must_be_true_r2/validation-*
- split: test
path: anli_must_be_true_r2/test-*
- config_name: anli_must_be_true_r2_score_eval
data_files:
- split: train
path: anli_must_be_true_r2_score_eval/train-*
- split: validation
path: anli_must_be_true_r2_score_eval/validation-*
- split: test
path: anli_must_be_true_r2_score_eval/test-*
- config_name: anli_must_be_true_r3
data_files:
- split: train
path: anli_must_be_true_r3/train-*
- split: validation
path: anli_must_be_true_r3/validation-*
- split: test
path: anli_must_be_true_r3/test-*
- config_name: anli_must_be_true_r3_score_eval
data_files:
- split: train
path: anli_must_be_true_r3_score_eval/train-*
- split: validation
path: anli_must_be_true_r3_score_eval/validation-*
- split: test
path: anli_must_be_true_r3_score_eval/test-*
- config_name: anli_should_assume_r1
data_files:
- split: train
path: anli_should_assume_r1/train-*
- split: validation
path: anli_should_assume_r1/validation-*
- split: test
path: anli_should_assume_r1/test-*
- config_name: anli_should_assume_r1_score_eval
data_files:
- split: train
path: anli_should_assume_r1_score_eval/train-*
- split: validation
path: anli_should_assume_r1_score_eval/validation-*
- split: test
path: anli_should_assume_r1_score_eval/test-*
- config_name: anli_should_assume_r2
data_files:
- split: train
path: anli_should_assume_r2/train-*
- split: validation
path: anli_should_assume_r2/validation-*
- split: test
path: anli_should_assume_r2/test-*
- config_name: anli_should_assume_r2_score_eval
data_files:
- split: train
path: anli_should_assume_r2_score_eval/train-*
- split: validation
path: anli_should_assume_r2_score_eval/validation-*
- split: test
path: anli_should_assume_r2_score_eval/test-*
- config_name: anli_should_assume_r3
data_files:
- split: train
path: anli_should_assume_r3/train-*
- split: validation
path: anli_should_assume_r3/validation-*
- split: test
path: anli_should_assume_r3/test-*
- config_name: anli_should_assume_r3_score_eval
data_files:
- split: train
path: anli_should_assume_r3_score_eval/train-*
- split: validation
path: anli_should_assume_r3_score_eval/validation-*
- split: test
path: anli_should_assume_r3_score_eval/test-*
- config_name: anli_take_the_following_as_truth_r1
data_files:
- split: train
path: anli_take_the_following_as_truth_r1/train-*
- split: validation
path: anli_take_the_following_as_truth_r1/validation-*
- split: test
path: anli_take_the_following_as_truth_r1/test-*
- config_name: anli_take_the_following_as_truth_r1_score_eval
data_files:
- split: train
path: anli_take_the_following_as_truth_r1_score_eval/train-*
- split: validation
path: anli_take_the_following_as_truth_r1_score_eval/validation-*
- split: test
path: anli_take_the_following_as_truth_r1_score_eval/test-*
- config_name: anli_take_the_following_as_truth_r2
data_files:
- split: train
path: anli_take_the_following_as_truth_r2/train-*
- split: validation
path: anli_take_the_following_as_truth_r2/validation-*
- split: test
path: anli_take_the_following_as_truth_r2/test-*
- config_name: anli_take_the_following_as_truth_r2_score_eval
data_files:
- split: train
path: anli_take_the_following_as_truth_r2_score_eval/train-*
- split: validation
path: anli_take_the_following_as_truth_r2_score_eval/validation-*
- split: test
path: anli_take_the_following_as_truth_r2_score_eval/test-*
- config_name: anli_take_the_following_as_truth_r3
data_files:
- split: train
path: anli_take_the_following_as_truth_r3/train-*
- split: validation
path: anli_take_the_following_as_truth_r3/validation-*
- split: test
path: anli_take_the_following_as_truth_r3/test-*
- config_name: anli_take_the_following_as_truth_r3_score_eval
data_files:
- split: train
path: anli_take_the_following_as_truth_r3_score_eval/train-*
- split: validation
path: anli_take_the_following_as_truth_r3_score_eval/validation-*
- split: test
path: anli_take_the_following_as_truth_r3_score_eval/test-*
- config_name: app_reviews_categorize_rating_using_review
data_files:
- split: train
path: app_reviews_categorize_rating_using_review/train-*
- config_name: app_reviews_convert_to_rating
data_files:
- split: train
path: app_reviews_convert_to_rating/train-*
- config_name: app_reviews_convert_to_star_rating
data_files:
- split: train
path: app_reviews_convert_to_star_rating/train-*
- config_name: app_reviews_generate_review
data_files:
- split: train
path: app_reviews_generate_review/train-*
- config_name: cnn_dailymail_3.0.0_2_or_3_sentences
data_files:
- split: train
path: cnn_dailymail_3.0.0_2_or_3_sentences/train-*
- split: validation
path: cnn_dailymail_3.0.0_2_or_3_sentences/validation-*
- split: test
path: cnn_dailymail_3.0.0_2_or_3_sentences/test-*
- config_name: cnn_dailymail_3.0.0_generate_story
data_files:
- split: train
path: cnn_dailymail_3.0.0_generate_story/train-*
- split: validation
path: cnn_dailymail_3.0.0_generate_story/validation-*
- split: test
path: cnn_dailymail_3.0.0_generate_story/test-*
- config_name: cnn_dailymail_3.0.0_news_card_view
data_files:
- split: train
path: cnn_dailymail_3.0.0_news_card_view/train-*
- split: validation
path: cnn_dailymail_3.0.0_news_card_view/validation-*
- split: test
path: cnn_dailymail_3.0.0_news_card_view/test-*
- config_name: cnn_dailymail_3.0.0_news_stock
data_files:
- split: train
path: cnn_dailymail_3.0.0_news_stock/train-*
- split: validation
path: cnn_dailymail_3.0.0_news_stock/validation-*
- split: test
path: cnn_dailymail_3.0.0_news_stock/test-*
- config_name: cnn_dailymail_3.0.0_news_summary
data_files:
- split: train
path: cnn_dailymail_3.0.0_news_summary/train-*
- split: validation
path: cnn_dailymail_3.0.0_news_summary/validation-*
- split: test
path: cnn_dailymail_3.0.0_news_summary/test-*
- config_name: cnn_dailymail_3.0.0_spice_up_story
data_files:
- split: train
path: cnn_dailymail_3.0.0_spice_up_story/train-*
- split: validation
path: cnn_dailymail_3.0.0_spice_up_story/validation-*
- split: test
path: cnn_dailymail_3.0.0_spice_up_story/test-*
- config_name: cnn_dailymail_3.0.0_sum_in_brief
data_files:
- split: train
path: cnn_dailymail_3.0.0_sum_in_brief/train-*
- split: validation
path: cnn_dailymail_3.0.0_sum_in_brief/validation-*
- split: test
path: cnn_dailymail_3.0.0_sum_in_brief/test-*
- config_name: cnn_dailymail_3.0.0_tldr_summary
data_files:
- split: train
path: cnn_dailymail_3.0.0_tldr_summary/train-*
- split: validation
path: cnn_dailymail_3.0.0_tldr_summary/validation-*
- split: test
path: cnn_dailymail_3.0.0_tldr_summary/test-*
- config_name: cnn_dailymail_3.0.0_write_an_outline
data_files:
- split: train
path: cnn_dailymail_3.0.0_write_an_outline/train-*
- split: validation
path: cnn_dailymail_3.0.0_write_an_outline/validation-*
- split: test
path: cnn_dailymail_3.0.0_write_an_outline/test-*
- config_name: common_gen_Example_prompt
data_files:
- split: train
path: common_gen_Example_prompt/train-*
- split: validation
path: common_gen_Example_prompt/validation-*
- split: test
path: common_gen_Example_prompt/test-*
- config_name: common_gen_Given_concepts_type_1
data_files:
- split: train
path: common_gen_Given_concepts_type_1/train-*
- split: validation
path: common_gen_Given_concepts_type_1/validation-*
- split: test
path: common_gen_Given_concepts_type_1/test-*
- config_name: common_gen_Given_concepts_type_2
data_files:
- split: train
path: common_gen_Given_concepts_type_2/train-*
- split: validation
path: common_gen_Given_concepts_type_2/validation-*
- split: test
path: common_gen_Given_concepts_type_2/test-*
- config_name: common_gen_Put_together
data_files:
- split: train
path: common_gen_Put_together/train-*
- split: validation
path: common_gen_Put_together/validation-*
- split: test
path: common_gen_Put_together/test-*
- config_name: common_gen_choice_in_concept_centric_sentence_generation
data_files:
- split: train
path: common_gen_choice_in_concept_centric_sentence_generation/train-*
- split: validation
path: common_gen_choice_in_concept_centric_sentence_generation/validation-*
- split: test
path: common_gen_choice_in_concept_centric_sentence_generation/test-*
- config_name: common_gen_random_task_template_prompt
data_files:
- split: train
path: common_gen_random_task_template_prompt/train-*
- split: validation
path: common_gen_random_task_template_prompt/validation-*
- split: test
path: common_gen_random_task_template_prompt/test-*
- config_name: common_gen_sentence_to_concepts
data_files:
- split: train
path: common_gen_sentence_to_concepts/train-*
- split: validation
path: common_gen_sentence_to_concepts/validation-*
- split: test
path: common_gen_sentence_to_concepts/test-*
- config_name: common_gen_topic_to_sentence
data_files:
- split: train
path: common_gen_topic_to_sentence/train-*
- split: validation
path: common_gen_topic_to_sentence/validation-*
- split: test
path: common_gen_topic_to_sentence/test-*
- config_name: common_gen_topics_from_the_sentence
data_files:
- split: train
path: common_gen_topics_from_the_sentence/train-*
- split: validation
path: common_gen_topics_from_the_sentence/validation-*
- split: test
path: common_gen_topics_from_the_sentence/test-*
- config_name: cos_e_v1.11_aligned_with_common_sense
data_files:
- split: train
path: cos_e_v1.11_aligned_with_common_sense/train-*
- split: validation
path: cos_e_v1.11_aligned_with_common_sense/validation-*
- config_name: cos_e_v1.11_description_question_option_id
data_files:
- split: train
path: cos_e_v1.11_description_question_option_id/train-*
- split: validation
path: cos_e_v1.11_description_question_option_id/validation-*
- config_name: cos_e_v1.11_description_question_option_text
data_files:
- split: train
path: cos_e_v1.11_description_question_option_text/train-*
- split: validation
path: cos_e_v1.11_description_question_option_text/validation-*
- config_name: cos_e_v1.11_explain_why_human
data_files:
- split: train
path: cos_e_v1.11_explain_why_human/train-*
- split: validation
path: cos_e_v1.11_explain_why_human/validation-*
- config_name: cos_e_v1.11_generate_explanation_given_text
data_files:
- split: train
path: cos_e_v1.11_generate_explanation_given_text/train-*
- split: validation
path: cos_e_v1.11_generate_explanation_given_text/validation-*
- config_name: cos_e_v1.11_i_think
data_files:
- split: train
path: cos_e_v1.11_i_think/train-*
- split: validation
path: cos_e_v1.11_i_think/validation-*
- config_name: cos_e_v1.11_question_description_option_id
data_files:
- split: train
path: cos_e_v1.11_question_description_option_id/train-*
- split: validation
path: cos_e_v1.11_question_description_option_id/validation-*
- config_name: cos_e_v1.11_question_description_option_text
data_files:
- split: train
path: cos_e_v1.11_question_description_option_text/train-*
- split: validation
path: cos_e_v1.11_question_description_option_text/validation-*
- config_name: cos_e_v1.11_question_option_description_id
data_files:
- split: train
path: cos_e_v1.11_question_option_description_id/train-*
- split: validation
path: cos_e_v1.11_question_option_description_id/validation-*
- config_name: cos_e_v1.11_question_option_description_text
data_files:
- split: train
path: cos_e_v1.11_question_option_description_text/train-*
- split: validation
path: cos_e_v1.11_question_option_description_text/validation-*
- config_name: cos_e_v1.11_rationale
data_files:
- split: train
path: cos_e_v1.11_rationale/train-*
- split: validation
path: cos_e_v1.11_rationale/validation-*
- config_name: cosmos_qa_context_answer_to_question
data_files:
- split: train
path: cosmos_qa_context_answer_to_question/train-*
- split: validation
path: cosmos_qa_context_answer_to_question/validation-*
- split: test
path: cosmos_qa_context_answer_to_question/test-*
- config_name: cosmos_qa_context_description_question_answer_id
data_files:
- split: train
path: cosmos_qa_context_description_question_answer_id/train-*
- split: validation
path: cosmos_qa_context_description_question_answer_id/validation-*
- split: test
path: cosmos_qa_context_description_question_answer_id/test-*
- config_name: cosmos_qa_context_description_question_answer_text
data_files:
- split: train
path: cosmos_qa_context_description_question_answer_text/train-*
- split: validation
path: cosmos_qa_context_description_question_answer_text/validation-*
- split: test
path: cosmos_qa_context_description_question_answer_text/test-*
- config_name: cosmos_qa_context_description_question_text
data_files:
- split: train
path: cosmos_qa_context_description_question_text/train-*
- split: validation
path: cosmos_qa_context_description_question_text/validation-*
- split: test
path: cosmos_qa_context_description_question_text/test-*
- config_name: cosmos_qa_context_question_description_answer_id
data_files:
- split: train
path: cosmos_qa_context_question_description_answer_id/train-*
- split: validation
path: cosmos_qa_context_question_description_answer_id/validation-*
- split: test
path: cosmos_qa_context_question_description_answer_id/test-*
- config_name: cosmos_qa_context_question_description_answer_text
data_files:
- split: train
path: cosmos_qa_context_question_description_answer_text/train-*
- split: validation
path: cosmos_qa_context_question_description_answer_text/validation-*
- split: test
path: cosmos_qa_context_question_description_answer_text/test-*
- config_name: cosmos_qa_context_question_description_text
data_files:
- split: train
path: cosmos_qa_context_question_description_text/train-*
- split: validation
path: cosmos_qa_context_question_description_text/validation-*
- split: test
path: cosmos_qa_context_question_description_text/test-*
- config_name: cosmos_qa_description_context_question_answer_id
data_files:
- split: train
path: cosmos_qa_description_context_question_answer_id/train-*
- split: validation
path: cosmos_qa_description_context_question_answer_id/validation-*
- split: test
path: cosmos_qa_description_context_question_answer_id/test-*
- config_name: cosmos_qa_description_context_question_answer_text
data_files:
- split: train
path: cosmos_qa_description_context_question_answer_text/train-*
- split: validation
path: cosmos_qa_description_context_question_answer_text/validation-*
- split: test
path: cosmos_qa_description_context_question_answer_text/test-*
- config_name: cosmos_qa_description_context_question_text
data_files:
- split: train
path: cosmos_qa_description_context_question_text/train-*
- split: validation
path: cosmos_qa_description_context_question_text/validation-*
- split: test
path: cosmos_qa_description_context_question_text/test-*
- config_name: cosmos_qa_no_prompt_id
data_files:
- split: train
path: cosmos_qa_no_prompt_id/train-*
- split: validation
path: cosmos_qa_no_prompt_id/validation-*
- split: test
path: cosmos_qa_no_prompt_id/test-*
- config_name: cosmos_qa_no_prompt_text
data_files:
- split: train
path: cosmos_qa_no_prompt_text/train-*
- split: validation
path: cosmos_qa_no_prompt_text/validation-*
- split: test
path: cosmos_qa_no_prompt_text/test-*
- config_name: cosmos_qa_only_question_answer
data_files:
- split: train
path: cosmos_qa_only_question_answer/train-*
- split: validation
path: cosmos_qa_only_question_answer/validation-*
- split: test
path: cosmos_qa_only_question_answer/test-*
- config_name: dbpedia_14_given_a_choice_of_categories_
data_files:
- split: train
path: dbpedia_14_given_a_choice_of_categories_/train-*
- split: test
path: dbpedia_14_given_a_choice_of_categories_/test-*
- config_name: dbpedia_14_given_a_list_of_category_what_does_the_title_belong_to
data_files:
- split: train
path: dbpedia_14_given_a_list_of_category_what_does_the_title_belong_to/train-*
- split: test
path: dbpedia_14_given_a_list_of_category_what_does_the_title_belong_to/test-*
- config_name: dbpedia_14_given_list_what_category_does_the_paragraph_belong_to
data_files:
- split: train
path: dbpedia_14_given_list_what_category_does_the_paragraph_belong_to/train-*
- split: test
path: dbpedia_14_given_list_what_category_does_the_paragraph_belong_to/test-*
- config_name: dbpedia_14_pick_one_category_for_the_following_text
data_files:
- split: train
path: dbpedia_14_pick_one_category_for_the_following_text/train-*
- split: test
path: dbpedia_14_pick_one_category_for_the_following_text/test-*
- config_name: dream_answer_to_dialogue
data_files:
- split: train
path: dream_answer_to_dialogue/train-*
- split: validation
path: dream_answer_to_dialogue/validation-*
- split: test
path: dream_answer_to_dialogue/test-*
- config_name: dream_baseline
data_files:
- split: train
path: dream_baseline/train-*
- split: validation
path: dream_baseline/validation-*
- split: test
path: dream_baseline/test-*
- config_name: dream_generate_first_utterance
data_files:
- split: train
path: dream_generate_first_utterance/train-*
- split: validation
path: dream_generate_first_utterance/validation-*
- split: test
path: dream_generate_first_utterance/test-*
- config_name: dream_generate_last_utterance
data_files:
- split: train
path: dream_generate_last_utterance/train-*
- split: validation
path: dream_generate_last_utterance/validation-*
- split: test
path: dream_generate_last_utterance/test-*
- config_name: dream_read_the_following_conversation_and_answer_the_question
data_files:
- split: train
path: dream_read_the_following_conversation_and_answer_the_question/train-*
- split: validation
path: dream_read_the_following_conversation_and_answer_the_question/validation-*
- split: test
path: dream_read_the_following_conversation_and_answer_the_question/test-*
- config_name: duorc_ParaphraseRC_answer_question
data_files:
- split: train
path: duorc_ParaphraseRC_answer_question/train-*
- split: validation
path: duorc_ParaphraseRC_answer_question/validation-*
- split: test
path: duorc_ParaphraseRC_answer_question/test-*
- config_name: duorc_ParaphraseRC_build_story_around_qa
data_files:
- split: train
path: duorc_ParaphraseRC_build_story_around_qa/train-*
- split: validation
path: duorc_ParaphraseRC_build_story_around_qa/validation-*
- split: test
path: duorc_ParaphraseRC_build_story_around_qa/test-*
- config_name: duorc_ParaphraseRC_decide_worth_it
data_files:
- split: train
path: duorc_ParaphraseRC_decide_worth_it/train-*
- split: validation
path: duorc_ParaphraseRC_decide_worth_it/validation-*
- split: test
path: duorc_ParaphraseRC_decide_worth_it/test-*
- config_name: duorc_ParaphraseRC_extract_answer
data_files:
- split: train
path: duorc_ParaphraseRC_extract_answer/train-*
- split: validation
path: duorc_ParaphraseRC_extract_answer/validation-*
- split: test
path: duorc_ParaphraseRC_extract_answer/test-*
- config_name: duorc_ParaphraseRC_generate_question
data_files:
- split: train
path: duorc_ParaphraseRC_generate_question/train-*
- split: validation
path: duorc_ParaphraseRC_generate_question/validation-*
- split: test
path: duorc_ParaphraseRC_generate_question/test-*
- config_name: duorc_ParaphraseRC_generate_question_by_answer
data_files:
- split: train
path: duorc_ParaphraseRC_generate_question_by_answer/train-*
- split: validation
path: duorc_ParaphraseRC_generate_question_by_answer/validation-*
- split: test
path: duorc_ParaphraseRC_generate_question_by_answer/test-*
- config_name: duorc_ParaphraseRC_movie_director
data_files:
- split: train
path: duorc_ParaphraseRC_movie_director/train-*
- split: validation
path: duorc_ParaphraseRC_movie_director/validation-*
- split: test
path: duorc_ParaphraseRC_movie_director/test-*
- config_name: duorc_ParaphraseRC_question_answering
data_files:
- split: train
path: duorc_ParaphraseRC_question_answering/train-*
- split: validation
path: duorc_ParaphraseRC_question_answering/validation-*
- split: test
path: duorc_ParaphraseRC_question_answering/test-*
- config_name: duorc_ParaphraseRC_title_generation
data_files:
- split: train
path: duorc_ParaphraseRC_title_generation/train-*
- split: validation
path: duorc_ParaphraseRC_title_generation/validation-*
- split: test
path: duorc_ParaphraseRC_title_generation/test-*
- config_name: duorc_SelfRC_answer_question
data_files:
- split: train
path: duorc_SelfRC_answer_question/train-*
- split: validation
path: duorc_SelfRC_answer_question/validation-*
- split: test
path: duorc_SelfRC_answer_question/test-*
- config_name: duorc_SelfRC_build_story_around_qa
data_files:
- split: train
path: duorc_SelfRC_build_story_around_qa/train-*
- split: validation
path: duorc_SelfRC_build_story_around_qa/validation-*
- split: test
path: duorc_SelfRC_build_story_around_qa/test-*
- config_name: duorc_SelfRC_decide_worth_it
data_files:
- split: train
path: duorc_SelfRC_decide_worth_it/train-*
- split: validation
path: duorc_SelfRC_decide_worth_it/validation-*
- split: test
path: duorc_SelfRC_decide_worth_it/test-*
- config_name: duorc_SelfRC_extract_answer
data_files:
- split: train
path: duorc_SelfRC_extract_answer/train-*
- split: validation
path: duorc_SelfRC_extract_answer/validation-*
- split: test
path: duorc_SelfRC_extract_answer/test-*
- config_name: duorc_SelfRC_generate_question
data_files:
- split: train
path: duorc_SelfRC_generate_question/train-*
- split: validation
path: duorc_SelfRC_generate_question/validation-*
- split: test
path: duorc_SelfRC_generate_question/test-*
- config_name: duorc_SelfRC_generate_question_by_answer
data_files:
- split: train
path: duorc_SelfRC_generate_question_by_answer/train-*
- split: validation
path: duorc_SelfRC_generate_question_by_answer/validation-*
- split: test
path: duorc_SelfRC_generate_question_by_answer/test-*
- config_name: duorc_SelfRC_movie_director
data_files:
- split: train
path: duorc_SelfRC_movie_director/train-*
- split: validation
path: duorc_SelfRC_movie_director/validation-*
- split: test
path: duorc_SelfRC_movie_director/test-*
- config_name: duorc_SelfRC_question_answering
data_files:
- split: train
path: duorc_SelfRC_question_answering/train-*
- split: validation
path: duorc_SelfRC_question_answering/validation-*
- split: test
path: duorc_SelfRC_question_answering/test-*
- config_name: duorc_SelfRC_title_generation
data_files:
- split: train
path: duorc_SelfRC_title_generation/train-*
- split: validation
path: duorc_SelfRC_title_generation/validation-*
- split: test
path: duorc_SelfRC_title_generation/test-*
- config_name: gigaword_TLDR
data_files:
- split: train
path: gigaword_TLDR/train-*
- split: validation
path: gigaword_TLDR/validation-*
- split: test
path: gigaword_TLDR/test-*
- config_name: gigaword_first_sentence_title
data_files:
- split: train
path: gigaword_first_sentence_title/train-*
- split: validation
path: gigaword_first_sentence_title/validation-*
- split: test
path: gigaword_first_sentence_title/test-*
- config_name: gigaword_generate_summary_for_this
data_files:
- split: train
path: gigaword_generate_summary_for_this/train-*
- split: validation
path: gigaword_generate_summary_for_this/validation-*
- split: test
path: gigaword_generate_summary_for_this/test-*
- config_name: gigaword_in_a_nutshell
data_files:
- split: train
path: gigaword_in_a_nutshell/train-*
- split: validation
path: gigaword_in_a_nutshell/validation-*
- split: test
path: gigaword_in_a_nutshell/test-*
- config_name: gigaword_make_a_title
data_files:
- split: train
path: gigaword_make_a_title/train-*
- split: validation
path: gigaword_make_a_title/validation-*
- split: test
path: gigaword_make_a_title/test-*
- config_name: gigaword_reverse_writing
data_files:
- split: train
path: gigaword_reverse_writing/train-*
- split: validation
path: gigaword_reverse_writing/validation-*
- split: test
path: gigaword_reverse_writing/test-*
- config_name: gigaword_write_a_title_for_this_sentence
data_files:
- split: train
path: gigaword_write_a_title_for_this_sentence/train-*
- split: validation
path: gigaword_write_a_title_for_this_sentence/validation-*
- split: test
path: gigaword_write_a_title_for_this_sentence/test-*
- config_name: gigaword_write_an_article
data_files:
- split: train
path: gigaword_write_an_article/train-*
- split: validation
path: gigaword_write_an_article/validation-*
- split: test
path: gigaword_write_an_article/test-*
- config_name: gigaword_write_its_sentence
data_files:
- split: train
path: gigaword_write_its_sentence/train-*
- split: validation
path: gigaword_write_its_sentence/validation-*
- split: test
path: gigaword_write_its_sentence/test-*
- config_name: glue_mrpc_equivalent
data_files:
- split: train
path: glue_mrpc_equivalent/train-*
- split: validation
path: glue_mrpc_equivalent/validation-*
- split: test
path: glue_mrpc_equivalent/test-*
- config_name: glue_mrpc_generate_paraphrase
data_files:
- split: train
path: glue_mrpc_generate_paraphrase/train-*
- split: validation
path: glue_mrpc_generate_paraphrase/validation-*
- split: test
path: glue_mrpc_generate_paraphrase/test-*
- config_name: glue_mrpc_generate_sentence
data_files:
- split: train
path: glue_mrpc_generate_sentence/train-*
- split: validation
path: glue_mrpc_generate_sentence/validation-*
- split: test
path: glue_mrpc_generate_sentence/test-*
- config_name: glue_mrpc_paraphrase
data_files:
- split: train
path: glue_mrpc_paraphrase/train-*
- split: validation
path: glue_mrpc_paraphrase/validation-*
- split: test
path: glue_mrpc_paraphrase/test-*
- config_name: glue_mrpc_replace
data_files:
- split: train
path: glue_mrpc_replace/train-*
- split: validation
path: glue_mrpc_replace/validation-*
- split: test
path: glue_mrpc_replace/test-*
- config_name: glue_mrpc_same_thing
data_files:
- split: train
path: glue_mrpc_same_thing/train-*
- split: validation
path: glue_mrpc_same_thing/validation-*
- split: test
path: glue_mrpc_same_thing/test-*
- config_name: glue_mrpc_want_to_know
data_files:
- split: train
path: glue_mrpc_want_to_know/train-*
- split: validation
path: glue_mrpc_want_to_know/validation-*
- split: test
path: glue_mrpc_want_to_know/test-*
- config_name: glue_qqp_answer
data_files:
- split: train
path: glue_qqp_answer/train-*
- split: validation
path: glue_qqp_answer/validation-*
- split: test
path: glue_qqp_answer/test-*
- config_name: glue_qqp_duplicate
data_files:
- split: train
path: glue_qqp_duplicate/train-*
- split: validation
path: glue_qqp_duplicate/validation-*
- split: test
path: glue_qqp_duplicate/test-*
- config_name: glue_qqp_duplicate_or_not
data_files:
- split: train
path: glue_qqp_duplicate_or_not/train-*
- split: validation
path: glue_qqp_duplicate_or_not/validation-*
- split: test
path: glue_qqp_duplicate_or_not/test-*
- config_name: glue_qqp_meaning
data_files:
- split: train
path: glue_qqp_meaning/train-*
- split: validation
path: glue_qqp_meaning/validation-*
- split: test
path: glue_qqp_meaning/test-*
- config_name: glue_qqp_quora
data_files:
- split: train
path: glue_qqp_quora/train-*
- split: validation
path: glue_qqp_quora/validation-*
- split: test
path: glue_qqp_quora/test-*
- config_name: glue_qqp_same_thing
data_files:
- split: train
path: glue_qqp_same_thing/train-*
- split: validation
path: glue_qqp_same_thing/validation-*
- split: test
path: glue_qqp_same_thing/test-*
- config_name: hellaswag_Appropriate_continuation_Yes_or_No
data_files:
- split: train
path: hellaswag_Appropriate_continuation_Yes_or_No/train-*
- split: validation
path: hellaswag_Appropriate_continuation_Yes_or_No/validation-*
- split: test
path: hellaswag_Appropriate_continuation_Yes_or_No/test-*
- config_name: hellaswag_Open_ended_completion
data_files:
- split: train
path: hellaswag_Open_ended_completion/train-*
- split: validation
path: hellaswag_Open_ended_completion/validation-*
- split: test
path: hellaswag_Open_ended_completion/test-*
- config_name: hellaswag_Open_ended_start
data_files:
- split: train
path: hellaswag_Open_ended_start/train-*
- split: validation
path: hellaswag_Open_ended_start/validation-*
- split: test
path: hellaswag_Open_ended_start/test-*
- config_name: hellaswag_Predict_ending_with_hint
data_files:
- split: train
path: hellaswag_Predict_ending_with_hint/train-*
- split: validation
path: hellaswag_Predict_ending_with_hint/validation-*
- split: test
path: hellaswag_Predict_ending_with_hint/test-*
- config_name: hellaswag_Predict_ending_with_hint_score_eval
data_files:
- split: train
path: hellaswag_Predict_ending_with_hint_score_eval/train-*
- split: validation
path: hellaswag_Predict_ending_with_hint_score_eval/validation-*
- split: test
path: hellaswag_Predict_ending_with_hint_score_eval/test-*
- config_name: hellaswag_Randomized_prompts_template
data_files:
- split: train
path: hellaswag_Randomized_prompts_template/train-*
- split: validation
path: hellaswag_Randomized_prompts_template/validation-*
- split: test
path: hellaswag_Randomized_prompts_template/test-*
- config_name: hellaswag_Randomized_prompts_template_score_eval
data_files:
- split: train
path: hellaswag_Randomized_prompts_template_score_eval/train-*
- split: validation
path: hellaswag_Randomized_prompts_template_score_eval/validation-*
- split: test
path: hellaswag_Randomized_prompts_template_score_eval/test-*
- config_name: hellaswag_Reversed_appropriate_continuation_Yes_or_No
data_files:
- split: train
path: hellaswag_Reversed_appropriate_continuation_Yes_or_No/train-*
- split: validation
path: hellaswag_Reversed_appropriate_continuation_Yes_or_No/validation-*
- split: test
path: hellaswag_Reversed_appropriate_continuation_Yes_or_No/test-*
- config_name: hellaswag_Topic_of_the_context
data_files:
- split: train
path: hellaswag_Topic_of_the_context/train-*
- split: validation
path: hellaswag_Topic_of_the_context/validation-*
- split: test
path: hellaswag_Topic_of_the_context/test-*
- config_name: hellaswag_Topic_without_the_ending_answer
data_files:
- split: train
path: hellaswag_Topic_without_the_ending_answer/train-*
- split: validation
path: hellaswag_Topic_without_the_ending_answer/validation-*
- split: test
path: hellaswag_Topic_without_the_ending_answer/test-*
- config_name: hellaswag_complete_first_then
data_files:
- split: train
path: hellaswag_complete_first_then/train-*
- split: validation
path: hellaswag_complete_first_then/validation-*
- split: test
path: hellaswag_complete_first_then/test-*
- config_name: hellaswag_complete_first_then_score_eval
data_files:
- split: train
path: hellaswag_complete_first_then_score_eval/train-*
- split: validation
path: hellaswag_complete_first_then_score_eval/validation-*
- split: test
path: hellaswag_complete_first_then_score_eval/test-*
- config_name: hellaswag_how_ends
data_files:
- split: train
path: hellaswag_how_ends/train-*
- split: validation
path: hellaswag_how_ends/validation-*
- split: test
path: hellaswag_how_ends/test-*
- config_name: hellaswag_if_begins_how_continues
data_files:
- split: train
path: hellaswag_if_begins_how_continues/train-*
- split: validation
path: hellaswag_if_begins_how_continues/validation-*
- split: test
path: hellaswag_if_begins_how_continues/test-*
- config_name: hellaswag_if_begins_how_continues_score_eval
data_files:
- split: train
path: hellaswag_if_begins_how_continues_score_eval/train-*
- split: validation
path: hellaswag_if_begins_how_continues_score_eval/validation-*
- split: test
path: hellaswag_if_begins_how_continues_score_eval/test-*
- config_name: imdb_Movie_Expressed_Sentiment
data_files:
- split: train
path: imdb_Movie_Expressed_Sentiment/train-*
- split: test
path: imdb_Movie_Expressed_Sentiment/test-*
- split: unsupervised
path: imdb_Movie_Expressed_Sentiment/unsupervised-*
- config_name: imdb_Movie_Expressed_Sentiment_2
data_files:
- split: train
path: imdb_Movie_Expressed_Sentiment_2/train-*
- split: test
path: imdb_Movie_Expressed_Sentiment_2/test-*
- split: unsupervised
path: imdb_Movie_Expressed_Sentiment_2/unsupervised-*
- config_name: imdb_Negation_template_for_positive_and_negative
data_files:
- split: train
path: imdb_Negation_template_for_positive_and_negative/train-*
- split: test
path: imdb_Negation_template_for_positive_and_negative/test-*
- split: unsupervised
path: imdb_Negation_template_for_positive_and_negative/unsupervised-*
- config_name: imdb_Reviewer_Enjoyment
data_files:
- split: train
path: imdb_Reviewer_Enjoyment/train-*
- split: test
path: imdb_Reviewer_Enjoyment/test-*
- split: unsupervised
path: imdb_Reviewer_Enjoyment/unsupervised-*
- config_name: imdb_Reviewer_Enjoyment_Yes_No
data_files:
- split: train
path: imdb_Reviewer_Enjoyment_Yes_No/train-*
- split: test
path: imdb_Reviewer_Enjoyment_Yes_No/test-*
- split: unsupervised
path: imdb_Reviewer_Enjoyment_Yes_No/unsupervised-*
- config_name: imdb_Reviewer_Expressed_Sentiment
data_files:
- split: train
path: imdb_Reviewer_Expressed_Sentiment/train-*
- split: test
path: imdb_Reviewer_Expressed_Sentiment/test-*
- split: unsupervised
path: imdb_Reviewer_Expressed_Sentiment/unsupervised-*
- config_name: imdb_Reviewer_Opinion_bad_good_choices
data_files:
- split: train
path: imdb_Reviewer_Opinion_bad_good_choices/train-*
- split: test
path: imdb_Reviewer_Opinion_bad_good_choices/test-*
- split: unsupervised
path: imdb_Reviewer_Opinion_bad_good_choices/unsupervised-*
- config_name: imdb_Reviewer_Sentiment_Feeling
data_files:
- split: train
path: imdb_Reviewer_Sentiment_Feeling/train-*
- split: test
path: imdb_Reviewer_Sentiment_Feeling/test-*
- split: unsupervised
path: imdb_Reviewer_Sentiment_Feeling/unsupervised-*
- config_name: imdb_Sentiment_with_choices_
data_files:
- split: train
path: imdb_Sentiment_with_choices_/train-*
- split: test
path: imdb_Sentiment_with_choices_/test-*
- split: unsupervised
path: imdb_Sentiment_with_choices_/unsupervised-*
- config_name: imdb_Text_Expressed_Sentiment
data_files:
- split: train
path: imdb_Text_Expressed_Sentiment/train-*
- split: test
path: imdb_Text_Expressed_Sentiment/test-*
- split: unsupervised
path: imdb_Text_Expressed_Sentiment/unsupervised-*
- config_name: imdb_Writer_Expressed_Sentiment
data_files:
- split: train
path: imdb_Writer_Expressed_Sentiment/train-*
- split: test
path: imdb_Writer_Expressed_Sentiment/test-*
- split: unsupervised
path: imdb_Writer_Expressed_Sentiment/unsupervised-*
- config_name: kilt_tasks_hotpotqa_combining_facts
data_files:
- split: train
path: kilt_tasks_hotpotqa_combining_facts/train-*
- split: validation
path: kilt_tasks_hotpotqa_combining_facts/validation-*
- config_name: kilt_tasks_hotpotqa_complex_question
data_files:
- split: train
path: kilt_tasks_hotpotqa_complex_question/train-*
- split: validation
path: kilt_tasks_hotpotqa_complex_question/validation-*
- config_name: kilt_tasks_hotpotqa_final_exam
data_files:
- split: train
path: kilt_tasks_hotpotqa_final_exam/train-*
- split: validation
path: kilt_tasks_hotpotqa_final_exam/validation-*
- config_name: kilt_tasks_hotpotqa_formulate
data_files:
- split: train
path: kilt_tasks_hotpotqa_formulate/train-*
- split: validation
path: kilt_tasks_hotpotqa_formulate/validation-*
- config_name: kilt_tasks_hotpotqa_straighforward_qa
data_files:
- split: train
path: kilt_tasks_hotpotqa_straighforward_qa/train-*
- split: validation
path: kilt_tasks_hotpotqa_straighforward_qa/validation-*
- config_name: multi_news_distill
data_files:
- split: train
path: multi_news_distill/train-*
- split: validation
path: multi_news_distill/validation-*
- split: test
path: multi_news_distill/test-*
- config_name: multi_news_expand_reverse_task_
data_files:
- split: train
path: multi_news_expand_reverse_task_/train-*
- split: validation
path: multi_news_expand_reverse_task_/validation-*
- split: test
path: multi_news_expand_reverse_task_/test-*
- config_name: multi_news_summarize
data_files:
- split: train
path: multi_news_summarize/train-*
- split: validation
path: multi_news_summarize/validation-*
- split: test
path: multi_news_summarize/test-*
- config_name: multi_news_summary_scenario
data_files:
- split: train
path: multi_news_summary_scenario/train-*
- split: validation
path: multi_news_summary_scenario/validation-*
- split: test
path: multi_news_summary_scenario/test-*
- config_name: multi_news_synthesize
data_files:
- split: train
path: multi_news_synthesize/train-*
- split: validation
path: multi_news_synthesize/validation-*
- split: test
path: multi_news_synthesize/test-*
- config_name: multi_news_what_are_the_key_points
data_files:
- split: train
path: multi_news_what_are_the_key_points/train-*
- split: validation
path: multi_news_what_are_the_key_points/validation-*
- split: test
path: multi_news_what_are_the_key_points/test-*
- config_name: openbookqa_main_choices
data_files:
- split: train
path: openbookqa_main_choices/train-*
- split: validation
path: openbookqa_main_choices/validation-*
- split: test
path: openbookqa_main_choices/test-*
- config_name: openbookqa_main_choose_an_answer_with_options
data_files:
- split: train
path: openbookqa_main_choose_an_answer_with_options/train-*
- split: validation
path: openbookqa_main_choose_an_answer_with_options/validation-*
- split: test
path: openbookqa_main_choose_an_answer_with_options/test-*
- config_name: openbookqa_main_only_options
data_files:
- split: train
path: openbookqa_main_only_options/train-*
- split: validation
path: openbookqa_main_only_options/validation-*
- split: test
path: openbookqa_main_only_options/test-*
- config_name: openbookqa_main_pick_answer_with_options
data_files:
- split: train
path: openbookqa_main_pick_answer_with_options/train-*
- split: validation
path: openbookqa_main_pick_answer_with_options/validation-*
- split: test
path: openbookqa_main_pick_answer_with_options/test-*
- config_name: openbookqa_main_pick_using_id
data_files:
- split: train
path: openbookqa_main_pick_using_id/train-*
- split: validation
path: openbookqa_main_pick_using_id/validation-*
- split: test
path: openbookqa_main_pick_using_id/test-*
- config_name: openbookqa_main_which_correct
data_files:
- split: train
path: openbookqa_main_which_correct/train-*
- split: validation
path: openbookqa_main_which_correct/validation-*
- split: test
path: openbookqa_main_which_correct/test-*
- config_name: openbookqa_main_which_correct_inverse
data_files:
- split: train
path: openbookqa_main_which_correct_inverse/train-*
- split: validation
path: openbookqa_main_which_correct_inverse/validation-*
- split: test
path: openbookqa_main_which_correct_inverse/test-*
- config_name: paws_labeled_final_Concatenation
data_files:
- split: train
path: paws_labeled_final_Concatenation/train-*
- split: validation
path: paws_labeled_final_Concatenation/validation-*
- split: test
path: paws_labeled_final_Concatenation/test-*
- config_name: paws_labeled_final_Concatenation_no_label
data_files:
- split: train
path: paws_labeled_final_Concatenation_no_label/train-*
- split: validation
path: paws_labeled_final_Concatenation_no_label/validation-*
- split: test
path: paws_labeled_final_Concatenation_no_label/test-*
- config_name: paws_labeled_final_Meaning
data_files:
- split: train
path: paws_labeled_final_Meaning/train-*
- split: validation
path: paws_labeled_final_Meaning/validation-*
- split: test
path: paws_labeled_final_Meaning/test-*
- config_name: paws_labeled_final_Meaning_no_label
data_files:
- split: train
path: paws_labeled_final_Meaning_no_label/train-*
- split: validation
path: paws_labeled_final_Meaning_no_label/validation-*
- split: test
path: paws_labeled_final_Meaning_no_label/test-*
- config_name: paws_labeled_final_PAWS_ANLI_GPT3
data_files:
- split: train
path: paws_labeled_final_PAWS_ANLI_GPT3/train-*
- split: validation
path: paws_labeled_final_PAWS_ANLI_GPT3/validation-*
- split: test
path: paws_labeled_final_PAWS_ANLI_GPT3/test-*
- config_name: paws_labeled_final_PAWS_ANLI_GPT3_no_label
data_files:
- split: train
path: paws_labeled_final_PAWS_ANLI_GPT3_no_label/train-*
- split: validation
path: paws_labeled_final_PAWS_ANLI_GPT3_no_label/validation-*
- split: test
path: paws_labeled_final_PAWS_ANLI_GPT3_no_label/test-*
- config_name: paws_labeled_final_Rewrite
data_files:
- split: train
path: paws_labeled_final_Rewrite/train-*
- split: validation
path: paws_labeled_final_Rewrite/validation-*
- split: test
path: paws_labeled_final_Rewrite/test-*
- config_name: paws_labeled_final_Rewrite_no_label
data_files:
- split: train
path: paws_labeled_final_Rewrite_no_label/train-*
- split: validation
path: paws_labeled_final_Rewrite_no_label/validation-*
- split: test
path: paws_labeled_final_Rewrite_no_label/test-*
- config_name: paws_labeled_final_context_question
data_files:
- split: train
path: paws_labeled_final_context_question/train-*
- split: validation
path: paws_labeled_final_context_question/validation-*
- split: test
path: paws_labeled_final_context_question/test-*
- config_name: paws_labeled_final_context_question_no_label
data_files:
- split: train
path: paws_labeled_final_context_question_no_label/train-*
- split: validation
path: paws_labeled_final_context_question_no_label/validation-*
- split: test
path: paws_labeled_final_context_question_no_label/test-*
- config_name: paws_labeled_final_paraphrase_task
data_files:
- split: train
path: paws_labeled_final_paraphrase_task/train-*
- split: validation
path: paws_labeled_final_paraphrase_task/validation-*
- split: test
path: paws_labeled_final_paraphrase_task/test-*
- config_name: paws_labeled_final_task_description_no_label
data_files:
- split: train
path: paws_labeled_final_task_description_no_label/train-*
- split: validation
path: paws_labeled_final_task_description_no_label/validation-*
- split: test
path: paws_labeled_final_task_description_no_label/test-*
- config_name: piqa_Correct_the_solution
data_files:
- split: train
path: piqa_Correct_the_solution/train-*
- split: validation
path: piqa_Correct_the_solution/validation-*
- split: test
path: piqa_Correct_the_solution/test-*
- config_name: piqa_Correct_the_solution_if_false_from_sol_1
data_files:
- split: train
path: piqa_Correct_the_solution_if_false_from_sol_1/train-*
- split: validation
path: piqa_Correct_the_solution_if_false_from_sol_1/validation-*
- split: test
path: piqa_Correct_the_solution_if_false_from_sol_1/test-*
- config_name: piqa_Correct_the_solution_if_false_from_sol_2
data_files:
- split: train
path: piqa_Correct_the_solution_if_false_from_sol_2/train-*
- split: validation
path: piqa_Correct_the_solution_if_false_from_sol_2/validation-*
- split: test
path: piqa_Correct_the_solution_if_false_from_sol_2/test-*
- config_name: piqa_Does_this_solution_make_sense_sol1
data_files:
- split: train
path: piqa_Does_this_solution_make_sense_sol1/train-*
- split: validation
path: piqa_Does_this_solution_make_sense_sol1/validation-*
- split: test
path: piqa_Does_this_solution_make_sense_sol1/test-*
- config_name: piqa_Does_this_solution_make_sense_sol2
data_files:
- split: train
path: piqa_Does_this_solution_make_sense_sol2/train-*
- split: validation
path: piqa_Does_this_solution_make_sense_sol2/validation-*
- split: test
path: piqa_Does_this_solution_make_sense_sol2/test-*
- config_name: piqa_choose_the_most_appropriate_solution
data_files:
- split: train
path: piqa_choose_the_most_appropriate_solution/train-*
- split: validation
path: piqa_choose_the_most_appropriate_solution/validation-*
- split: test
path: piqa_choose_the_most_appropriate_solution/test-*
- config_name: piqa_finish_sentence_with_correct_choice
data_files:
- split: train
path: piqa_finish_sentence_with_correct_choice/train-*
- split: validation
path: piqa_finish_sentence_with_correct_choice/validation-*
- split: test
path: piqa_finish_sentence_with_correct_choice/test-*
- config_name: piqa_no_prompt_needed
data_files:
- split: train
path: piqa_no_prompt_needed/train-*
- split: validation
path: piqa_no_prompt_needed/validation-*
- split: test
path: piqa_no_prompt_needed/test-*
- config_name: piqa_pick_correct_choice_index
data_files:
- split: train
path: piqa_pick_correct_choice_index/train-*
- split: validation
path: piqa_pick_correct_choice_index/validation-*
- split: test
path: piqa_pick_correct_choice_index/test-*
- config_name: piqa_pick_correct_choice_with_choice_given_before_goal
data_files:
- split: train
path: piqa_pick_correct_choice_with_choice_given_before_goal/train-*
- split: validation
path: piqa_pick_correct_choice_with_choice_given_before_goal/validation-*
- split: test
path: piqa_pick_correct_choice_with_choice_given_before_goal/test-*
- config_name: piqa_what_is_the_correct_ending
data_files:
- split: train
path: piqa_what_is_the_correct_ending/train-*
- split: validation
path: piqa_what_is_the_correct_ending/validation-*
- split: test
path: piqa_what_is_the_correct_ending/test-*
- config_name: qasc_is_correct_1
data_files:
- split: train
path: qasc_is_correct_1/train-*
- split: validation
path: qasc_is_correct_1/validation-*
- split: test
path: qasc_is_correct_1/test-*
- config_name: qasc_is_correct_2
data_files:
- split: train
path: qasc_is_correct_2/train-*
- split: validation
path: qasc_is_correct_2/validation-*
- split: test
path: qasc_is_correct_2/test-*
- config_name: qasc_qa_with_combined_facts_1
data_files:
- split: train
path: qasc_qa_with_combined_facts_1/train-*
- split: validation
path: qasc_qa_with_combined_facts_1/validation-*
- split: test
path: qasc_qa_with_combined_facts_1/test-*
- config_name: qasc_qa_with_separated_facts_1
data_files:
- split: train
path: qasc_qa_with_separated_facts_1/train-*
- split: validation
path: qasc_qa_with_separated_facts_1/validation-*
- split: test
path: qasc_qa_with_separated_facts_1/test-*
- config_name: qasc_qa_with_separated_facts_2
data_files:
- split: train
path: qasc_qa_with_separated_facts_2/train-*
- split: validation
path: qasc_qa_with_separated_facts_2/validation-*
- split: test
path: qasc_qa_with_separated_facts_2/test-*
- config_name: qasc_qa_with_separated_facts_3
data_files:
- split: train
path: qasc_qa_with_separated_facts_3/train-*
- split: validation
path: qasc_qa_with_separated_facts_3/validation-*
- split: test
path: qasc_qa_with_separated_facts_3/test-*
- config_name: qasc_qa_with_separated_facts_4
data_files:
- split: train
path: qasc_qa_with_separated_facts_4/train-*
- split: validation
path: qasc_qa_with_separated_facts_4/validation-*
- split: test
path: qasc_qa_with_separated_facts_4/test-*
- config_name: qasc_qa_with_separated_facts_5
data_files:
- split: train
path: qasc_qa_with_separated_facts_5/train-*
- split: validation
path: qasc_qa_with_separated_facts_5/validation-*
- split: test
path: qasc_qa_with_separated_facts_5/test-*
- config_name: quail_context_description_question_answer_id
data_files:
- split: train
path: quail_context_description_question_answer_id/train-*
- split: validation
path: quail_context_description_question_answer_id/validation-*
- split: challenge
path: quail_context_description_question_answer_id/challenge-*
- config_name: quail_context_description_question_answer_text
data_files:
- split: train
path: quail_context_description_question_answer_text/train-*
- split: validation
path: quail_context_description_question_answer_text/validation-*
- split: challenge
path: quail_context_description_question_answer_text/challenge-*
- config_name: quail_context_description_question_text
data_files:
- split: train
path: quail_context_description_question_text/train-*
- split: validation
path: quail_context_description_question_text/validation-*
- split: challenge
path: quail_context_description_question_text/challenge-*
- config_name: quail_context_question_answer_description_id
data_files:
- split: train
path: quail_context_question_answer_description_id/train-*
- split: validation
path: quail_context_question_answer_description_id/validation-*
- split: challenge
path: quail_context_question_answer_description_id/challenge-*
- config_name: quail_context_question_answer_description_text
data_files:
- split: train
path: quail_context_question_answer_description_text/train-*
- split: validation
path: quail_context_question_answer_description_text/validation-*
- split: challenge
path: quail_context_question_answer_description_text/challenge-*
- config_name: quail_context_question_description_answer_id
data_files:
- split: train
path: quail_context_question_description_answer_id/train-*
- split: validation
path: quail_context_question_description_answer_id/validation-*
- split: challenge
path: quail_context_question_description_answer_id/challenge-*
- config_name: quail_context_question_description_answer_text
data_files:
- split: train
path: quail_context_question_description_answer_text/train-*
- split: validation
path: quail_context_question_description_answer_text/validation-*
- split: challenge
path: quail_context_question_description_answer_text/challenge-*
- config_name: quail_context_question_description_text
data_files:
- split: train
path: quail_context_question_description_text/train-*
- split: validation
path: quail_context_question_description_text/validation-*
- split: challenge
path: quail_context_question_description_text/challenge-*
- config_name: quail_description_context_question_answer_id
data_files:
- split: train
path: quail_description_context_question_answer_id/train-*
- split: validation
path: quail_description_context_question_answer_id/validation-*
- split: challenge
path: quail_description_context_question_answer_id/challenge-*
- config_name: quail_description_context_question_answer_text
data_files:
- split: train
path: quail_description_context_question_answer_text/train-*
- split: validation
path: quail_description_context_question_answer_text/validation-*
- split: challenge
path: quail_description_context_question_answer_text/challenge-*
- config_name: quail_description_context_question_text
data_files:
- split: train
path: quail_description_context_question_text/train-*
- split: validation
path: quail_description_context_question_text/validation-*
- split: challenge
path: quail_description_context_question_text/challenge-*
- config_name: quail_no_prompt_id
data_files:
- split: train
path: quail_no_prompt_id/train-*
- split: validation
path: quail_no_prompt_id/validation-*
- split: challenge
path: quail_no_prompt_id/challenge-*
- config_name: quail_no_prompt_text
data_files:
- split: train
path: quail_no_prompt_text/train-*
- split: validation
path: quail_no_prompt_text/validation-*
- split: challenge
path: quail_no_prompt_text/challenge-*
- config_name: quarel_choose_between
data_files:
- split: train
path: quarel_choose_between/train-*
- split: validation
path: quarel_choose_between/validation-*
- split: test
path: quarel_choose_between/test-*
- config_name: quarel_do_not_use
data_files:
- split: train
path: quarel_do_not_use/train-*
- split: validation
path: quarel_do_not_use/validation-*
- split: test
path: quarel_do_not_use/test-*
- config_name: quarel_heres_a_story
data_files:
- split: train
path: quarel_heres_a_story/train-*
- split: validation
path: quarel_heres_a_story/validation-*
- split: test
path: quarel_heres_a_story/test-*
- config_name: quarel_logic_test
data_files:
- split: train
path: quarel_logic_test/train-*
- split: validation
path: quarel_logic_test/validation-*
- split: test
path: quarel_logic_test/test-*
- config_name: quarel_testing_students
data_files:
- split: train
path: quarel_testing_students/train-*
- split: validation
path: quarel_testing_students/validation-*
- split: test
path: quarel_testing_students/test-*
- config_name: quartz_answer_question_based_on
data_files:
- split: train
path: quartz_answer_question_based_on/train-*
- split: validation
path: quartz_answer_question_based_on/validation-*
- split: test
path: quartz_answer_question_based_on/test-*
- config_name: quartz_answer_question_below
data_files:
- split: train
path: quartz_answer_question_below/train-*
- split: validation
path: quartz_answer_question_below/validation-*
- split: test
path: quartz_answer_question_below/test-*
- config_name: quartz_given_the_fact_answer_the_q
data_files:
- split: train
path: quartz_given_the_fact_answer_the_q/train-*
- split: validation
path: quartz_given_the_fact_answer_the_q/validation-*
- split: test
path: quartz_given_the_fact_answer_the_q/test-*
- config_name: quartz_having_read_above_passage
data_files:
- split: train
path: quartz_having_read_above_passage/train-*
- split: validation
path: quartz_having_read_above_passage/validation-*
- split: test
path: quartz_having_read_above_passage/test-*
- config_name: quartz_paragraph_question_plain_concat
data_files:
- split: train
path: quartz_paragraph_question_plain_concat/train-*
- split: validation
path: quartz_paragraph_question_plain_concat/validation-*
- split: test
path: quartz_paragraph_question_plain_concat/test-*
- config_name: quartz_read_passage_below_choose
data_files:
- split: train
path: quartz_read_passage_below_choose/train-*
- split: validation
path: quartz_read_passage_below_choose/validation-*
- split: test
path: quartz_read_passage_below_choose/test-*
- config_name: quartz_use_info_from_paragraph_question
data_files:
- split: train
path: quartz_use_info_from_paragraph_question/train-*
- split: validation
path: quartz_use_info_from_paragraph_question/validation-*
- split: test
path: quartz_use_info_from_paragraph_question/test-*
- config_name: quartz_use_info_from_question_paragraph
data_files:
- split: train
path: quartz_use_info_from_question_paragraph/train-*
- split: validation
path: quartz_use_info_from_question_paragraph/validation-*
- split: test
path: quartz_use_info_from_question_paragraph/test-*
- config_name: quoref_Answer_Friend_Question
data_files:
- split: train
path: quoref_Answer_Friend_Question/train-*
- split: validation
path: quoref_Answer_Friend_Question/validation-*
- config_name: quoref_Answer_Question_Given_Context
data_files:
- split: train
path: quoref_Answer_Question_Given_Context/train-*
- split: validation
path: quoref_Answer_Question_Given_Context/validation-*
- config_name: quoref_Answer_Test
data_files:
- split: train
path: quoref_Answer_Test/train-*
- split: validation
path: quoref_Answer_Test/validation-*
- config_name: quoref_Context_Contains_Answer
data_files:
- split: train
path: quoref_Context_Contains_Answer/train-*
- split: validation
path: quoref_Context_Contains_Answer/validation-*
- config_name: quoref_Find_Answer
data_files:
- split: train
path: quoref_Find_Answer/train-*
- split: validation
path: quoref_Find_Answer/validation-*
- config_name: quoref_Found_Context_Online
data_files:
- split: train
path: quoref_Found_Context_Online/train-*
- split: validation
path: quoref_Found_Context_Online/validation-*
- config_name: quoref_Given_Context_Answer_Question
data_files:
- split: train
path: quoref_Given_Context_Answer_Question/train-*
- split: validation
path: quoref_Given_Context_Answer_Question/validation-*
- config_name: quoref_Guess_Answer
data_files:
- split: train
path: quoref_Guess_Answer/train-*
- split: validation
path: quoref_Guess_Answer/validation-*
- config_name: quoref_Guess_Title_For_Context
data_files:
- split: train
path: quoref_Guess_Title_For_Context/train-*
- split: validation
path: quoref_Guess_Title_For_Context/validation-*
- config_name: quoref_Read_And_Extract_
data_files:
- split: train
path: quoref_Read_And_Extract_/train-*
- split: validation
path: quoref_Read_And_Extract_/validation-*
- config_name: quoref_What_Is_The_Answer
data_files:
- split: train
path: quoref_What_Is_The_Answer/train-*
- split: validation
path: quoref_What_Is_The_Answer/validation-*
- config_name: race_high_Is_this_the_right_answer
data_files:
- split: train
path: race_high_Is_this_the_right_answer/train-*
- split: validation
path: race_high_Is_this_the_right_answer/validation-*
- split: test
path: race_high_Is_this_the_right_answer/test-*
- config_name: race_high_Read_the_article_and_answer_the_question_no_option_
data_files:
- split: train
path: race_high_Read_the_article_and_answer_the_question_no_option_/train-*
- split: validation
path: race_high_Read_the_article_and_answer_the_question_no_option_/validation-*
- split: test
path: race_high_Read_the_article_and_answer_the_question_no_option_/test-*
- config_name: race_high_Select_the_best_answer
data_files:
- split: train
path: race_high_Select_the_best_answer/train-*
- split: validation
path: race_high_Select_the_best_answer/validation-*
- split: test
path: race_high_Select_the_best_answer/test-*
- config_name: race_high_Select_the_best_answer_generate_span_
data_files:
- split: train
path: race_high_Select_the_best_answer_generate_span_/train-*
- split: validation
path: race_high_Select_the_best_answer_generate_span_/validation-*
- split: test
path: race_high_Select_the_best_answer_generate_span_/test-*
- config_name: race_high_Select_the_best_answer_no_instructions_
data_files:
- split: train
path: race_high_Select_the_best_answer_no_instructions_/train-*
- split: validation
path: race_high_Select_the_best_answer_no_instructions_/validation-*
- split: test
path: race_high_Select_the_best_answer_no_instructions_/test-*
- config_name: race_high_Taking_a_test
data_files:
- split: train
path: race_high_Taking_a_test/train-*
- split: validation
path: race_high_Taking_a_test/validation-*
- split: test
path: race_high_Taking_a_test/test-*
- config_name: race_high_Write_a_multi_choice_question_for_the_following_article
data_files:
- split: train
path: race_high_Write_a_multi_choice_question_for_the_following_article/train-*
- split: validation
path: race_high_Write_a_multi_choice_question_for_the_following_article/validation-*
- split: test
path: race_high_Write_a_multi_choice_question_for_the_following_article/test-*
- config_name: race_high_Write_a_multi_choice_question_options_given_
data_files:
- split: train
path: race_high_Write_a_multi_choice_question_options_given_/train-*
- split: validation
path: race_high_Write_a_multi_choice_question_options_given_/validation-*
- split: test
path: race_high_Write_a_multi_choice_question_options_given_/test-*
- config_name: race_middle_Is_this_the_right_answer
data_files:
- split: train
path: race_middle_Is_this_the_right_answer/train-*
- split: validation
path: race_middle_Is_this_the_right_answer/validation-*
- split: test
path: race_middle_Is_this_the_right_answer/test-*
- config_name: race_middle_Read_the_article_and_answer_the_question_no_option_
data_files:
- split: train
path: race_middle_Read_the_article_and_answer_the_question_no_option_/train-*
- split: validation
path: race_middle_Read_the_article_and_answer_the_question_no_option_/validation-*
- split: test
path: race_middle_Read_the_article_and_answer_the_question_no_option_/test-*
- config_name: race_middle_Select_the_best_answer
data_files:
- split: train
path: race_middle_Select_the_best_answer/train-*
- split: validation
path: race_middle_Select_the_best_answer/validation-*
- split: test
path: race_middle_Select_the_best_answer/test-*
- config_name: race_middle_Select_the_best_answer_generate_span_
data_files:
- split: train
path: race_middle_Select_the_best_answer_generate_span_/train-*
- split: validation
path: race_middle_Select_the_best_answer_generate_span_/validation-*
- split: test
path: race_middle_Select_the_best_answer_generate_span_/test-*
- config_name: race_middle_Select_the_best_answer_no_instructions_
data_files:
- split: train
path: race_middle_Select_the_best_answer_no_instructions_/train-*
- split: validation
path: race_middle_Select_the_best_answer_no_instructions_/validation-*
- split: test
path: race_middle_Select_the_best_answer_no_instructions_/test-*
- config_name: race_middle_Taking_a_test
data_files:
- split: train
path: race_middle_Taking_a_test/train-*
- split: validation
path: race_middle_Taking_a_test/validation-*
- split: test
path: race_middle_Taking_a_test/test-*
- config_name: race_middle_Write_a_multi_choice_question_for_the_following_article
data_files:
- split: train
path: race_middle_Write_a_multi_choice_question_for_the_following_article/train-*
- split: validation
path: race_middle_Write_a_multi_choice_question_for_the_following_article/validation-*
- split: test
path: race_middle_Write_a_multi_choice_question_for_the_following_article/test-*
- config_name: race_middle_Write_a_multi_choice_question_options_given_
data_files:
- split: train
path: race_middle_Write_a_multi_choice_question_options_given_/train-*
- split: validation
path: race_middle_Write_a_multi_choice_question_options_given_/validation-*
- split: test
path: race_middle_Write_a_multi_choice_question_options_given_/test-*
- config_name: ropes_background_new_situation_answer
data_files:
- split: train
path: ropes_background_new_situation_answer/train-*
- split: validation
path: ropes_background_new_situation_answer/validation-*
- config_name: ropes_background_situation_middle
data_files:
- split: train
path: ropes_background_situation_middle/train-*
- split: validation
path: ropes_background_situation_middle/validation-*
- config_name: ropes_given_background_situation
data_files:
- split: train
path: ropes_given_background_situation/train-*
- split: validation
path: ropes_given_background_situation/validation-*
- config_name: ropes_new_situation_background_answer
data_files:
- split: train
path: ropes_new_situation_background_answer/train-*
- split: validation
path: ropes_new_situation_background_answer/validation-*
- config_name: ropes_plain_background_situation
data_files:
- split: train
path: ropes_plain_background_situation/train-*
- split: validation
path: ropes_plain_background_situation/validation-*
- config_name: ropes_plain_bottom_hint
data_files:
- split: train
path: ropes_plain_bottom_hint/train-*
- split: validation
path: ropes_plain_bottom_hint/validation-*
- config_name: ropes_plain_no_background
data_files:
- split: train
path: ropes_plain_no_background/train-*
- split: validation
path: ropes_plain_no_background/validation-*
- config_name: ropes_prompt_beginning
data_files:
- split: train
path: ropes_prompt_beginning/train-*
- split: validation
path: ropes_prompt_beginning/validation-*
- config_name: ropes_prompt_bottom_hint_beginning
data_files:
- split: train
path: ropes_prompt_bottom_hint_beginning/train-*
- split: validation
path: ropes_prompt_bottom_hint_beginning/validation-*
- config_name: ropes_prompt_bottom_no_hint
data_files:
- split: train
path: ropes_prompt_bottom_no_hint/train-*
- split: validation
path: ropes_prompt_bottom_no_hint/validation-*
- config_name: ropes_prompt_mix
data_files:
- split: train
path: ropes_prompt_mix/train-*
- split: validation
path: ropes_prompt_mix/validation-*
- config_name: ropes_read_background_situation
data_files:
- split: train
path: ropes_read_background_situation/train-*
- split: validation
path: ropes_read_background_situation/validation-*
- config_name: rotten_tomatoes_Movie_Expressed_Sentiment
data_files:
- split: train
path: rotten_tomatoes_Movie_Expressed_Sentiment/train-*
- split: validation
path: rotten_tomatoes_Movie_Expressed_Sentiment/validation-*
- split: test
path: rotten_tomatoes_Movie_Expressed_Sentiment/test-*
- config_name: rotten_tomatoes_Movie_Expressed_Sentiment_2
data_files:
- split: train
path: rotten_tomatoes_Movie_Expressed_Sentiment_2/train-*
- split: validation
path: rotten_tomatoes_Movie_Expressed_Sentiment_2/validation-*
- split: test
path: rotten_tomatoes_Movie_Expressed_Sentiment_2/test-*
- config_name: rotten_tomatoes_Reviewer_Enjoyment
data_files:
- split: train
path: rotten_tomatoes_Reviewer_Enjoyment/train-*
- split: validation
path: rotten_tomatoes_Reviewer_Enjoyment/validation-*
- split: test
path: rotten_tomatoes_Reviewer_Enjoyment/test-*
- config_name: rotten_tomatoes_Reviewer_Enjoyment_Yes_No
data_files:
- split: train
path: rotten_tomatoes_Reviewer_Enjoyment_Yes_No/train-*
- split: validation
path: rotten_tomatoes_Reviewer_Enjoyment_Yes_No/validation-*
- split: test
path: rotten_tomatoes_Reviewer_Enjoyment_Yes_No/test-*
- config_name: rotten_tomatoes_Reviewer_Expressed_Sentiment
data_files:
- split: train
path: rotten_tomatoes_Reviewer_Expressed_Sentiment/train-*
- split: validation
path: rotten_tomatoes_Reviewer_Expressed_Sentiment/validation-*
- split: test
path: rotten_tomatoes_Reviewer_Expressed_Sentiment/test-*
- config_name: rotten_tomatoes_Reviewer_Opinion_bad_good_choices
data_files:
- split: train
path: rotten_tomatoes_Reviewer_Opinion_bad_good_choices/train-*
- split: validation
path: rotten_tomatoes_Reviewer_Opinion_bad_good_choices/validation-*
- split: test
path: rotten_tomatoes_Reviewer_Opinion_bad_good_choices/test-*
- config_name: rotten_tomatoes_Reviewer_Sentiment_Feeling
data_files:
- split: train
path: rotten_tomatoes_Reviewer_Sentiment_Feeling/train-*
- split: validation
path: rotten_tomatoes_Reviewer_Sentiment_Feeling/validation-*
- split: test
path: rotten_tomatoes_Reviewer_Sentiment_Feeling/test-*
- config_name: rotten_tomatoes_Sentiment_with_choices_
data_files:
- split: train
path: rotten_tomatoes_Sentiment_with_choices_/train-*
- split: validation
path: rotten_tomatoes_Sentiment_with_choices_/validation-*
- split: test
path: rotten_tomatoes_Sentiment_with_choices_/test-*
- config_name: rotten_tomatoes_Text_Expressed_Sentiment
data_files:
- split: train
path: rotten_tomatoes_Text_Expressed_Sentiment/train-*
- split: validation
path: rotten_tomatoes_Text_Expressed_Sentiment/validation-*
- split: test
path: rotten_tomatoes_Text_Expressed_Sentiment/test-*
- config_name: rotten_tomatoes_Writer_Expressed_Sentiment
data_files:
- split: train
path: rotten_tomatoes_Writer_Expressed_Sentiment/train-*
- split: validation
path: rotten_tomatoes_Writer_Expressed_Sentiment/validation-*
- split: test
path: rotten_tomatoes_Writer_Expressed_Sentiment/test-*
- config_name: samsum_Generate_a_summary_for_this_dialogue
data_files:
- split: train
path: samsum_Generate_a_summary_for_this_dialogue/train-*
- split: validation
path: samsum_Generate_a_summary_for_this_dialogue/validation-*
- split: test
path: samsum_Generate_a_summary_for_this_dialogue/test-*
- config_name: samsum_Given_the_above_dialogue_write_a_summary
data_files:
- split: train
path: samsum_Given_the_above_dialogue_write_a_summary/train-*
- split: validation
path: samsum_Given_the_above_dialogue_write_a_summary/validation-*
- split: test
path: samsum_Given_the_above_dialogue_write_a_summary/test-*
- config_name: samsum_Sum_up_the_following_dialogue
data_files:
- split: train
path: samsum_Sum_up_the_following_dialogue/train-*
- split: validation
path: samsum_Sum_up_the_following_dialogue/validation-*
- split: test
path: samsum_Sum_up_the_following_dialogue/test-*
- config_name: samsum_Summarize_
data_files:
- split: train
path: samsum_Summarize_/train-*
- split: validation
path: samsum_Summarize_/validation-*
- split: test
path: samsum_Summarize_/test-*
- config_name: samsum_Summarize_this_dialogue_
data_files:
- split: train
path: samsum_Summarize_this_dialogue_/train-*
- split: validation
path: samsum_Summarize_this_dialogue_/validation-*
- split: test
path: samsum_Summarize_this_dialogue_/test-*
- config_name: samsum_To_sum_up_this_dialog
data_files:
- split: train
path: samsum_To_sum_up_this_dialog/train-*
- split: validation
path: samsum_To_sum_up_this_dialog/validation-*
- split: test
path: samsum_To_sum_up_this_dialog/test-*
- config_name: samsum_Write_a_dialogue_that_match_this_summary
data_files:
- split: train
path: samsum_Write_a_dialogue_that_match_this_summary/train-*
- split: validation
path: samsum_Write_a_dialogue_that_match_this_summary/validation-*
- split: test
path: samsum_Write_a_dialogue_that_match_this_summary/test-*
- config_name: sciq_Direct_Question
data_files:
- split: train
path: sciq_Direct_Question/train-*
- split: validation
path: sciq_Direct_Question/validation-*
- split: test
path: sciq_Direct_Question/test-*
- config_name: sciq_Direct_Question_Closed_Book_
data_files:
- split: train
path: sciq_Direct_Question_Closed_Book_/train-*
- split: validation
path: sciq_Direct_Question_Closed_Book_/validation-*
- split: test
path: sciq_Direct_Question_Closed_Book_/test-*
- config_name: sciq_Multiple_Choice
data_files:
- split: train
path: sciq_Multiple_Choice/train-*
- split: validation
path: sciq_Multiple_Choice/validation-*
- split: test
path: sciq_Multiple_Choice/test-*
- config_name: sciq_Multiple_Choice_Closed_Book_
data_files:
- split: train
path: sciq_Multiple_Choice_Closed_Book_/train-*
- split: validation
path: sciq_Multiple_Choice_Closed_Book_/validation-*
- split: test
path: sciq_Multiple_Choice_Closed_Book_/test-*
- config_name: sciq_Multiple_Choice_Question_First
data_files:
- split: train
path: sciq_Multiple_Choice_Question_First/train-*
- split: validation
path: sciq_Multiple_Choice_Question_First/validation-*
- split: test
path: sciq_Multiple_Choice_Question_First/test-*
- config_name: social_i_qa_Check_if_a_random_answer_is_valid_or_not
data_files:
- split: train
path: social_i_qa_Check_if_a_random_answer_is_valid_or_not/train-*
- split: validation
path: social_i_qa_Check_if_a_random_answer_is_valid_or_not/validation-*
- config_name: social_i_qa_Generate_answer
data_files:
- split: train
path: social_i_qa_Generate_answer/train-*
- split: validation
path: social_i_qa_Generate_answer/validation-*
- config_name: social_i_qa_Generate_the_question_from_the_answer
data_files:
- split: train
path: social_i_qa_Generate_the_question_from_the_answer/train-*
- split: validation
path: social_i_qa_Generate_the_question_from_the_answer/validation-*
- config_name: social_i_qa_I_was_wondering
data_files:
- split: train
path: social_i_qa_I_was_wondering/train-*
- split: validation
path: social_i_qa_I_was_wondering/validation-*
- config_name: social_i_qa_Show_choices_and_generate_answer
data_files:
- split: train
path: social_i_qa_Show_choices_and_generate_answer/train-*
- split: validation
path: social_i_qa_Show_choices_and_generate_answer/validation-*
- config_name: social_i_qa_Show_choices_and_generate_index
data_files:
- split: train
path: social_i_qa_Show_choices_and_generate_index/train-*
- split: validation
path: social_i_qa_Show_choices_and_generate_index/validation-*
- config_name: squad_v2_Jeopardy_with_Context
data_files:
- split: train
path: squad_v2_Jeopardy_with_Context/train-*
- split: validation
path: squad_v2_Jeopardy_with_Context/validation-*
- config_name: squad_v2_Jeopardy_without_Context
data_files:
- split: train
path: squad_v2_Jeopardy_without_Context/train-*
- split: validation
path: squad_v2_Jeopardy_without_Context/validation-*
- config_name: squad_v2_Questions_with_Context
data_files:
- split: train
path: squad_v2_Questions_with_Context/train-*
- split: validation
path: squad_v2_Questions_with_Context/validation-*
- config_name: squad_v2_Questions_with_Context_Without_Prompt_Keywords
data_files:
- split: train
path: squad_v2_Questions_with_Context_Without_Prompt_Keywords/train-*
- split: validation
path: squad_v2_Questions_with_Context_Without_Prompt_Keywords/validation-*
- config_name: squad_v2_Questions_with_Context_Without_Prompt_Keywords_unanswerable
data_files:
- split: train
path: squad_v2_Questions_with_Context_Without_Prompt_Keywords_unanswerable/train-*
- split: validation
path: squad_v2_Questions_with_Context_Without_Prompt_Keywords_unanswerable/validation-*
- config_name: squad_v2_Questions_with_Context_unanswerable
data_files:
- split: train
path: squad_v2_Questions_with_Context_unanswerable/train-*
- split: validation
path: squad_v2_Questions_with_Context_unanswerable/validation-*
- config_name: squad_v2_Topic_Prediction_Context
data_files:
- split: train
path: squad_v2_Topic_Prediction_Context/train-*
- split: validation
path: squad_v2_Topic_Prediction_Context/validation-*
- config_name: squad_v2_Topic_Prediction_Context_with_randomized_prompt_options
data_files:
- split: train
path: squad_v2_Topic_Prediction_Context_with_randomized_prompt_options/train-*
- split: validation
path: squad_v2_Topic_Prediction_Context_with_randomized_prompt_options/validation-*
- config_name: squad_v2_Topic_Prediction_Context_with_randomized_prompt_options_placed_in_the_end
data_files:
- split: train
path: squad_v2_Topic_Prediction_Context_with_randomized_prompt_options_placed_in_the_end/train-*
- split: validation
path: squad_v2_Topic_Prediction_Context_with_randomized_prompt_options_placed_in_the_end/validation-*
- config_name: squad_v2_Topic_Prediction_Question_and_Answer_Pair
data_files:
- split: train
path: squad_v2_Topic_Prediction_Question_and_Answer_Pair/train-*
- split: validation
path: squad_v2_Topic_Prediction_Question_and_Answer_Pair/validation-*
- config_name: squad_v2_Trivia
data_files:
- split: train
path: squad_v2_Trivia/train-*
- split: validation
path: squad_v2_Trivia/validation-*
- config_name: squad_v2_Unanwerable_question
data_files:
- split: train
path: squad_v2_Unanwerable_question/train-*
- split: validation
path: squad_v2_Unanwerable_question/validation-*
- config_name: super_glue_boolq_GPT_3_Style
data_files:
- split: train
path: super_glue_boolq_GPT_3_Style/train-*
- split: validation
path: super_glue_boolq_GPT_3_Style/validation-*
- split: test
path: super_glue_boolq_GPT_3_Style/test-*
- config_name: super_glue_boolq_I_wonder_
data_files:
- split: train
path: super_glue_boolq_I_wonder_/train-*
- split: validation
path: super_glue_boolq_I_wonder_/validation-*
- split: test
path: super_glue_boolq_I_wonder_/test-*
- config_name: super_glue_boolq_after_reading
data_files:
- split: train
path: super_glue_boolq_after_reading/train-*
- split: validation
path: super_glue_boolq_after_reading/validation-*
- split: test
path: super_glue_boolq_after_reading/test-*
- config_name: super_glue_boolq_based_on_the_following_passage
data_files:
- split: train
path: super_glue_boolq_based_on_the_following_passage/train-*
- split: validation
path: super_glue_boolq_based_on_the_following_passage/validation-*
- split: test
path: super_glue_boolq_based_on_the_following_passage/test-*
- config_name: super_glue_boolq_based_on_the_previous_passage
data_files:
- split: train
path: super_glue_boolq_based_on_the_previous_passage/train-*
- split: validation
path: super_glue_boolq_based_on_the_previous_passage/validation-*
- split: test
path: super_glue_boolq_based_on_the_previous_passage/test-*
- config_name: super_glue_boolq_could_you_tell_me_
data_files:
- split: train
path: super_glue_boolq_could_you_tell_me_/train-*
- split: validation
path: super_glue_boolq_could_you_tell_me_/validation-*
- split: test
path: super_glue_boolq_could_you_tell_me_/test-*
- config_name: super_glue_boolq_exam
data_files:
- split: train
path: super_glue_boolq_exam/train-*
- split: validation
path: super_glue_boolq_exam/validation-*
- split: test
path: super_glue_boolq_exam/test-*
- config_name: super_glue_boolq_exercise
data_files:
- split: train
path: super_glue_boolq_exercise/train-*
- split: validation
path: super_glue_boolq_exercise/validation-*
- split: test
path: super_glue_boolq_exercise/test-*
- config_name: super_glue_boolq_valid_binary
data_files:
- split: train
path: super_glue_boolq_valid_binary/train-*
- split: validation
path: super_glue_boolq_valid_binary/validation-*
- split: test
path: super_glue_boolq_valid_binary/test-*
- config_name: super_glue_boolq_yes_no_question
data_files:
- split: train
path: super_glue_boolq_yes_no_question/train-*
- split: validation
path: super_glue_boolq_yes_no_question/validation-*
- split: test
path: super_glue_boolq_yes_no_question/test-*
- config_name: super_glue_cb_GPT_3_style
data_files:
- split: train
path: super_glue_cb_GPT_3_style/train-*
- split: validation
path: super_glue_cb_GPT_3_style/validation-*
- split: test
path: super_glue_cb_GPT_3_style/test-*
- config_name: super_glue_cb_GPT_3_style_score_eval
data_files:
- split: train
path: super_glue_cb_GPT_3_style_score_eval/train-*
- split: validation
path: super_glue_cb_GPT_3_style_score_eval/validation-*
- split: test
path: super_glue_cb_GPT_3_style_score_eval/test-*
- config_name: super_glue_cb_MNLI_crowdsource
data_files:
- split: train
path: super_glue_cb_MNLI_crowdsource/train-*
- split: validation
path: super_glue_cb_MNLI_crowdsource/validation-*
- split: test
path: super_glue_cb_MNLI_crowdsource/test-*
- config_name: super_glue_cb_MNLI_crowdsource_score_eval
data_files:
- split: train
path: super_glue_cb_MNLI_crowdsource_score_eval/train-*
- split: validation
path: super_glue_cb_MNLI_crowdsource_score_eval/validation-*
- split: test
path: super_glue_cb_MNLI_crowdsource_score_eval/test-*
- config_name: super_glue_cb_always_sometimes_never
data_files:
- split: train
path: super_glue_cb_always_sometimes_never/train-*
- split: validation
path: super_glue_cb_always_sometimes_never/validation-*
- split: test
path: super_glue_cb_always_sometimes_never/test-*
- config_name: super_glue_cb_always_sometimes_never_score_eval
data_files:
- split: train
path: super_glue_cb_always_sometimes_never_score_eval/train-*
- split: validation
path: super_glue_cb_always_sometimes_never_score_eval/validation-*
- split: test
path: super_glue_cb_always_sometimes_never_score_eval/test-*
- config_name: super_glue_cb_based_on_the_previous_passage
data_files:
- split: train
path: super_glue_cb_based_on_the_previous_passage/train-*
- split: validation
path: super_glue_cb_based_on_the_previous_passage/validation-*
- split: test
path: super_glue_cb_based_on_the_previous_passage/test-*
- config_name: super_glue_cb_based_on_the_previous_passage_score_eval
data_files:
- split: train
path: super_glue_cb_based_on_the_previous_passage_score_eval/train-*
- split: validation
path: super_glue_cb_based_on_the_previous_passage_score_eval/validation-*
- split: test
path: super_glue_cb_based_on_the_previous_passage_score_eval/test-*
- config_name: super_glue_cb_can_we_infer
data_files:
- split: train
path: super_glue_cb_can_we_infer/train-*
- split: validation
path: super_glue_cb_can_we_infer/validation-*
- split: test
path: super_glue_cb_can_we_infer/test-*
- config_name: super_glue_cb_can_we_infer_score_eval
data_files:
- split: train
path: super_glue_cb_can_we_infer_score_eval/train-*
- split: validation
path: super_glue_cb_can_we_infer_score_eval/validation-*
- split: test
path: super_glue_cb_can_we_infer_score_eval/test-*
- config_name: super_glue_cb_claim_true_false_inconclusive
data_files:
- split: train
path: super_glue_cb_claim_true_false_inconclusive/train-*
- split: validation
path: super_glue_cb_claim_true_false_inconclusive/validation-*
- split: test
path: super_glue_cb_claim_true_false_inconclusive/test-*
- config_name: super_glue_cb_claim_true_false_inconclusive_score_eval
data_files:
- split: train
path: super_glue_cb_claim_true_false_inconclusive_score_eval/train-*
- split: validation
path: super_glue_cb_claim_true_false_inconclusive_score_eval/validation-*
- split: test
path: super_glue_cb_claim_true_false_inconclusive_score_eval/test-*
- config_name: super_glue_cb_consider_always_sometimes_never
data_files:
- split: train
path: super_glue_cb_consider_always_sometimes_never/train-*
- split: validation
path: super_glue_cb_consider_always_sometimes_never/validation-*
- split: test
path: super_glue_cb_consider_always_sometimes_never/test-*
- config_name: super_glue_cb_consider_always_sometimes_never_score_eval
data_files:
- split: train
path: super_glue_cb_consider_always_sometimes_never_score_eval/train-*
- split: validation
path: super_glue_cb_consider_always_sometimes_never_score_eval/validation-*
- split: test
path: super_glue_cb_consider_always_sometimes_never_score_eval/test-*
- config_name: super_glue_cb_does_it_follow_that
data_files:
- split: train
path: super_glue_cb_does_it_follow_that/train-*
- split: validation
path: super_glue_cb_does_it_follow_that/validation-*
- split: test
path: super_glue_cb_does_it_follow_that/test-*
- config_name: super_glue_cb_does_it_follow_that_score_eval
data_files:
- split: train
path: super_glue_cb_does_it_follow_that_score_eval/train-*
- split: validation
path: super_glue_cb_does_it_follow_that_score_eval/validation-*
- split: test
path: super_glue_cb_does_it_follow_that_score_eval/test-*
- config_name: super_glue_cb_does_this_imply
data_files:
- split: train
path: super_glue_cb_does_this_imply/train-*
- split: validation
path: super_glue_cb_does_this_imply/validation-*
- split: test
path: super_glue_cb_does_this_imply/test-*
- config_name: super_glue_cb_does_this_imply_score_eval
data_files:
- split: train
path: super_glue_cb_does_this_imply_score_eval/train-*
- split: validation
path: super_glue_cb_does_this_imply_score_eval/validation-*
- split: test
path: super_glue_cb_does_this_imply_score_eval/test-*
- config_name: super_glue_cb_guaranteed_possible_impossible
data_files:
- split: train
path: super_glue_cb_guaranteed_possible_impossible/train-*
- split: validation
path: super_glue_cb_guaranteed_possible_impossible/validation-*
- split: test
path: super_glue_cb_guaranteed_possible_impossible/test-*
- config_name: super_glue_cb_guaranteed_possible_impossible_score_eval
data_files:
- split: train
path: super_glue_cb_guaranteed_possible_impossible_score_eval/train-*
- split: validation
path: super_glue_cb_guaranteed_possible_impossible_score_eval/validation-*
- split: test
path: super_glue_cb_guaranteed_possible_impossible_score_eval/test-*
- config_name: super_glue_cb_guaranteed_true
data_files:
- split: train
path: super_glue_cb_guaranteed_true/train-*
- split: validation
path: super_glue_cb_guaranteed_true/validation-*
- split: test
path: super_glue_cb_guaranteed_true/test-*
- config_name: super_glue_cb_guaranteed_true_score_eval
data_files:
- split: train
path: super_glue_cb_guaranteed_true_score_eval/train-*
- split: validation
path: super_glue_cb_guaranteed_true_score_eval/validation-*
- split: test
path: super_glue_cb_guaranteed_true_score_eval/test-*
- config_name: super_glue_cb_justified_in_saying
data_files:
- split: train
path: super_glue_cb_justified_in_saying/train-*
- split: validation
path: super_glue_cb_justified_in_saying/validation-*
- split: test
path: super_glue_cb_justified_in_saying/test-*
- config_name: super_glue_cb_justified_in_saying_score_eval
data_files:
- split: train
path: super_glue_cb_justified_in_saying_score_eval/train-*
- split: validation
path: super_glue_cb_justified_in_saying_score_eval/validation-*
- split: test
path: super_glue_cb_justified_in_saying_score_eval/test-*
- config_name: super_glue_cb_must_be_true
data_files:
- split: train
path: super_glue_cb_must_be_true/train-*
- split: validation
path: super_glue_cb_must_be_true/validation-*
- split: test
path: super_glue_cb_must_be_true/test-*
- config_name: super_glue_cb_must_be_true_score_eval
data_files:
- split: train
path: super_glue_cb_must_be_true_score_eval/train-*
- split: validation
path: super_glue_cb_must_be_true_score_eval/validation-*
- split: test
path: super_glue_cb_must_be_true_score_eval/test-*
- config_name: super_glue_cb_should_assume
data_files:
- split: train
path: super_glue_cb_should_assume/train-*
- split: validation
path: super_glue_cb_should_assume/validation-*
- split: test
path: super_glue_cb_should_assume/test-*
- config_name: super_glue_cb_should_assume_score_eval
data_files:
- split: train
path: super_glue_cb_should_assume_score_eval/train-*
- split: validation
path: super_glue_cb_should_assume_score_eval/validation-*
- split: test
path: super_glue_cb_should_assume_score_eval/test-*
- config_name: super_glue_cb_take_the_following_as_truth
data_files:
- split: train
path: super_glue_cb_take_the_following_as_truth/train-*
- split: validation
path: super_glue_cb_take_the_following_as_truth/validation-*
- split: test
path: super_glue_cb_take_the_following_as_truth/test-*
- config_name: super_glue_cb_take_the_following_as_truth_score_eval
data_files:
- split: train
path: super_glue_cb_take_the_following_as_truth_score_eval/train-*
- split: validation
path: super_glue_cb_take_the_following_as_truth_score_eval/validation-*
- split: test
path: super_glue_cb_take_the_following_as_truth_score_eval/test-*
- config_name: super_glue_copa_C1_or_C2_premise_so_because_
data_files:
- split: train
path: super_glue_copa_C1_or_C2_premise_so_because_/train-*
- split: validation
path: super_glue_copa_C1_or_C2_premise_so_because_/validation-*
- split: test
path: super_glue_copa_C1_or_C2_premise_so_because_/test-*
- config_name: super_glue_copa_C1_or_C2_premise_so_because__score_eval
data_files:
- split: train
path: super_glue_copa_C1_or_C2_premise_so_because__score_eval/train-*
- split: validation
path: super_glue_copa_C1_or_C2_premise_so_because__score_eval/validation-*
- split: test
path: super_glue_copa_C1_or_C2_premise_so_because__score_eval/test-*
- config_name: super_glue_copa__As_a_result_C1_or_C2_
data_files:
- split: train
path: super_glue_copa__As_a_result_C1_or_C2_/train-*
- split: validation
path: super_glue_copa__As_a_result_C1_or_C2_/validation-*
- split: test
path: super_glue_copa__As_a_result_C1_or_C2_/test-*
- config_name: super_glue_copa__As_a_result_C1_or_C2__score_eval
data_files:
- split: train
path: super_glue_copa__As_a_result_C1_or_C2__score_eval/train-*
- split: validation
path: super_glue_copa__As_a_result_C1_or_C2__score_eval/validation-*
- split: test
path: super_glue_copa__As_a_result_C1_or_C2__score_eval/test-*
- config_name: super_glue_copa__What_could_happen_next_C1_or_C2_
data_files:
- split: train
path: super_glue_copa__What_could_happen_next_C1_or_C2_/train-*
- split: validation
path: super_glue_copa__What_could_happen_next_C1_or_C2_/validation-*
- split: test
path: super_glue_copa__What_could_happen_next_C1_or_C2_/test-*
- config_name: super_glue_copa__What_could_happen_next_C1_or_C2__score_eval
data_files:
- split: train
path: super_glue_copa__What_could_happen_next_C1_or_C2__score_eval/train-*
- split: validation
path: super_glue_copa__What_could_happen_next_C1_or_C2__score_eval/validation-*
- split: test
path: super_glue_copa__What_could_happen_next_C1_or_C2__score_eval/test-*
- config_name: super_glue_copa__which_may_be_caused_by
data_files:
- split: train
path: super_glue_copa__which_may_be_caused_by/train-*
- split: validation
path: super_glue_copa__which_may_be_caused_by/validation-*
- split: test
path: super_glue_copa__which_may_be_caused_by/test-*
- config_name: super_glue_copa__which_may_be_caused_by_score_eval
data_files:
- split: train
path: super_glue_copa__which_may_be_caused_by_score_eval/train-*
- split: validation
path: super_glue_copa__which_may_be_caused_by_score_eval/validation-*
- split: test
path: super_glue_copa__which_may_be_caused_by_score_eval/test-*
- config_name: super_glue_copa__why_C1_or_C2
data_files:
- split: train
path: super_glue_copa__why_C1_or_C2/train-*
- split: validation
path: super_glue_copa__why_C1_or_C2/validation-*
- split: test
path: super_glue_copa__why_C1_or_C2/test-*
- config_name: super_glue_copa__why_C1_or_C2_score_eval
data_files:
- split: train
path: super_glue_copa__why_C1_or_C2_score_eval/train-*
- split: validation
path: super_glue_copa__why_C1_or_C2_score_eval/validation-*
- split: test
path: super_glue_copa__why_C1_or_C2_score_eval/test-*
- config_name: super_glue_copa_best_option
data_files:
- split: train
path: super_glue_copa_best_option/train-*
- split: validation
path: super_glue_copa_best_option/validation-*
- split: test
path: super_glue_copa_best_option/test-*
- config_name: super_glue_copa_best_option_score_eval
data_files:
- split: train
path: super_glue_copa_best_option_score_eval/train-*
- split: validation
path: super_glue_copa_best_option_score_eval/validation-*
- split: test
path: super_glue_copa_best_option_score_eval/test-*
- config_name: super_glue_copa_cause_effect
data_files:
- split: train
path: super_glue_copa_cause_effect/train-*
- split: validation
path: super_glue_copa_cause_effect/validation-*
- split: test
path: super_glue_copa_cause_effect/test-*
- config_name: super_glue_copa_cause_effect_score_eval
data_files:
- split: train
path: super_glue_copa_cause_effect_score_eval/train-*
- split: validation
path: super_glue_copa_cause_effect_score_eval/validation-*
- split: test
path: super_glue_copa_cause_effect_score_eval/test-*
- config_name: super_glue_copa_choose
data_files:
- split: train
path: super_glue_copa_choose/train-*
- split: validation
path: super_glue_copa_choose/validation-*
- split: test
path: super_glue_copa_choose/test-*
- config_name: super_glue_copa_choose_score_eval
data_files:
- split: train
path: super_glue_copa_choose_score_eval/train-*
- split: validation
path: super_glue_copa_choose_score_eval/validation-*
- split: test
path: super_glue_copa_choose_score_eval/test-*
- config_name: super_glue_copa_exercise
data_files:
- split: train
path: super_glue_copa_exercise/train-*
- split: validation
path: super_glue_copa_exercise/validation-*
- split: test
path: super_glue_copa_exercise/test-*
- config_name: super_glue_copa_exercise_score_eval
data_files:
- split: train
path: super_glue_copa_exercise_score_eval/train-*
- split: validation
path: super_glue_copa_exercise_score_eval/validation-*
- split: test
path: super_glue_copa_exercise_score_eval/test-*
- config_name: super_glue_copa_i_am_hesitating
data_files:
- split: train
path: super_glue_copa_i_am_hesitating/train-*
- split: validation
path: super_glue_copa_i_am_hesitating/validation-*
- split: test
path: super_glue_copa_i_am_hesitating/test-*
- config_name: super_glue_copa_i_am_hesitating_score_eval
data_files:
- split: train
path: super_glue_copa_i_am_hesitating_score_eval/train-*
- split: validation
path: super_glue_copa_i_am_hesitating_score_eval/validation-*
- split: test
path: super_glue_copa_i_am_hesitating_score_eval/test-*
- config_name: super_glue_copa_more_likely
data_files:
- split: train
path: super_glue_copa_more_likely/train-*
- split: validation
path: super_glue_copa_more_likely/validation-*
- split: test
path: super_glue_copa_more_likely/test-*
- config_name: super_glue_copa_more_likely_score_eval
data_files:
- split: train
path: super_glue_copa_more_likely_score_eval/train-*
- split: validation
path: super_glue_copa_more_likely_score_eval/validation-*
- split: test
path: super_glue_copa_more_likely_score_eval/test-*
- config_name: super_glue_copa_plausible_alternatives
data_files:
- split: train
path: super_glue_copa_plausible_alternatives/train-*
- split: validation
path: super_glue_copa_plausible_alternatives/validation-*
- split: test
path: super_glue_copa_plausible_alternatives/test-*
- config_name: super_glue_copa_plausible_alternatives_score_eval
data_files:
- split: train
path: super_glue_copa_plausible_alternatives_score_eval/train-*
- split: validation
path: super_glue_copa_plausible_alternatives_score_eval/validation-*
- split: test
path: super_glue_copa_plausible_alternatives_score_eval/test-*
- config_name: super_glue_multirc_I_was_going_to_say_
data_files:
- split: train
path: super_glue_multirc_I_was_going_to_say_/train-*
- split: validation
path: super_glue_multirc_I_was_going_to_say_/validation-*
- split: test
path: super_glue_multirc_I_was_going_to_say_/test-*
- config_name: super_glue_multirc_Would_it_be_good_to_answer_
data_files:
- split: train
path: super_glue_multirc_Would_it_be_good_to_answer_/train-*
- split: validation
path: super_glue_multirc_Would_it_be_good_to_answer_/validation-*
- split: test
path: super_glue_multirc_Would_it_be_good_to_answer_/test-*
- config_name: super_glue_multirc_confirm
data_files:
- split: train
path: super_glue_multirc_confirm/train-*
- split: validation
path: super_glue_multirc_confirm/validation-*
- split: test
path: super_glue_multirc_confirm/test-*
- config_name: super_glue_multirc_correct
data_files:
- split: train
path: super_glue_multirc_correct/train-*
- split: validation
path: super_glue_multirc_correct/validation-*
- split: test
path: super_glue_multirc_correct/test-*
- config_name: super_glue_multirc_decide_valid
data_files:
- split: train
path: super_glue_multirc_decide_valid/train-*
- split: validation
path: super_glue_multirc_decide_valid/validation-*
- split: test
path: super_glue_multirc_decide_valid/test-*
- config_name: super_glue_multirc_found_this_answer
data_files:
- split: train
path: super_glue_multirc_found_this_answer/train-*
- split: validation
path: super_glue_multirc_found_this_answer/validation-*
- split: test
path: super_glue_multirc_found_this_answer/test-*
- config_name: super_glue_multirc_grading
data_files:
- split: train
path: super_glue_multirc_grading/train-*
- split: validation
path: super_glue_multirc_grading/validation-*
- split: test
path: super_glue_multirc_grading/test-*
- config_name: super_glue_multirc_is_a_correct_answer_
data_files:
- split: train
path: super_glue_multirc_is_a_correct_answer_/train-*
- split: validation
path: super_glue_multirc_is_a_correct_answer_/validation-*
- split: test
path: super_glue_multirc_is_a_correct_answer_/test-*
- config_name: super_glue_multirc_is_the_correct_answer_
data_files:
- split: train
path: super_glue_multirc_is_the_correct_answer_/train-*
- split: validation
path: super_glue_multirc_is_the_correct_answer_/validation-*
- split: test
path: super_glue_multirc_is_the_correct_answer_/test-*
- config_name: super_glue_multirc_paragraph_question_is_it_
data_files:
- split: train
path: super_glue_multirc_paragraph_question_is_it_/train-*
- split: validation
path: super_glue_multirc_paragraph_question_is_it_/validation-*
- split: test
path: super_glue_multirc_paragraph_question_is_it_/test-*
- config_name: super_glue_record_Add_sentence_after_after_continuation_choices_
data_files:
- split: train
path: super_glue_record_Add_sentence_after_after_continuation_choices_/train-*
- split: validation
path: super_glue_record_Add_sentence_after_after_continuation_choices_/validation-*
- split: test
path: super_glue_record_Add_sentence_after_after_continuation_choices_/test-*
- config_name: super_glue_record_Add_sentence_after_continuation_choices_
data_files:
- split: train
path: super_glue_record_Add_sentence_after_continuation_choices_/train-*
- split: validation
path: super_glue_record_Add_sentence_after_continuation_choices_/validation-*
- split: test
path: super_glue_record_Add_sentence_after_continuation_choices_/test-*
- config_name: super_glue_record_Can_you_figure_out_
data_files:
- split: train
path: super_glue_record_Can_you_figure_out_/train-*
- split: validation
path: super_glue_record_Can_you_figure_out_/validation-*
- split: test
path: super_glue_record_Can_you_figure_out_/test-*
- config_name: super_glue_record_GPT_3_style_continuation_choices_
data_files:
- split: train
path: super_glue_record_GPT_3_style_continuation_choices_/train-*
- split: validation
path: super_glue_record_GPT_3_style_continuation_choices_/validation-*
- split: test
path: super_glue_record_GPT_3_style_continuation_choices_/test-*
- config_name: super_glue_record_GPT_3_style_summary_only_continuation_choices_
data_files:
- split: train
path: super_glue_record_GPT_3_style_summary_only_continuation_choices_/train-*
- split: validation
path: super_glue_record_GPT_3_style_summary_only_continuation_choices_/validation-*
- split: test
path: super_glue_record_GPT_3_style_summary_only_continuation_choices_/test-*
- config_name: super_glue_record_GPT_3_style_with_labels_continuation_choices_
data_files:
- split: train
path: super_glue_record_GPT_3_style_with_labels_continuation_choices_/train-*
- split: validation
path: super_glue_record_GPT_3_style_with_labels_continuation_choices_/validation-*
- split: test
path: super_glue_record_GPT_3_style_with_labels_continuation_choices_/test-*
- config_name: super_glue_record_GPT_3_style_with_labels_without_hyphens_continuation_choices_
data_files:
- split: train
path: super_glue_record_GPT_3_style_with_labels_without_hyphens_continuation_choices_/train-*
- split: validation
path: super_glue_record_GPT_3_style_with_labels_without_hyphens_continuation_choices_/validation-*
- split: test
path: super_glue_record_GPT_3_style_with_labels_without_hyphens_continuation_choices_/test-*
- config_name: super_glue_record_GPT_3_style_without_hyphens_continuation_choices_
data_files:
- split: train
path: super_glue_record_GPT_3_style_without_hyphens_continuation_choices_/train-*
- split: validation
path: super_glue_record_GPT_3_style_without_hyphens_continuation_choices_/validation-*
- split: test
path: super_glue_record_GPT_3_style_without_hyphens_continuation_choices_/test-*
- config_name: super_glue_record_In_the_question_above_the_placeholder_stands_for
data_files:
- split: train
path: super_glue_record_In_the_question_above_the_placeholder_stands_for/train-*
- split: validation
path: super_glue_record_In_the_question_above_the_placeholder_stands_for/validation-*
- split: test
path: super_glue_record_In_the_question_above_the_placeholder_stands_for/test-*
- config_name: super_glue_record_New_highlight_continuation_choices_
data_files:
- split: train
path: super_glue_record_New_highlight_continuation_choices_/train-*
- split: validation
path: super_glue_record_New_highlight_continuation_choices_/validation-*
- split: test
path: super_glue_record_New_highlight_continuation_choices_/test-*
- config_name: super_glue_record_News_article_continuation_choices_
data_files:
- split: train
path: super_glue_record_News_article_continuation_choices_/train-*
- split: validation
path: super_glue_record_News_article_continuation_choices_/validation-*
- split: test
path: super_glue_record_News_article_continuation_choices_/test-*
- config_name: super_glue_record_Summary_first_continuation_choices_
data_files:
- split: train
path: super_glue_record_Summary_first_continuation_choices_/train-*
- split: validation
path: super_glue_record_Summary_first_continuation_choices_/validation-*
- split: test
path: super_glue_record_Summary_first_continuation_choices_/test-*
- config_name: super_glue_record_What_could_the_placeholder_be_
data_files:
- split: train
path: super_glue_record_What_could_the_placeholder_be_/train-*
- split: validation
path: super_glue_record_What_could_the_placeholder_be_/validation-*
- split: test
path: super_glue_record_What_could_the_placeholder_be_/test-*
- config_name: super_glue_record_Which_one_is_the_placeholder_
data_files:
- split: train
path: super_glue_record_Which_one_is_the_placeholder_/train-*
- split: validation
path: super_glue_record_Which_one_is_the_placeholder_/validation-*
- split: test
path: super_glue_record_Which_one_is_the_placeholder_/test-*
- config_name: super_glue_record_choose_between
data_files:
- split: train
path: super_glue_record_choose_between/train-*
- split: validation
path: super_glue_record_choose_between/validation-*
- split: test
path: super_glue_record_choose_between/test-*
- config_name: super_glue_record_corrupted
data_files:
- split: train
path: super_glue_record_corrupted/train-*
- split: validation
path: super_glue_record_corrupted/validation-*
- split: test
path: super_glue_record_corrupted/test-*
- config_name: super_glue_record_exercise
data_files:
- split: train
path: super_glue_record_exercise/train-*
- split: validation
path: super_glue_record_exercise/validation-*
- split: test
path: super_glue_record_exercise/test-*
- config_name: super_glue_record_pick_one_option
data_files:
- split: train
path: super_glue_record_pick_one_option/train-*
- split: validation
path: super_glue_record_pick_one_option/validation-*
- split: test
path: super_glue_record_pick_one_option/test-*
- config_name: super_glue_record_the_placeholder_refers_to_
data_files:
- split: train
path: super_glue_record_the_placeholder_refers_to_/train-*
- split: validation
path: super_glue_record_the_placeholder_refers_to_/validation-*
- split: test
path: super_glue_record_the_placeholder_refers_to_/test-*
- config_name: super_glue_record_trying_to_decide
data_files:
- split: train
path: super_glue_record_trying_to_decide/train-*
- split: validation
path: super_glue_record_trying_to_decide/validation-*
- split: test
path: super_glue_record_trying_to_decide/test-*
- config_name: super_glue_rte_GPT_3_style
data_files:
- split: train
path: super_glue_rte_GPT_3_style/train-*
- split: validation
path: super_glue_rte_GPT_3_style/validation-*
- split: test
path: super_glue_rte_GPT_3_style/test-*
- config_name: super_glue_rte_GPT_3_style_score_eval
data_files:
- split: train
path: super_glue_rte_GPT_3_style_score_eval/train-*
- split: validation
path: super_glue_rte_GPT_3_style_score_eval/validation-*
- split: test
path: super_glue_rte_GPT_3_style_score_eval/test-*
- config_name: super_glue_rte_MNLI_crowdsource
data_files:
- split: train
path: super_glue_rte_MNLI_crowdsource/train-*
- split: validation
path: super_glue_rte_MNLI_crowdsource/validation-*
- split: test
path: super_glue_rte_MNLI_crowdsource/test-*
- config_name: super_glue_rte_MNLI_crowdsource_score_eval
data_files:
- split: train
path: super_glue_rte_MNLI_crowdsource_score_eval/train-*
- split: validation
path: super_glue_rte_MNLI_crowdsource_score_eval/validation-*
- split: test
path: super_glue_rte_MNLI_crowdsource_score_eval/test-*
- config_name: super_glue_rte_based_on_the_previous_passage
data_files:
- split: train
path: super_glue_rte_based_on_the_previous_passage/train-*
- split: validation
path: super_glue_rte_based_on_the_previous_passage/validation-*
- split: test
path: super_glue_rte_based_on_the_previous_passage/test-*
- config_name: super_glue_rte_based_on_the_previous_passage_score_eval
data_files:
- split: train
path: super_glue_rte_based_on_the_previous_passage_score_eval/train-*
- split: validation
path: super_glue_rte_based_on_the_previous_passage_score_eval/validation-*
- split: test
path: super_glue_rte_based_on_the_previous_passage_score_eval/test-*
- config_name: super_glue_rte_can_we_infer
data_files:
- split: train
path: super_glue_rte_can_we_infer/train-*
- split: validation
path: super_glue_rte_can_we_infer/validation-*
- split: test
path: super_glue_rte_can_we_infer/test-*
- config_name: super_glue_rte_can_we_infer_score_eval
data_files:
- split: train
path: super_glue_rte_can_we_infer_score_eval/train-*
- split: validation
path: super_glue_rte_can_we_infer_score_eval/validation-*
- split: test
path: super_glue_rte_can_we_infer_score_eval/test-*
- config_name: super_glue_rte_does_it_follow_that
data_files:
- split: train
path: super_glue_rte_does_it_follow_that/train-*
- split: validation
path: super_glue_rte_does_it_follow_that/validation-*
- split: test
path: super_glue_rte_does_it_follow_that/test-*
- config_name: super_glue_rte_does_it_follow_that_score_eval
data_files:
- split: train
path: super_glue_rte_does_it_follow_that_score_eval/train-*
- split: validation
path: super_glue_rte_does_it_follow_that_score_eval/validation-*
- split: test
path: super_glue_rte_does_it_follow_that_score_eval/test-*
- config_name: super_glue_rte_does_this_imply
data_files:
- split: train
path: super_glue_rte_does_this_imply/train-*
- split: validation
path: super_glue_rte_does_this_imply/validation-*
- split: test
path: super_glue_rte_does_this_imply/test-*
- config_name: super_glue_rte_does_this_imply_score_eval
data_files:
- split: train
path: super_glue_rte_does_this_imply_score_eval/train-*
- split: validation
path: super_glue_rte_does_this_imply_score_eval/validation-*
- split: test
path: super_glue_rte_does_this_imply_score_eval/test-*
- config_name: super_glue_rte_guaranteed_true
data_files:
- split: train
path: super_glue_rte_guaranteed_true/train-*
- split: validation
path: super_glue_rte_guaranteed_true/validation-*
- split: test
path: super_glue_rte_guaranteed_true/test-*
- config_name: super_glue_rte_guaranteed_true_score_eval
data_files:
- split: train
path: super_glue_rte_guaranteed_true_score_eval/train-*
- split: validation
path: super_glue_rte_guaranteed_true_score_eval/validation-*
- split: test
path: super_glue_rte_guaranteed_true_score_eval/test-*
- config_name: super_glue_rte_justified_in_saying
data_files:
- split: train
path: super_glue_rte_justified_in_saying/train-*
- split: validation
path: super_glue_rte_justified_in_saying/validation-*
- split: test
path: super_glue_rte_justified_in_saying/test-*
- config_name: super_glue_rte_justified_in_saying_score_eval
data_files:
- split: train
path: super_glue_rte_justified_in_saying_score_eval/train-*
- split: validation
path: super_glue_rte_justified_in_saying_score_eval/validation-*
- split: test
path: super_glue_rte_justified_in_saying_score_eval/test-*
- config_name: super_glue_rte_must_be_true
data_files:
- split: train
path: super_glue_rte_must_be_true/train-*
- split: validation
path: super_glue_rte_must_be_true/validation-*
- split: test
path: super_glue_rte_must_be_true/test-*
- config_name: super_glue_rte_must_be_true_score_eval
data_files:
- split: train
path: super_glue_rte_must_be_true_score_eval/train-*
- split: validation
path: super_glue_rte_must_be_true_score_eval/validation-*
- split: test
path: super_glue_rte_must_be_true_score_eval/test-*
- config_name: super_glue_rte_should_assume
data_files:
- split: train
path: super_glue_rte_should_assume/train-*
- split: validation
path: super_glue_rte_should_assume/validation-*
- split: test
path: super_glue_rte_should_assume/test-*
- config_name: super_glue_rte_should_assume_score_eval
data_files:
- split: train
path: super_glue_rte_should_assume_score_eval/train-*
- split: validation
path: super_glue_rte_should_assume_score_eval/validation-*
- split: test
path: super_glue_rte_should_assume_score_eval/test-*
- config_name: super_glue_wic_GPT_3_prompt
data_files:
- split: train
path: super_glue_wic_GPT_3_prompt/train-*
- split: validation
path: super_glue_wic_GPT_3_prompt/validation-*
- split: test
path: super_glue_wic_GPT_3_prompt/test-*
- config_name: super_glue_wic_GPT_3_prompt_score_eval
data_files:
- split: train
path: super_glue_wic_GPT_3_prompt_score_eval/train-*
- split: validation
path: super_glue_wic_GPT_3_prompt_score_eval/validation-*
- split: test
path: super_glue_wic_GPT_3_prompt_score_eval/test-*
- config_name: super_glue_wic_GPT_3_prompt_with_label
data_files:
- split: train
path: super_glue_wic_GPT_3_prompt_with_label/train-*
- split: validation
path: super_glue_wic_GPT_3_prompt_with_label/validation-*
- split: test
path: super_glue_wic_GPT_3_prompt_with_label/test-*
- config_name: super_glue_wic_GPT_3_prompt_with_label_score_eval
data_files:
- split: train
path: super_glue_wic_GPT_3_prompt_with_label_score_eval/train-*
- split: validation
path: super_glue_wic_GPT_3_prompt_with_label_score_eval/validation-*
- split: test
path: super_glue_wic_GPT_3_prompt_with_label_score_eval/test-*
- config_name: super_glue_wic_affirmation_true_or_false
data_files:
- split: train
path: super_glue_wic_affirmation_true_or_false/train-*
- split: validation
path: super_glue_wic_affirmation_true_or_false/validation-*
- split: test
path: super_glue_wic_affirmation_true_or_false/test-*
- config_name: super_glue_wic_affirmation_true_or_false_score_eval
data_files:
- split: train
path: super_glue_wic_affirmation_true_or_false_score_eval/train-*
- split: validation
path: super_glue_wic_affirmation_true_or_false_score_eval/validation-*
- split: test
path: super_glue_wic_affirmation_true_or_false_score_eval/test-*
- config_name: super_glue_wic_grammar_homework
data_files:
- split: train
path: super_glue_wic_grammar_homework/train-*
- split: validation
path: super_glue_wic_grammar_homework/validation-*
- split: test
path: super_glue_wic_grammar_homework/test-*
- config_name: super_glue_wic_grammar_homework_score_eval
data_files:
- split: train
path: super_glue_wic_grammar_homework_score_eval/train-*
- split: validation
path: super_glue_wic_grammar_homework_score_eval/validation-*
- split: test
path: super_glue_wic_grammar_homework_score_eval/test-*
- config_name: super_glue_wic_polysemous
data_files:
- split: train
path: super_glue_wic_polysemous/train-*
- split: validation
path: super_glue_wic_polysemous/validation-*
- split: test
path: super_glue_wic_polysemous/test-*
- config_name: super_glue_wic_polysemous_score_eval
data_files:
- split: train
path: super_glue_wic_polysemous_score_eval/train-*
- split: validation
path: super_glue_wic_polysemous_score_eval/validation-*
- split: test
path: super_glue_wic_polysemous_score_eval/test-*
- config_name: super_glue_wic_question_context
data_files:
- split: train
path: super_glue_wic_question_context/train-*
- split: validation
path: super_glue_wic_question_context/validation-*
- split: test
path: super_glue_wic_question_context/test-*
- config_name: super_glue_wic_question_context_meaning
data_files:
- split: train
path: super_glue_wic_question_context_meaning/train-*
- split: validation
path: super_glue_wic_question_context_meaning/validation-*
- split: test
path: super_glue_wic_question_context_meaning/test-*
- config_name: super_glue_wic_question_context_meaning_score_eval
data_files:
- split: train
path: super_glue_wic_question_context_meaning_score_eval/train-*
- split: validation
path: super_glue_wic_question_context_meaning_score_eval/validation-*
- split: test
path: super_glue_wic_question_context_meaning_score_eval/test-*
- config_name: super_glue_wic_question_context_meaning_with_label
data_files:
- split: train
path: super_glue_wic_question_context_meaning_with_label/train-*
- split: validation
path: super_glue_wic_question_context_meaning_with_label/validation-*
- split: test
path: super_glue_wic_question_context_meaning_with_label/test-*
- config_name: super_glue_wic_question_context_meaning_with_label_score_eval
data_files:
- split: train
path: super_glue_wic_question_context_meaning_with_label_score_eval/train-*
- split: validation
path: super_glue_wic_question_context_meaning_with_label_score_eval/validation-*
- split: test
path: super_glue_wic_question_context_meaning_with_label_score_eval/test-*
- config_name: super_glue_wic_question_context_score_eval
data_files:
- split: train
path: super_glue_wic_question_context_score_eval/train-*
- split: validation
path: super_glue_wic_question_context_score_eval/validation-*
- split: test
path: super_glue_wic_question_context_score_eval/test-*
- config_name: super_glue_wic_same_sense
data_files:
- split: train
path: super_glue_wic_same_sense/train-*
- split: validation
path: super_glue_wic_same_sense/validation-*
- split: test
path: super_glue_wic_same_sense/test-*
- config_name: super_glue_wic_same_sense_score_eval
data_files:
- split: train
path: super_glue_wic_same_sense_score_eval/train-*
- split: validation
path: super_glue_wic_same_sense_score_eval/validation-*
- split: test
path: super_glue_wic_same_sense_score_eval/test-*
- config_name: super_glue_wic_similar_sense
data_files:
- split: train
path: super_glue_wic_similar_sense/train-*
- split: validation
path: super_glue_wic_similar_sense/validation-*
- split: test
path: super_glue_wic_similar_sense/test-*
- config_name: super_glue_wic_similar_sense_score_eval
data_files:
- split: train
path: super_glue_wic_similar_sense_score_eval/train-*
- split: validation
path: super_glue_wic_similar_sense_score_eval/validation-*
- split: test
path: super_glue_wic_similar_sense_score_eval/test-*
- config_name: super_glue_wsc.fixed_GPT_3_Style
data_files:
- split: train
path: super_glue_wsc.fixed_GPT_3_Style/train-*
- split: validation
path: super_glue_wsc.fixed_GPT_3_Style/validation-*
- split: test
path: super_glue_wsc.fixed_GPT_3_Style/test-*
- config_name: super_glue_wsc.fixed_GPT_3_Style_score_eval
data_files:
- split: train
path: super_glue_wsc.fixed_GPT_3_Style_score_eval/train-*
- split: validation
path: super_glue_wsc.fixed_GPT_3_Style_score_eval/validation-*
- split: test
path: super_glue_wsc.fixed_GPT_3_Style_score_eval/test-*
- config_name: super_glue_wsc.fixed_I_think_they_mean
data_files:
- split: train
path: super_glue_wsc.fixed_I_think_they_mean/train-*
- split: validation
path: super_glue_wsc.fixed_I_think_they_mean/validation-*
- split: test
path: super_glue_wsc.fixed_I_think_they_mean/test-*
- config_name: super_glue_wsc.fixed_I_think_they_mean_score_eval
data_files:
- split: train
path: super_glue_wsc.fixed_I_think_they_mean_score_eval/train-*
- split: validation
path: super_glue_wsc.fixed_I_think_they_mean_score_eval/validation-*
- split: test
path: super_glue_wsc.fixed_I_think_they_mean_score_eval/test-*
- config_name: super_glue_wsc.fixed_Who_or_what_is_are
data_files:
- split: train
path: super_glue_wsc.fixed_Who_or_what_is_are/train-*
- split: validation
path: super_glue_wsc.fixed_Who_or_what_is_are/validation-*
- split: test
path: super_glue_wsc.fixed_Who_or_what_is_are/test-*
- config_name: super_glue_wsc.fixed_Who_or_what_is_are_score_eval
data_files:
- split: train
path: super_glue_wsc.fixed_Who_or_what_is_are_score_eval/train-*
- split: validation
path: super_glue_wsc.fixed_Who_or_what_is_are_score_eval/validation-*
- split: test
path: super_glue_wsc.fixed_Who_or_what_is_are_score_eval/test-*
- config_name: super_glue_wsc.fixed_by_p_they_mean
data_files:
- split: train
path: super_glue_wsc.fixed_by_p_they_mean/train-*
- split: validation
path: super_glue_wsc.fixed_by_p_they_mean/validation-*
- split: test
path: super_glue_wsc.fixed_by_p_they_mean/test-*
- config_name: super_glue_wsc.fixed_by_p_they_mean_score_eval
data_files:
- split: train
path: super_glue_wsc.fixed_by_p_they_mean_score_eval/train-*
- split: validation
path: super_glue_wsc.fixed_by_p_they_mean_score_eval/validation-*
- split: test
path: super_glue_wsc.fixed_by_p_they_mean_score_eval/test-*
- config_name: super_glue_wsc.fixed_does_p_stand_for
data_files:
- split: train
path: super_glue_wsc.fixed_does_p_stand_for/train-*
- split: validation
path: super_glue_wsc.fixed_does_p_stand_for/validation-*
- split: test
path: super_glue_wsc.fixed_does_p_stand_for/test-*
- config_name: super_glue_wsc.fixed_does_p_stand_for_score_eval
data_files:
- split: train
path: super_glue_wsc.fixed_does_p_stand_for_score_eval/train-*
- split: validation
path: super_glue_wsc.fixed_does_p_stand_for_score_eval/validation-*
- split: test
path: super_glue_wsc.fixed_does_p_stand_for_score_eval/test-*
- config_name: super_glue_wsc.fixed_does_the_pronoun_refer_to
data_files:
- split: train
path: super_glue_wsc.fixed_does_the_pronoun_refer_to/train-*
- split: validation
path: super_glue_wsc.fixed_does_the_pronoun_refer_to/validation-*
- split: test
path: super_glue_wsc.fixed_does_the_pronoun_refer_to/test-*
- config_name: super_glue_wsc.fixed_does_the_pronoun_refer_to_score_eval
data_files:
- split: train
path: super_glue_wsc.fixed_does_the_pronoun_refer_to_score_eval/train-*
- split: validation
path: super_glue_wsc.fixed_does_the_pronoun_refer_to_score_eval/validation-*
- split: test
path: super_glue_wsc.fixed_does_the_pronoun_refer_to_score_eval/test-*
- config_name: super_glue_wsc.fixed_in_other_words
data_files:
- split: train
path: super_glue_wsc.fixed_in_other_words/train-*
- split: validation
path: super_glue_wsc.fixed_in_other_words/validation-*
- split: test
path: super_glue_wsc.fixed_in_other_words/test-*
- config_name: super_glue_wsc.fixed_in_other_words_score_eval
data_files:
- split: train
path: super_glue_wsc.fixed_in_other_words_score_eval/train-*
- split: validation
path: super_glue_wsc.fixed_in_other_words_score_eval/validation-*
- split: test
path: super_glue_wsc.fixed_in_other_words_score_eval/test-*
- config_name: super_glue_wsc.fixed_p_is_are_r
data_files:
- split: train
path: super_glue_wsc.fixed_p_is_are_r/train-*
- split: validation
path: super_glue_wsc.fixed_p_is_are_r/validation-*
- split: test
path: super_glue_wsc.fixed_p_is_are_r/test-*
- config_name: super_glue_wsc.fixed_p_is_are_r_score_eval
data_files:
- split: train
path: super_glue_wsc.fixed_p_is_are_r_score_eval/train-*
- split: validation
path: super_glue_wsc.fixed_p_is_are_r_score_eval/validation-*
- split: test
path: super_glue_wsc.fixed_p_is_are_r_score_eval/test-*
- config_name: super_glue_wsc.fixed_replaced_with
data_files:
- split: train
path: super_glue_wsc.fixed_replaced_with/train-*
- split: validation
path: super_glue_wsc.fixed_replaced_with/validation-*
- split: test
path: super_glue_wsc.fixed_replaced_with/test-*
- config_name: super_glue_wsc.fixed_replaced_with_score_eval
data_files:
- split: train
path: super_glue_wsc.fixed_replaced_with_score_eval/train-*
- split: validation
path: super_glue_wsc.fixed_replaced_with_score_eval/validation-*
- split: test
path: super_glue_wsc.fixed_replaced_with_score_eval/test-*
- config_name: super_glue_wsc.fixed_the_pronoun_refers_to
data_files:
- split: train
path: super_glue_wsc.fixed_the_pronoun_refers_to/train-*
- split: validation
path: super_glue_wsc.fixed_the_pronoun_refers_to/validation-*
- split: test
path: super_glue_wsc.fixed_the_pronoun_refers_to/test-*
- config_name: super_glue_wsc.fixed_the_pronoun_refers_to_score_eval
data_files:
- split: train
path: super_glue_wsc.fixed_the_pronoun_refers_to_score_eval/train-*
- split: validation
path: super_glue_wsc.fixed_the_pronoun_refers_to_score_eval/validation-*
- split: test
path: super_glue_wsc.fixed_the_pronoun_refers_to_score_eval/test-*
- config_name: trec_fine_grained_ABBR
data_files:
- split: train
path: trec_fine_grained_ABBR/train-*
- split: test
path: trec_fine_grained_ABBR/test-*
- config_name: trec_fine_grained_ABBR_context_first
data_files:
- split: train
path: trec_fine_grained_ABBR_context_first/train-*
- split: test
path: trec_fine_grained_ABBR_context_first/test-*
- config_name: trec_fine_grained_DESC
data_files:
- split: train
path: trec_fine_grained_DESC/train-*
- split: test
path: trec_fine_grained_DESC/test-*
- config_name: trec_fine_grained_DESC_context_first
data_files:
- split: train
path: trec_fine_grained_DESC_context_first/train-*
- split: test
path: trec_fine_grained_DESC_context_first/test-*
- config_name: trec_fine_grained_ENTY
data_files:
- split: train
path: trec_fine_grained_ENTY/train-*
- split: test
path: trec_fine_grained_ENTY/test-*
- config_name: trec_fine_grained_HUM
data_files:
- split: train
path: trec_fine_grained_HUM/train-*
- split: test
path: trec_fine_grained_HUM/test-*
- config_name: trec_fine_grained_HUM_context_first
data_files:
- split: train
path: trec_fine_grained_HUM_context_first/train-*
- split: test
path: trec_fine_grained_HUM_context_first/test-*
- config_name: trec_fine_grained_LOC
data_files:
- split: train
path: trec_fine_grained_LOC/train-*
- split: test
path: trec_fine_grained_LOC/test-*
- config_name: trec_fine_grained_LOC_context_first
data_files:
- split: train
path: trec_fine_grained_LOC_context_first/train-*
- split: test
path: trec_fine_grained_LOC_context_first/test-*
- config_name: trec_fine_grained_NUM
data_files:
- split: train
path: trec_fine_grained_NUM/train-*
- split: test
path: trec_fine_grained_NUM/test-*
- config_name: trec_fine_grained_NUM_context_first
data_files:
- split: train
path: trec_fine_grained_NUM_context_first/train-*
- split: test
path: trec_fine_grained_NUM_context_first/test-*
- config_name: trec_fine_grained_open
data_files:
- split: train
path: trec_fine_grained_open/train-*
- split: test
path: trec_fine_grained_open/test-*
- config_name: trec_fine_grained_open_context_first
data_files:
- split: train
path: trec_fine_grained_open_context_first/train-*
- split: test
path: trec_fine_grained_open_context_first/test-*
- config_name: trec_pick_the_best_descriptor
data_files:
- split: train
path: trec_pick_the_best_descriptor/train-*
- split: test
path: trec_pick_the_best_descriptor/test-*
- config_name: trec_trec1
data_files:
- split: train
path: trec_trec1/train-*
- split: test
path: trec_trec1/test-*
- config_name: trec_trec2
data_files:
- split: train
path: trec_trec2/train-*
- split: test
path: trec_trec2/test-*
- config_name: trec_what_category_best_describe
data_files:
- split: train
path: trec_what_category_best_describe/train-*
- split: test
path: trec_what_category_best_describe/test-*
- config_name: trec_which_category_best_describes
data_files:
- split: train
path: trec_which_category_best_describes/train-*
- split: test
path: trec_which_category_best_describes/test-*
- config_name: trivia_qa_unfiltered_first_person_context
data_files:
- split: train
path: trivia_qa_unfiltered_first_person_context/train-*
- split: validation
path: trivia_qa_unfiltered_first_person_context/validation-*
- split: test
path: trivia_qa_unfiltered_first_person_context/test-*
- config_name: trivia_qa_unfiltered_formal_description
data_files:
- split: train
path: trivia_qa_unfiltered_formal_description/train-*
- split: validation
path: trivia_qa_unfiltered_formal_description/validation-*
- split: test
path: trivia_qa_unfiltered_formal_description/test-*
- config_name: trivia_qa_unfiltered_guess_question
data_files:
- split: train
path: trivia_qa_unfiltered_guess_question/train-*
- split: validation
path: trivia_qa_unfiltered_guess_question/validation-*
- config_name: trivia_qa_unfiltered_question_answer
data_files:
- split: train
path: trivia_qa_unfiltered_question_answer/train-*
- split: validation
path: trivia_qa_unfiltered_question_answer/validation-*
- split: test
path: trivia_qa_unfiltered_question_answer/test-*
- config_name: trivia_qa_unfiltered_question_with_instruction
data_files:
- split: train
path: trivia_qa_unfiltered_question_with_instruction/train-*
- split: validation
path: trivia_qa_unfiltered_question_with_instruction/validation-*
- split: test
path: trivia_qa_unfiltered_question_with_instruction/test-*
- config_name: web_questions_get_the_answer
data_files:
- split: train
path: web_questions_get_the_answer/train-*
- split: test
path: web_questions_get_the_answer/test-*
- config_name: web_questions_potential_correct_answer
data_files:
- split: train
path: web_questions_potential_correct_answer/train-*
- split: test
path: web_questions_potential_correct_answer/test-*
- config_name: web_questions_question_answer
data_files:
- split: train
path: web_questions_question_answer/train-*
- split: test
path: web_questions_question_answer/test-*
- config_name: web_questions_short_general_knowledge_q
data_files:
- split: train
path: web_questions_short_general_knowledge_q/train-*
- split: test
path: web_questions_short_general_knowledge_q/test-*
- config_name: web_questions_whats_the_answer
data_files:
- split: train
path: web_questions_whats_the_answer/train-*
- split: test
path: web_questions_whats_the_answer/test-*
- config_name: wiki_bio_comprehension
data_files:
- split: train
path: wiki_bio_comprehension/train-*
- split: test
path: wiki_bio_comprehension/test-*
- split: val
path: wiki_bio_comprehension/val-*
- config_name: wiki_bio_guess_person
data_files:
- split: train
path: wiki_bio_guess_person/train-*
- split: test
path: wiki_bio_guess_person/test-*
- split: val
path: wiki_bio_guess_person/val-*
- config_name: wiki_bio_key_content
data_files:
- split: train
path: wiki_bio_key_content/train-*
- split: test
path: wiki_bio_key_content/test-*
- split: val
path: wiki_bio_key_content/val-*
- config_name: wiki_bio_what_content
data_files:
- split: train
path: wiki_bio_what_content/train-*
- split: test
path: wiki_bio_what_content/test-*
- split: val
path: wiki_bio_what_content/val-*
- config_name: wiki_bio_who
data_files:
- split: train
path: wiki_bio_who/train-*
- split: test
path: wiki_bio_who/test-*
- split: val
path: wiki_bio_who/val-*
- config_name: wiki_hop_original_choose_best_object_affirmative_1
data_files:
- split: train
path: wiki_hop_original_choose_best_object_affirmative_1/train-*
- split: validation
path: wiki_hop_original_choose_best_object_affirmative_1/validation-*
- config_name: wiki_hop_original_choose_best_object_affirmative_2
data_files:
- split: train
path: wiki_hop_original_choose_best_object_affirmative_2/train-*
- split: validation
path: wiki_hop_original_choose_best_object_affirmative_2/validation-*
- config_name: wiki_hop_original_choose_best_object_affirmative_3
data_files:
- split: train
path: wiki_hop_original_choose_best_object_affirmative_3/train-*
- split: validation
path: wiki_hop_original_choose_best_object_affirmative_3/validation-*
- config_name: wiki_hop_original_choose_best_object_interrogative_1
data_files:
- split: train
path: wiki_hop_original_choose_best_object_interrogative_1/train-*
- split: validation
path: wiki_hop_original_choose_best_object_interrogative_1/validation-*
- config_name: wiki_hop_original_choose_best_object_interrogative_2
data_files:
- split: train
path: wiki_hop_original_choose_best_object_interrogative_2/train-*
- split: validation
path: wiki_hop_original_choose_best_object_interrogative_2/validation-*
- config_name: wiki_hop_original_explain_relation
data_files:
- split: train
path: wiki_hop_original_explain_relation/train-*
- split: validation
path: wiki_hop_original_explain_relation/validation-*
- config_name: wiki_hop_original_generate_object
data_files:
- split: train
path: wiki_hop_original_generate_object/train-*
- split: validation
path: wiki_hop_original_generate_object/validation-*
- config_name: wiki_hop_original_generate_subject
data_files:
- split: train
path: wiki_hop_original_generate_subject/train-*
- split: validation
path: wiki_hop_original_generate_subject/validation-*
- config_name: wiki_hop_original_generate_subject_and_object
data_files:
- split: train
path: wiki_hop_original_generate_subject_and_object/train-*
- split: validation
path: wiki_hop_original_generate_subject_and_object/validation-*
- config_name: wiki_qa_Decide_good_answer
data_files:
- split: train
path: wiki_qa_Decide_good_answer/train-*
- split: validation
path: wiki_qa_Decide_good_answer/validation-*
- split: test
path: wiki_qa_Decide_good_answer/test-*
- config_name: wiki_qa_Direct_Answer_to_Question
data_files:
- split: train
path: wiki_qa_Direct_Answer_to_Question/train-*
- split: validation
path: wiki_qa_Direct_Answer_to_Question/validation-*
- split: test
path: wiki_qa_Direct_Answer_to_Question/test-*
- config_name: wiki_qa_Generate_Question_from_Topic
data_files:
- split: train
path: wiki_qa_Generate_Question_from_Topic/train-*
- split: validation
path: wiki_qa_Generate_Question_from_Topic/validation-*
- split: test
path: wiki_qa_Generate_Question_from_Topic/test-*
- config_name: wiki_qa_Is_This_True_
data_files:
- split: train
path: wiki_qa_Is_This_True_/train-*
- split: validation
path: wiki_qa_Is_This_True_/validation-*
- split: test
path: wiki_qa_Is_This_True_/test-*
- config_name: wiki_qa_Jeopardy_style
data_files:
- split: train
path: wiki_qa_Jeopardy_style/train-*
- split: validation
path: wiki_qa_Jeopardy_style/validation-*
- split: test
path: wiki_qa_Jeopardy_style/test-*
- config_name: wiki_qa_Topic_Prediction_Answer_Only
data_files:
- split: train
path: wiki_qa_Topic_Prediction_Answer_Only/train-*
- split: validation
path: wiki_qa_Topic_Prediction_Answer_Only/validation-*
- split: test
path: wiki_qa_Topic_Prediction_Answer_Only/test-*
- config_name: wiki_qa_Topic_Prediction_Question_Only
data_files:
- split: train
path: wiki_qa_Topic_Prediction_Question_Only/train-*
- split: validation
path: wiki_qa_Topic_Prediction_Question_Only/validation-*
- split: test
path: wiki_qa_Topic_Prediction_Question_Only/test-*
- config_name: wiki_qa_Topic_Prediction_Question_and_Answer_Pair
data_files:
- split: train
path: wiki_qa_Topic_Prediction_Question_and_Answer_Pair/train-*
- split: validation
path: wiki_qa_Topic_Prediction_Question_and_Answer_Pair/validation-*
- split: test
path: wiki_qa_Topic_Prediction_Question_and_Answer_Pair/test-*
- config_name: wiki_qa_automatic_system
data_files:
- split: train
path: wiki_qa_automatic_system/train-*
- split: validation
path: wiki_qa_automatic_system/validation-*
- split: test
path: wiki_qa_automatic_system/test-*
- config_name: wiki_qa_exercise
data_files:
- split: train
path: wiki_qa_exercise/train-*
- split: validation
path: wiki_qa_exercise/validation-*
- split: test
path: wiki_qa_exercise/test-*
- config_name: wiki_qa_found_on_google
data_files:
- split: train
path: wiki_qa_found_on_google/train-*
- split: validation
path: wiki_qa_found_on_google/validation-*
- split: test
path: wiki_qa_found_on_google/test-*
- config_name: winogrande_winogrande_debiased_Replace
data_files:
- split: train
path: winogrande_winogrande_debiased_Replace/train-*
- split: validation
path: winogrande_winogrande_debiased_Replace/validation-*
- split: test
path: winogrande_winogrande_debiased_Replace/test-*
- config_name: winogrande_winogrande_debiased_Replace_score_eval
data_files:
- split: train
path: winogrande_winogrande_debiased_Replace_score_eval/train-*
- split: validation
path: winogrande_winogrande_debiased_Replace_score_eval/validation-*
- split: test
path: winogrande_winogrande_debiased_Replace_score_eval/test-*
- config_name: winogrande_winogrande_debiased_does_underscore_refer_to
data_files:
- split: train
path: winogrande_winogrande_debiased_does_underscore_refer_to/train-*
- split: validation
path: winogrande_winogrande_debiased_does_underscore_refer_to/validation-*
- split: test
path: winogrande_winogrande_debiased_does_underscore_refer_to/test-*
- config_name: winogrande_winogrande_debiased_does_underscore_refer_to_score_eval
data_files:
- split: train
path: winogrande_winogrande_debiased_does_underscore_refer_to_score_eval/train-*
- split: validation
path: winogrande_winogrande_debiased_does_underscore_refer_to_score_eval/validation-*
- split: test
path: winogrande_winogrande_debiased_does_underscore_refer_to_score_eval/test-*
- config_name: winogrande_winogrande_debiased_fill_in_the_blank
data_files:
- split: train
path: winogrande_winogrande_debiased_fill_in_the_blank/train-*
- split: validation
path: winogrande_winogrande_debiased_fill_in_the_blank/validation-*
- split: test
path: winogrande_winogrande_debiased_fill_in_the_blank/test-*
- config_name: winogrande_winogrande_debiased_fill_in_the_blank_score_eval
data_files:
- split: train
path: winogrande_winogrande_debiased_fill_in_the_blank_score_eval/train-*
- split: validation
path: winogrande_winogrande_debiased_fill_in_the_blank_score_eval/validation-*
- split: test
path: winogrande_winogrande_debiased_fill_in_the_blank_score_eval/test-*
- config_name: winogrande_winogrande_debiased_stand_for
data_files:
- split: train
path: winogrande_winogrande_debiased_stand_for/train-*
- split: validation
path: winogrande_winogrande_debiased_stand_for/validation-*
- split: test
path: winogrande_winogrande_debiased_stand_for/test-*
- config_name: winogrande_winogrande_debiased_stand_for_score_eval
data_files:
- split: train
path: winogrande_winogrande_debiased_stand_for_score_eval/train-*
- split: validation
path: winogrande_winogrande_debiased_stand_for_score_eval/validation-*
- split: test
path: winogrande_winogrande_debiased_stand_for_score_eval/test-*
- config_name: winogrande_winogrande_debiased_underscore_refer_to
data_files:
- split: train
path: winogrande_winogrande_debiased_underscore_refer_to/train-*
- split: validation
path: winogrande_winogrande_debiased_underscore_refer_to/validation-*
- split: test
path: winogrande_winogrande_debiased_underscore_refer_to/test-*
- config_name: winogrande_winogrande_debiased_underscore_refer_to_score_eval
data_files:
- split: train
path: winogrande_winogrande_debiased_underscore_refer_to_score_eval/train-*
- split: validation
path: winogrande_winogrande_debiased_underscore_refer_to_score_eval/validation-*
- split: test
path: winogrande_winogrande_debiased_underscore_refer_to_score_eval/test-*
- config_name: winogrande_winogrande_xl_Replace
data_files:
- split: train
path: winogrande_winogrande_xl_Replace/train-*
- split: validation
path: winogrande_winogrande_xl_Replace/validation-*
- split: test
path: winogrande_winogrande_xl_Replace/test-*
- config_name: winogrande_winogrande_xl_Replace_score_eval
data_files:
- split: train
path: winogrande_winogrande_xl_Replace_score_eval/train-*
- split: validation
path: winogrande_winogrande_xl_Replace_score_eval/validation-*
- split: test
path: winogrande_winogrande_xl_Replace_score_eval/test-*
- config_name: winogrande_winogrande_xl_does_underscore_refer_to
data_files:
- split: train
path: winogrande_winogrande_xl_does_underscore_refer_to/train-*
- split: validation
path: winogrande_winogrande_xl_does_underscore_refer_to/validation-*
- split: test
path: winogrande_winogrande_xl_does_underscore_refer_to/test-*
- config_name: winogrande_winogrande_xl_does_underscore_refer_to_score_eval
data_files:
- split: train
path: winogrande_winogrande_xl_does_underscore_refer_to_score_eval/train-*
- split: validation
path: winogrande_winogrande_xl_does_underscore_refer_to_score_eval/validation-*
- split: test
path: winogrande_winogrande_xl_does_underscore_refer_to_score_eval/test-*
- config_name: winogrande_winogrande_xl_fill_in_the_blank
data_files:
- split: train
path: winogrande_winogrande_xl_fill_in_the_blank/train-*
- split: validation
path: winogrande_winogrande_xl_fill_in_the_blank/validation-*
- split: test
path: winogrande_winogrande_xl_fill_in_the_blank/test-*
- config_name: winogrande_winogrande_xl_fill_in_the_blank_score_eval
data_files:
- split: train
path: winogrande_winogrande_xl_fill_in_the_blank_score_eval/train-*
- split: validation
path: winogrande_winogrande_xl_fill_in_the_blank_score_eval/validation-*
- split: test
path: winogrande_winogrande_xl_fill_in_the_blank_score_eval/test-*
- config_name: winogrande_winogrande_xl_stand_for
data_files:
- split: train
path: winogrande_winogrande_xl_stand_for/train-*
- split: validation
path: winogrande_winogrande_xl_stand_for/validation-*
- split: test
path: winogrande_winogrande_xl_stand_for/test-*
- config_name: winogrande_winogrande_xl_stand_for_score_eval
data_files:
- split: train
path: winogrande_winogrande_xl_stand_for_score_eval/train-*
- split: validation
path: winogrande_winogrande_xl_stand_for_score_eval/validation-*
- split: test
path: winogrande_winogrande_xl_stand_for_score_eval/test-*
- config_name: winogrande_winogrande_xl_underscore_refer_to
data_files:
- split: train
path: winogrande_winogrande_xl_underscore_refer_to/train-*
- split: validation
path: winogrande_winogrande_xl_underscore_refer_to/validation-*
- split: test
path: winogrande_winogrande_xl_underscore_refer_to/test-*
- config_name: winogrande_winogrande_xl_underscore_refer_to_score_eval
data_files:
- split: train
path: winogrande_winogrande_xl_underscore_refer_to_score_eval/train-*
- split: validation
path: winogrande_winogrande_xl_underscore_refer_to_score_eval/validation-*
- split: test
path: winogrande_winogrande_xl_underscore_refer_to_score_eval/test-*
- config_name: wiqa_does_the_supposed_perturbation_have_an_effect
data_files:
- split: train
path: wiqa_does_the_supposed_perturbation_have_an_effect/train-*
- split: validation
path: wiqa_does_the_supposed_perturbation_have_an_effect/validation-*
- split: test
path: wiqa_does_the_supposed_perturbation_have_an_effect/test-*
- config_name: wiqa_effect_with_label_answer
data_files:
- split: train
path: wiqa_effect_with_label_answer/train-*
- split: validation
path: wiqa_effect_with_label_answer/validation-*
- split: test
path: wiqa_effect_with_label_answer/test-*
- config_name: wiqa_effect_with_string_answer
data_files:
- split: train
path: wiqa_effect_with_string_answer/train-*
- split: validation
path: wiqa_effect_with_string_answer/validation-*
- split: test
path: wiqa_effect_with_string_answer/test-*
- config_name: wiqa_what_is_the_final_step_of_the_following_process
data_files:
- split: train
path: wiqa_what_is_the_final_step_of_the_following_process/train-*
- split: validation
path: wiqa_what_is_the_final_step_of_the_following_process/validation-*
- split: test
path: wiqa_what_is_the_final_step_of_the_following_process/test-*
- config_name: wiqa_what_is_the_missing_first_step
data_files:
- split: train
path: wiqa_what_is_the_missing_first_step/train-*
- split: validation
path: wiqa_what_is_the_missing_first_step/validation-*
- split: test
path: wiqa_what_is_the_missing_first_step/test-*
- config_name: wiqa_what_might_be_the_first_step_of_the_process
data_files:
- split: train
path: wiqa_what_might_be_the_first_step_of_the_process/train-*
- split: validation
path: wiqa_what_might_be_the_first_step_of_the_process/validation-*
- split: test
path: wiqa_what_might_be_the_first_step_of_the_process/test-*
- config_name: wiqa_what_might_be_the_last_step_of_the_process
data_files:
- split: train
path: wiqa_what_might_be_the_last_step_of_the_process/train-*
- split: validation
path: wiqa_what_might_be_the_last_step_of_the_process/validation-*
- split: test
path: wiqa_what_might_be_the_last_step_of_the_process/test-*
- config_name: wiqa_which_of_the_following_is_the_supposed_perturbation
data_files:
- split: train
path: wiqa_which_of_the_following_is_the_supposed_perturbation/train-*
- split: validation
path: wiqa_which_of_the_following_is_the_supposed_perturbation/validation-*
- split: test
path: wiqa_which_of_the_following_is_the_supposed_perturbation/test-*
- config_name: xsum_DOC_boils_down_to_simple_idea_that
data_files:
- split: train
path: xsum_DOC_boils_down_to_simple_idea_that/train-*
- split: validation
path: xsum_DOC_boils_down_to_simple_idea_that/validation-*
- split: test
path: xsum_DOC_boils_down_to_simple_idea_that/test-*
- config_name: xsum_DOC_given_above_write_one_sentence
data_files:
- split: train
path: xsum_DOC_given_above_write_one_sentence/train-*
- split: validation
path: xsum_DOC_given_above_write_one_sentence/validation-*
- split: test
path: xsum_DOC_given_above_write_one_sentence/test-*
- config_name: xsum_DOC_how_would_you_rephrase_few_words
data_files:
- split: train
path: xsum_DOC_how_would_you_rephrase_few_words/train-*
- split: validation
path: xsum_DOC_how_would_you_rephrase_few_words/validation-*
- split: test
path: xsum_DOC_how_would_you_rephrase_few_words/test-*
- config_name: xsum_DOC_tldr
data_files:
- split: train
path: xsum_DOC_tldr/train-*
- split: validation
path: xsum_DOC_tldr/validation-*
- split: test
path: xsum_DOC_tldr/test-*
- config_name: xsum_DOC_write_summary_of_above
data_files:
- split: train
path: xsum_DOC_write_summary_of_above/train-*
- split: validation
path: xsum_DOC_write_summary_of_above/validation-*
- split: test
path: xsum_DOC_write_summary_of_above/test-*
- config_name: xsum_article_DOC_summary
data_files:
- split: train
path: xsum_article_DOC_summary/train-*
- split: validation
path: xsum_article_DOC_summary/validation-*
- split: test
path: xsum_article_DOC_summary/test-*
- config_name: xsum_college_roommate_asked_DOC_so_I_recap
data_files:
- split: train
path: xsum_college_roommate_asked_DOC_so_I_recap/train-*
- split: validation
path: xsum_college_roommate_asked_DOC_so_I_recap/validation-*
- split: test
path: xsum_college_roommate_asked_DOC_so_I_recap/test-*
- config_name: xsum_read_below_DOC_write_abstract
data_files:
- split: train
path: xsum_read_below_DOC_write_abstract/train-*
- split: validation
path: xsum_read_below_DOC_write_abstract/validation-*
- split: test
path: xsum_read_below_DOC_write_abstract/test-*
- config_name: xsum_summarize_DOC
data_files:
- split: train
path: xsum_summarize_DOC/train-*
- split: validation
path: xsum_summarize_DOC/validation-*
- split: test
path: xsum_summarize_DOC/test-*
- config_name: xsum_summarize_this_DOC_summary
data_files:
- split: train
path: xsum_summarize_this_DOC_summary/train-*
- split: validation
path: xsum_summarize_this_DOC_summary/validation-*
- split: test
path: xsum_summarize_this_DOC_summary/test-*
- config_name: yelp_review_full_based_on_that
data_files:
- split: train
path: yelp_review_full_based_on_that/train-*
- split: test
path: yelp_review_full_based_on_that/test-*
- config_name: yelp_review_full_format_rating
data_files:
- split: train
path: yelp_review_full_format_rating/train-*
- split: test
path: yelp_review_full_format_rating/test-*
- config_name: yelp_review_full_format_score
data_files:
- split: train
path: yelp_review_full_format_score/train-*
- split: test
path: yelp_review_full_format_score/test-*
- config_name: yelp_review_full_format_star
data_files:
- split: train
path: yelp_review_full_format_star/train-*
- split: test
path: yelp_review_full_format_star/test-*
- config_name: yelp_review_full_on_a_scale
data_files:
- split: train
path: yelp_review_full_on_a_scale/train-*
- split: test
path: yelp_review_full_on_a_scale/test-*
- config_name: yelp_review_full_so_i_would
data_files:
- split: train
path: yelp_review_full_so_i_would/train-*
- split: test
path: yelp_review_full_so_i_would/test-*
- config_name: yelp_review_full_this_place
data_files:
- split: train
path: yelp_review_full_this_place/train-*
- split: test
path: yelp_review_full_this_place/test-*
---
# Dataset Card for P3
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Additional Information](#additional-information)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** https://bigscience.huggingface.co/promptsource
- **Repository:** https://github.com/bigscience-workshop/promptsource/
- **Paper:** [Multitask Prompted Training Enables Zero-Shot Task Generalization](https://arxiv.org/abs/2110.08207)
- **Point of Contact:** [Victor Sanh](mailto:victor@huggingface.co)
### Dataset Summary
P3 (Public Pool of Prompts) is a collection of prompted English datasets covering a diverse set of NLP tasks. A prompt is the combination of an input template and a target template. The templates are functions mapping a data example into natural language for the input and target sequences. For example, in the case of an NLI dataset, the data example would include fields for *Premise, Hypothesis, Label*. An input template would be *If {Premise} is true, is it also true that {Hypothesis}?*, whereas a target template can be defined with the label choices *Choices[label]*. Here *Choices* is prompt-specific metadata that consists of the options *yes, maybe, no* corresponding to *label* being entailment (0), neutral (1) or contradiction (2).
Prompts are collected using [Promptsource](https://github.com/bigscience-workshop/promptsource), an interface to interactively write prompts on datasets, and collect prompt-specific metadata such as evaluation metrics. As of October 13th, there are 2'000 prompts collected for 270+ data(sub)sets. The collection of prompts of P3 is publicly available on [Promptsource](https://github.com/bigscience-workshop/promptsource).
To train [T0*](https://huggingface.co/bigscience/T0pp), we used a subset of the prompts available in Promptsource (see details [here](https://huggingface.co/bigscience/T0pp#training-data)). However, some of the prompts use `random.choice`, a method that selects uniformly at random an option in a list of valid possibilities. For reproducibility purposes, we release the collection of prompted examples used to train T0*. **The data available here are the materialized version of the prompted datasets used in [Multitask Prompted Training Enables Zero-Shot Task Generalization](https://arxiv.org/abs/2110.08207) which represent only a subset of the datasets for which there is at least one prompt in Promptsource.**
### Supported Tasks and Leaderboards
The tasks represented in P3 cover a diverse set of NLP tasks including multiple-choice QA, sentiment analysis or natural language inference. We detail the full list of datasets in [Source Data](#source-data).
### Languages
The data in P3 are in English (BCP-47 `en`).
## Dataset Structure
### Data Instances
An example of "train" looks as follows:
```bash
{
'answer_choices': ['safe', 'trolley'],
'inputs': [86, 8, 7142, 666, 6, 405, 8, 3, 834, 1518, 21, 1346, 42, 31682, 58, 37, 3, 929, 9, 3042, 63, 2765, 808, 8, 2045, 6448, 326, 13, 8, 31682, 11, 3, 24052, 135, 16, 8, 1346, 552, 8, 3, 834, 47, 6364, 5], 'inputs_pretokenized': 'In the sentence below, does the _ stand for safe or trolley?\nThe treasury workers took the gold bars off of the trolley and stacked them in the safe until the _ was empty.',
'targets': [31682, 1],
'targets_pretokenized': '\ntrolley'
}
```
In the case of rank classification (letting the model select its the prediction the option with the highest log-likelihood), an example looks as follows:
```bash
{
'idx': [5, 0],
'inputs': [86, 8, 7142, 666, 6, 405, 8, 3, 834, 1518, 21, 19454, 42, 22227, 58, 19454, 744, 31, 17, 2112, 4553, 17742, 7, 12, 1953, 6, 298, 22227, 966, 373, 405, 5, 3, 834, 19, 72, 952, 12, 619, 16, 3, 9, 17742, 3298, 5],
'inputs_pretokenized': "In the sentence below, does the _ stand for Kyle or Logan?\nKyle doesn't wear leg warmers to bed, while Logan almost always does. _ is more likely to live in a warmer climate.",
'is_correct': True,
'targets': [19454, 1],
'targets_pretokenized': 'Kyle',
'weight': 1.0
}
```
To check all the prompted examples, you can use the [Promptsource hosted tool](http://bigscience.huggingface.co/promptsource) and choose the `Prompted dataset viewer` mode in the left panel.
### Data Fields
The data fields are the same among all splits:
- `answer_choices`: the choices (in natural language) available to the model
- `inputs_pretokenized`: the natural language input fed to the model
- `targets_pretokenized`: the natural language target that the model has to generate
- `inputs`: the tokenized input with [T5](https://huggingface.co/google/t5-v1_1-base)'s tokenizer
- `targets`: the tokenized target with [T5](https://huggingface.co/google/t5-v1_1-base)'s tokenizer
- `idx`: identifier of the (example, answer_option_id) in the case of rank classification
- `weight`: a weight for the example produced by seqio (always set to 1.0 in practise)
- `is_correct`: whether the (example, answer_option_id) is the correct one
### Data Splits
The list of data splits and their respective sizes is very long. You'll find the whole list in this [file](https://huggingface.co/datasets/bigscience/P3/blob/main/tasks_splits_and_features.py).
## Dataset Creation
### Curation Rationale
The Public Pool of Prompts relies on the Hugging Face Dataset library. Any public dataset in the Datasets library can be prompted. We select the datasets that have at least one subset in English and excluded datasets containing (predominantly) non-natural language examples.
We conservatively decided not to prompt datasets that contain potentially harmful content (for instance, datasets built on social media content). However, we sometimes prompt datasets that are purposefully built to measure bias and fairness of trained models, and reserve these prompted datasets (the validation or test sets) for evaluation purposes.
### Source Data
Here's the full list of the datasets present in the materialized version of P3:
- Multiple-Choice QA
- CommonsenseQA
- DREAM
- QUAIL
- QuaRTz
- Social IQA
- WiQA
- Cosmos
- QASC
- Quarel
- SciQ
- Wiki Hop
- ARC
- OpenBookQA
- MultiRC
- PIQA
- RACE
- HellaSwag
- BoolQ
- Extractive QA
- Adversarial QA
- Quoref
- DuoRC
- ROPES
- SQuAD v2
- ReCoRD
- Close-book QA
- Hotpot QA
- Wiki QA
- Trivia QA
- Web Questions
- Structure-to-text
- Common Gen
- Wiki Bio
- Sentiment
- Amazon
- App Reviews
- IMDB
- Rotten Tomatoes
- Yelp
- Summarization
- CNN Daily Mail
- Gigaword
- MultiNews
- SamSum
- XSum
- Topic Classification
- AG News
- DBPedia
- TREC
- Paraphrase Identification
- MRPC
- PAWS
- QQP
- Natural Language Inference
- ANLI
- CB
- RTE
- Coreference Resolution
- WSC
- Winogrande
- Word Sense disambiguation
- WiC
- Sentence Completion
- COPA
- HellaSwag
- Story Cloze
### Annotations
The prompts available in Promptsource are collected as part of BigScience, one-year long research workshop on large multilingual models and datasets. 36 contributors affiliated with 24 institutions in 8 countries participated to the prompt collection. Contributors are in majority machine learning researchers or machine learning engineers.
The main annotation guideline was that prompts needed to be grammatical and understandable by a native English speaker with no prior experience of the tasks. Additionally, prompts that required explicit counting or numerical indexing were removed in favor of natural language variants, e.g., instead of predicting indices of a span to extract (e.g. in extractive question answering), the model was expected to copy the span's text instead. With these minimal constraints, prompt writers were encouraged to use both formal and creative prompts and various orderings of the data. Most of the prompts correspond directly to a version of the original proposed task, although we also allowed prompts that permuted the original task (for instance, generating a document from its summary) or allowed for ambiguous output (for instance, not indicating a list of available choices).
The full annotation given to the contributors can be found [here](https://github.com/bigscience-workshop/promptsource/blob/main/CONTRIBUTING.md). *Note to self: the link is currently being updated with the)
## Additional Information
### Licensing Information
The dataset is released under Apache 2.0.
### Citation Information
```bibtex
@misc{sanh2021multitask,
title={Multitask Prompted Training Enables Zero-Shot Task Generalization},
author={Victor Sanh and Albert Webson and Colin Raffel and Stephen H. Bach and Lintang Sutawika and Zaid Alyafeai and Antoine Chaffin and Arnaud Stiegler and Teven Le Scao and Arun Raja and Manan Dey and M Saiful Bari and Canwen Xu and Urmish Thakker and Shanya Sharma Sharma and Eliza Szczechla and Taewoon Kim and Gunjan Chhablani and Nihal Nayak and Debajyoti Datta and Jonathan Chang and Mike Tian-Jian Jiang and Han Wang and Matteo Manica and Sheng Shen and Zheng Xin Yong and Harshit Pandey and Rachel Bawden and Thomas Wang and Trishala Neeraj and Jos Rozen and Abheesht Sharma and Andrea Santilli and Thibault Fevry and Jason Alan Fries and Ryan Teehan and Stella Biderman and Leo Gao and Tali Bers and Thomas Wolf and Alexander M. Rush},
year={2021},
eprint={2110.08207},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
```
### Contributions
Thanks to the contributors of [promptsource](https://github.com/bigscience-workshop/promptsource/graphs/contributors) for adding this dataset.
|
open-llm-leaderboard/details_aqweteddy__llama_chat-tv_en_luban-tv_stable_platypus2 | ---
pretty_name: Evaluation run of aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2](https://huggingface.co/aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 61 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the agregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_aqweteddy__llama_chat-tv_en_luban-tv_stable_platypus2\"\
,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\
\nThese are the [latest results from run 2023-09-14T19:14:45.418998](https://huggingface.co/datasets/open-llm-leaderboard/details_aqweteddy__llama_chat-tv_en_luban-tv_stable_platypus2/blob/main/results_2023-09-14T19-14-45.418998.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\": 0.4945007463965186,\n\
\ \"acc_stderr\": 0.03527731102256181,\n \"acc_norm\": 0.49711825981073476,\n\
\ \"acc_norm_stderr\": 0.035276035393914426,\n \"mc1\": 0.32558139534883723,\n\
\ \"mc1_stderr\": 0.016403989469907825,\n \"mc2\": 0.5188093512935639,\n\
\ \"mc2_stderr\": 0.016351300657386426\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.4351535836177474,\n \"acc_stderr\": 0.014487986197186043,\n\
\ \"acc_norm\": 0.4453924914675768,\n \"acc_norm_stderr\": 0.01452398763834409\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.4660426209918343,\n\
\ \"acc_stderr\": 0.004978260641742204,\n \"acc_norm\": 0.6102370045807608,\n\
\ \"acc_norm_stderr\": 0.004866997110388195\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\": 0.4740740740740741,\n\
\ \"acc_stderr\": 0.04313531696750574,\n \"acc_norm\": 0.4740740740740741,\n\
\ \"acc_norm_stderr\": 0.04313531696750574\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.47368421052631576,\n \"acc_stderr\": 0.04063302731486671,\n\
\ \"acc_norm\": 0.47368421052631576,\n \"acc_norm_stderr\": 0.04063302731486671\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\": 0.5320754716981132,\n \"acc_stderr\": 0.030709486992556538,\n\
\ \"acc_norm\": 0.5320754716981132,\n \"acc_norm_stderr\": 0.030709486992556538\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5277777777777778,\n\
\ \"acc_stderr\": 0.04174752578923185,\n \"acc_norm\": 0.5277777777777778,\n\
\ \"acc_norm_stderr\": 0.04174752578923185\n },\n \"harness|hendrycksTest-college_chemistry|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_computer_science|5\": {\n \"\
acc\": 0.43,\n \"acc_stderr\": 0.049756985195624284,\n \"acc_norm\"\
: 0.43,\n \"acc_norm_stderr\": 0.049756985195624284\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \
\ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.4797687861271676,\n\
\ \"acc_stderr\": 0.03809342081273957,\n \"acc_norm\": 0.4797687861271676,\n\
\ \"acc_norm_stderr\": 0.03809342081273957\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.2647058823529412,\n \"acc_stderr\": 0.04389869956808778,\n\
\ \"acc_norm\": 0.2647058823529412,\n \"acc_norm_stderr\": 0.04389869956808778\n\
\ },\n \"harness|hendrycksTest-computer_security|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-conceptual_physics|5\"\
: {\n \"acc\": 0.425531914893617,\n \"acc_stderr\": 0.032321469162244695,\n\
\ \"acc_norm\": 0.425531914893617,\n \"acc_norm_stderr\": 0.032321469162244695\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.3333333333333333,\n\
\ \"acc_stderr\": 0.044346007015849245,\n \"acc_norm\": 0.3333333333333333,\n\
\ \"acc_norm_stderr\": 0.044346007015849245\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.4206896551724138,\n \"acc_stderr\": 0.0411391498118926,\n\
\ \"acc_norm\": 0.4206896551724138,\n \"acc_norm_stderr\": 0.0411391498118926\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.2857142857142857,\n \"acc_stderr\": 0.02326651221373057,\n \"\
acc_norm\": 0.2857142857142857,\n \"acc_norm_stderr\": 0.02326651221373057\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\": 0.36,\n \"acc_stderr\": 0.04824181513244218,\n \
\ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.04824181513244218\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.535483870967742,\n\
\ \"acc_stderr\": 0.028372287797962935,\n \"acc_norm\": 0.535483870967742,\n\
\ \"acc_norm_stderr\": 0.028372287797962935\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.3842364532019704,\n \"acc_stderr\": 0.03422398565657551,\n\
\ \"acc_norm\": 0.3842364532019704,\n \"acc_norm_stderr\": 0.03422398565657551\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.56,\n \"acc_stderr\": 0.049888765156985884,\n \"acc_norm\"\
: 0.56,\n \"acc_norm_stderr\": 0.049888765156985884\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.6363636363636364,\n \"acc_stderr\": 0.03756335775187896,\n\
\ \"acc_norm\": 0.6363636363636364,\n \"acc_norm_stderr\": 0.03756335775187896\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.6515151515151515,\n \"acc_stderr\": 0.033948539651564025,\n \"\
acc_norm\": 0.6515151515151515,\n \"acc_norm_stderr\": 0.033948539651564025\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.7461139896373057,\n \"acc_stderr\": 0.0314102478056532,\n\
\ \"acc_norm\": 0.7461139896373057,\n \"acc_norm_stderr\": 0.0314102478056532\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.5153846153846153,\n \"acc_stderr\": 0.025339003010106515,\n\
\ \"acc_norm\": 0.5153846153846153,\n \"acc_norm_stderr\": 0.025339003010106515\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.2851851851851852,\n \"acc_stderr\": 0.02752859921034049,\n \
\ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.02752859921034049\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.47058823529411764,\n \"acc_stderr\": 0.03242225027115006,\n\
\ \"acc_norm\": 0.47058823529411764,\n \"acc_norm_stderr\": 0.03242225027115006\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.32450331125827814,\n \"acc_stderr\": 0.038227469376587525,\n \"\
acc_norm\": 0.32450331125827814,\n \"acc_norm_stderr\": 0.038227469376587525\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.6495412844036698,\n \"acc_stderr\": 0.020456077599824467,\n \"\
acc_norm\": 0.6495412844036698,\n \"acc_norm_stderr\": 0.020456077599824467\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.28703703703703703,\n \"acc_stderr\": 0.030851992993257013,\n \"\
acc_norm\": 0.28703703703703703,\n \"acc_norm_stderr\": 0.030851992993257013\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.5784313725490197,\n \"acc_stderr\": 0.03465868196380762,\n \"\
acc_norm\": 0.5784313725490197,\n \"acc_norm_stderr\": 0.03465868196380762\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.6582278481012658,\n \"acc_stderr\": 0.030874537537553617,\n \
\ \"acc_norm\": 0.6582278481012658,\n \"acc_norm_stderr\": 0.030874537537553617\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.5739910313901345,\n\
\ \"acc_stderr\": 0.033188332862172806,\n \"acc_norm\": 0.5739910313901345,\n\
\ \"acc_norm_stderr\": 0.033188332862172806\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.5572519083969466,\n \"acc_stderr\": 0.0435644720266507,\n\
\ \"acc_norm\": 0.5572519083969466,\n \"acc_norm_stderr\": 0.0435644720266507\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.6033057851239669,\n \"acc_stderr\": 0.04465869780531009,\n \"\
acc_norm\": 0.6033057851239669,\n \"acc_norm_stderr\": 0.04465869780531009\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.5648148148148148,\n\
\ \"acc_stderr\": 0.04792898170907061,\n \"acc_norm\": 0.5648148148148148,\n\
\ \"acc_norm_stderr\": 0.04792898170907061\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.5705521472392638,\n \"acc_stderr\": 0.03889066619112723,\n\
\ \"acc_norm\": 0.5705521472392638,\n \"acc_norm_stderr\": 0.03889066619112723\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.45535714285714285,\n\
\ \"acc_stderr\": 0.047268355537191,\n \"acc_norm\": 0.45535714285714285,\n\
\ \"acc_norm_stderr\": 0.047268355537191\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.6699029126213593,\n \"acc_stderr\": 0.0465614711001235,\n\
\ \"acc_norm\": 0.6699029126213593,\n \"acc_norm_stderr\": 0.0465614711001235\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7863247863247863,\n\
\ \"acc_stderr\": 0.026853450377009157,\n \"acc_norm\": 0.7863247863247863,\n\
\ \"acc_norm_stderr\": 0.026853450377009157\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.53,\n \"acc_stderr\": 0.05016135580465919,\n \
\ \"acc_norm\": 0.53,\n \"acc_norm_stderr\": 0.05016135580465919\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.6730523627075351,\n\
\ \"acc_stderr\": 0.016774908180131467,\n \"acc_norm\": 0.6730523627075351,\n\
\ \"acc_norm_stderr\": 0.016774908180131467\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.5144508670520231,\n \"acc_stderr\": 0.02690784985628254,\n\
\ \"acc_norm\": 0.5144508670520231,\n \"acc_norm_stderr\": 0.02690784985628254\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.41564245810055866,\n\
\ \"acc_stderr\": 0.016482782187500662,\n \"acc_norm\": 0.41564245810055866,\n\
\ \"acc_norm_stderr\": 0.016482782187500662\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.5163398692810458,\n \"acc_stderr\": 0.028614624752805427,\n\
\ \"acc_norm\": 0.5163398692810458,\n \"acc_norm_stderr\": 0.028614624752805427\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.5209003215434084,\n\
\ \"acc_stderr\": 0.02837327096106942,\n \"acc_norm\": 0.5209003215434084,\n\
\ \"acc_norm_stderr\": 0.02837327096106942\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.5185185185185185,\n \"acc_stderr\": 0.027801656212323674,\n\
\ \"acc_norm\": 0.5185185185185185,\n \"acc_norm_stderr\": 0.027801656212323674\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.38652482269503546,\n \"acc_stderr\": 0.029049190342543465,\n \
\ \"acc_norm\": 0.38652482269503546,\n \"acc_norm_stderr\": 0.029049190342543465\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3728813559322034,\n\
\ \"acc_stderr\": 0.012350630058333353,\n \"acc_norm\": 0.3728813559322034,\n\
\ \"acc_norm_stderr\": 0.012350630058333353\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.40441176470588236,\n \"acc_stderr\": 0.029812630701569743,\n\
\ \"acc_norm\": 0.40441176470588236,\n \"acc_norm_stderr\": 0.029812630701569743\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.45588235294117646,\n \"acc_stderr\": 0.020148939420415738,\n \
\ \"acc_norm\": 0.45588235294117646,\n \"acc_norm_stderr\": 0.020148939420415738\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.5909090909090909,\n\
\ \"acc_stderr\": 0.04709306978661896,\n \"acc_norm\": 0.5909090909090909,\n\
\ \"acc_norm_stderr\": 0.04709306978661896\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.5306122448979592,\n \"acc_stderr\": 0.031949171367580624,\n\
\ \"acc_norm\": 0.5306122448979592,\n \"acc_norm_stderr\": 0.031949171367580624\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.572139303482587,\n\
\ \"acc_stderr\": 0.03498541988407795,\n \"acc_norm\": 0.572139303482587,\n\
\ \"acc_norm_stderr\": 0.03498541988407795\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.65,\n \"acc_stderr\": 0.0479372485441102,\n \
\ \"acc_norm\": 0.65,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\
\ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.39759036144578314,\n\
\ \"acc_stderr\": 0.038099730845402184,\n \"acc_norm\": 0.39759036144578314,\n\
\ \"acc_norm_stderr\": 0.038099730845402184\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.7017543859649122,\n \"acc_stderr\": 0.03508771929824563,\n\
\ \"acc_norm\": 0.7017543859649122,\n \"acc_norm_stderr\": 0.03508771929824563\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.32558139534883723,\n\
\ \"mc1_stderr\": 0.016403989469907825,\n \"mc2\": 0.5188093512935639,\n\
\ \"mc2_stderr\": 0.016351300657386426\n }\n}\n```"
repo_url: https://huggingface.co/aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|arc:challenge|25_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hellaswag|10_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-09-14T19-14-45.418998.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-09-14T19-14-45.418998.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-14T19-14-45.418998.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-09-14T19-14-45.418998.parquet'
- config_name: results
data_files:
- split: 2023_09_14T19_14_45.418998
path:
- results_2023-09-14T19-14-45.418998.parquet
- split: latest
path:
- results_2023-09-14T19-14-45.418998.parquet
---
# Dataset Card for Evaluation run of aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset Summary
Dataset automatically created during the evaluation run of model [aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2](https://huggingface.co/aqweteddy/llama_chat-tv_en_luban-tv_stable_platypus2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_aqweteddy__llama_chat-tv_en_luban-tv_stable_platypus2",
"harness_truthfulqa_mc_0",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-14T19:14:45.418998](https://huggingface.co/datasets/open-llm-leaderboard/details_aqweteddy__llama_chat-tv_en_luban-tv_stable_platypus2/blob/main/results_2023-09-14T19-14-45.418998.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": 0.4945007463965186,
"acc_stderr": 0.03527731102256181,
"acc_norm": 0.49711825981073476,
"acc_norm_stderr": 0.035276035393914426,
"mc1": 0.32558139534883723,
"mc1_stderr": 0.016403989469907825,
"mc2": 0.5188093512935639,
"mc2_stderr": 0.016351300657386426
},
"harness|arc:challenge|25": {
"acc": 0.4351535836177474,
"acc_stderr": 0.014487986197186043,
"acc_norm": 0.4453924914675768,
"acc_norm_stderr": 0.01452398763834409
},
"harness|hellaswag|10": {
"acc": 0.4660426209918343,
"acc_stderr": 0.004978260641742204,
"acc_norm": 0.6102370045807608,
"acc_norm_stderr": 0.004866997110388195
},
"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": 0.4740740740740741,
"acc_stderr": 0.04313531696750574,
"acc_norm": 0.4740740740740741,
"acc_norm_stderr": 0.04313531696750574
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.47368421052631576,
"acc_stderr": 0.04063302731486671,
"acc_norm": 0.47368421052631576,
"acc_norm_stderr": 0.04063302731486671
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.53,
"acc_stderr": 0.05016135580465919,
"acc_norm": 0.53,
"acc_norm_stderr": 0.05016135580465919
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.5320754716981132,
"acc_stderr": 0.030709486992556538,
"acc_norm": 0.5320754716981132,
"acc_norm_stderr": 0.030709486992556538
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.5277777777777778,
"acc_stderr": 0.04174752578923185,
"acc_norm": 0.5277777777777778,
"acc_norm_stderr": 0.04174752578923185
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.33,
"acc_stderr": 0.047258156262526045,
"acc_norm": 0.33,
"acc_norm_stderr": 0.047258156262526045
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.43,
"acc_stderr": 0.049756985195624284,
"acc_norm": 0.43,
"acc_norm_stderr": 0.049756985195624284
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.29,
"acc_stderr": 0.04560480215720684,
"acc_norm": 0.29,
"acc_norm_stderr": 0.04560480215720684
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.4797687861271676,
"acc_stderr": 0.03809342081273957,
"acc_norm": 0.4797687861271676,
"acc_norm_stderr": 0.03809342081273957
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.2647058823529412,
"acc_stderr": 0.04389869956808778,
"acc_norm": 0.2647058823529412,
"acc_norm_stderr": 0.04389869956808778
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.67,
"acc_stderr": 0.04725815626252609,
"acc_norm": 0.67,
"acc_norm_stderr": 0.04725815626252609
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.425531914893617,
"acc_stderr": 0.032321469162244695,
"acc_norm": 0.425531914893617,
"acc_norm_stderr": 0.032321469162244695
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.3333333333333333,
"acc_stderr": 0.044346007015849245,
"acc_norm": 0.3333333333333333,
"acc_norm_stderr": 0.044346007015849245
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.4206896551724138,
"acc_stderr": 0.0411391498118926,
"acc_norm": 0.4206896551724138,
"acc_norm_stderr": 0.0411391498118926
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.2857142857142857,
"acc_stderr": 0.02326651221373057,
"acc_norm": 0.2857142857142857,
"acc_norm_stderr": 0.02326651221373057
},
"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": 0.36,
"acc_stderr": 0.04824181513244218,
"acc_norm": 0.36,
"acc_norm_stderr": 0.04824181513244218
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.535483870967742,
"acc_stderr": 0.028372287797962935,
"acc_norm": 0.535483870967742,
"acc_norm_stderr": 0.028372287797962935
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.3842364532019704,
"acc_stderr": 0.03422398565657551,
"acc_norm": 0.3842364532019704,
"acc_norm_stderr": 0.03422398565657551
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.56,
"acc_stderr": 0.049888765156985884,
"acc_norm": 0.56,
"acc_norm_stderr": 0.049888765156985884
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.6363636363636364,
"acc_stderr": 0.03756335775187896,
"acc_norm": 0.6363636363636364,
"acc_norm_stderr": 0.03756335775187896
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.6515151515151515,
"acc_stderr": 0.033948539651564025,
"acc_norm": 0.6515151515151515,
"acc_norm_stderr": 0.033948539651564025
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.7461139896373057,
"acc_stderr": 0.0314102478056532,
"acc_norm": 0.7461139896373057,
"acc_norm_stderr": 0.0314102478056532
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.5153846153846153,
"acc_stderr": 0.025339003010106515,
"acc_norm": 0.5153846153846153,
"acc_norm_stderr": 0.025339003010106515
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.2851851851851852,
"acc_stderr": 0.02752859921034049,
"acc_norm": 0.2851851851851852,
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},
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"mc2": 0.5188093512935639,
"mc2_stderr": 0.016351300657386426
}
}
```
### 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] |
distilled-from-one-sec-cv12/chunk_94 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 1244961616
num_examples: 242588
download_size: 1272146302
dataset_size: 1244961616
---
# Dataset Card for "chunk_94"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
ftopal/german-law-dataset | ---
dataset_info:
features:
- name: page_url
dtype: string
- name: law_page_url
dtype: string
- name: text
dtype: string
- name: sections
sequence: string
splits:
- name: train
num_bytes: 275461250
num_examples: 6746
download_size: 109054727
dataset_size: 275461250
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
biglab/webui-all | ---
license: other
---
This data accompanies the WebUI project (https://dl.acm.org/doi/abs/10.1145/3544548.3581158)
For more information, check out the project website: https://uimodeling.github.io/
To download this dataset, you need to install the huggingface-hub package
```
pip install huggingface-hub
```
Use snapshot_download
```
from huggingface_hub import snapshot_download
snapshot_download(repo_id="biglab/webui-all", repo_type="dataset")
```
IMPORTANT
* Before downloading and using, please review the copyright info here: https://github.com/js0nwu/webui/blob/main/COPYRIGHT.txt
* Not all data samples have the same number of files (e.g., same number of device screenshots) due to the fact that the crawler used a timeout during collection
* The dataset released on HuggingFace was filtered using a list of explicit words and therefore contains fewer samples than the experiments originally used in the paper. The raw dataset is currently available (https://drive.google.com/drive/folders/1hcO75W2FjsZoibsj2TIbKz67hy9JkOBz?usp=share_link) but may be removed in the future. |
AnonymousGM/MultiSetTransformerData | ---
license: mit
---
## General Description
MultiSetTransformerData is a large dataset designed to train and validate neural Symbolic Regression models. It was designed to solve the Multi-Set Symbolic Skeleton Prediction (MSSP) problems, described in the paper **"Univariate Skeleton Prediction in Multivariate Systems Using Transformers"**. However, it can be used for training generic SR models as well.
This dataset consists of artificially generated **univariate symbolic skeletons**, from which mathematical expressions are sampled, which are then used to sample data sets.
In this repository, two subsets are presented, **Q1** and **Q2**:
* **Q1**: Consists of mathematical expressions that use up to 5 unary and binary operators (e.g., \\(1 + 1 / (\sin(2x) + 3)\\) uses five operators).
* **Q2**: Consists of mathematical expressions that use up to 7 unary and binary operators.
Both datasets allow up to one nested operator (e.g., \\(\sin( \exp(x))\\) is allowed but \\(\sin( \exp(x^2))\\) is not).
## Dataset Structure
In both subsets **Q1** and **Q2**, you will find a training set alongside its corresponding validation set.
Then, each folder consists of a collection of HDF5 files, as shown below:
```
├── Q1
│ ├── training
│ │ ├── 0.h5
│ │ ├── 1.h5
│ │ ├── ...
│ ├── validation
│ │ ├── 0.h5
│ │ ├── 1.h5
│ │ ├── ...
```
Each HDF5 file contains 5000 **blocks** and has the following structure:
```
{ "block_1": {
"X": "Support vector, shape (10000, 10)",
"Y": "Response vector, shape (10000, 10)",
"tokenized": "Symbolic skeleton expression tokenized using vocabulary, list",
"exprs": "Symbolic skeleton expression, str",
"sampled_exprs": "Ten mathematical expressions sampled from a common skeleton"
},
"block_2": {
"X": "Support, shape (10000, 10)",
"Y": "Response, shape (10000, 10)",
"tokenized": "Symbolic skeleton expression tokenized using vocabulary, list",
"exprs": "Symbolic skeleton expression, str",
"sampled_exprs": "Ten mathematical expressions sampled from a common skeleton"
},
...
}
```
More specifically, each block corresponds to one univariate symbolic skeleton (i.e., a function without defined constant values); for example, `c + c/(c*sin(c*x_1) + c)`.
From this skeleton, 10 random functions are sampled; for example:
* `-2.284 + 0.48/(-sin(0.787*x_1) - 1.136)`
* `4.462 - 2.545/(3.157*sin(0.422*x_1) - 1.826)`, ...
Then, for the \\(i\\)-th function (where \\(i \in [0, 1, ..., 9]\\)), we sample a **support vector** `X[:, i]` of 10000 elements whose values are drawn from a uniform distribution \\(\mathcal{U}(-10, 10)\\).
The support vector `X[:, i]` is evaluated on the \\(i\\)-th function to obtain the response vector `Y[:, i]`.
In other words, a block contains input-output data generated from 10 **different functions that share the same symbolic skeleton**.
For instance, the following figure shows 10 sets of data generated from the symbolic skeleton `c + c/(c*sin(c*x_1) + c)`:
<p align="center">
<img src="images/data_example.jpg" alt="alt text" width="600">
</p>
## Loading Data
Once the data is downloaded, it can be loaded using Python as follows:
```
imort os
import glob
import h5py
def open_h5(path):
block = []
with h5py.File(path, "r") as hf:
# Iterate through the groups in the HDF5 file (group names are integers)
for group_name in hf:
group = hf[group_name]
X = group["X"][:]
Y = group["Y"][:]
# Load 'tokenized' as a list of integers
tokenized = list(group["tokenized"])
# Load 'exprs' as a string
exprs = group["exprs"][()].tobytes().decode("utf-8")
# Load 'sampled_exprs' as a list of sympy expressions
sampled_exprs = [expr_str for expr_str in group["sampled_exprs"][:].astype(str)]
block.append([X, Y, tokenized, exprs, sampled_exprs])
return block
train_path = 'data/Q1/training'
train_files = glob.glob(os.path.join(self.sampledData_train_path, '*.h5'))
for tfile in train_files:
# Read block
block = open_h5(tfile)
# Do stuff with your data
```
## Vocabulary and Expression Generation
The table below provides the vocabulary used to construct the expressions of this dataset.
<p align="center">
<img src="images/vocabulary.jpg" alt="alt text" width="500">
</p>
We use a method that builds the expression tree recursively in a preorder fashion, which allows us to enforce certain conditions and constraints effectively.
That is, we forbid certain combinations of operators and set a maximum limit on the nesting depth of unary operators within each other.
For example, we avoid embedding the operator \\(\text{log}\\) within the operator \\(\text{exp}\\), or vice versa, since such composition could lead to direct simplification (e.g., \\(\text{log}\left( \text{exp} (x) \right) = x\\).
We can also avoid combinations of operators that would generate extremely large values (e.g., \\(\text{exp}\left( \text{exp} (x) \right)\\) and \\(\text{sinh} \left( \text{sinh} (x) \right)\\)).
The table below shows the forbidden operators we considered for some specific parent operators.
<p align="center">
<img src="images/forbidden_ops.jpg" alt="alt text" width="500">
</p>
## Citation
Our paper **"Univariate Skeleton Prediction in Multivariate Systems Using Transformers"** is currently undergoing "double-blind" review process at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024).
We will provide more details after acceptance.
|
onethousand/LPFF | ---
license: cc-by-nc-2.0
---
# LPFF: Large-Pose-Flickr-Faces Dataset
**LPFF is a large-pose Flickr face dataset comprised of 19,590 high-quality real large-pose portrait images.**
> **[ICCV 2023] LPFF: A Portrait Dataset for Face Generators Across Large Poses**
>
> [Yiqian Wu](https://onethousandwu.com/), Jing Zhang, [Hongbo Fu](http://sweb.cityu.edu.hk/hongbofu/publications.html), [Xiaogang Jin*](http://www.cad.zju.edu.cn/home/jin)
[Paper](https://arxiv.org/abs/2303.14407) [Video](http://www.cad.zju.edu.cn/home/jin/iccv2023/demo.mp4) [Suppl](https://drive.google.com/file/d/1Xktg7oqMMNN9hqGYva3BBTJoux17y2SR/view?usp=sharing) [Project Page](http://www.cad.zju.edu.cn/home/jin/iccv2023/iccv2023.htm)
The creation of 2D realistic facial images and 3D face shapes using generative networks has been a hot topic in recent years. Existing face generators exhibit exceptional performance on faces in small to medium poses (with respect to frontal faces), but struggle to produce realistic results for large poses. The distorted rendering results on large poses in 3D-aware generators further show that the generated 3D face shapes are far from the distribution of 3D faces in reality. We find that the above issues are caused by the training dataset's posture imbalance.
In this paper, we present **LPFF**, a large-pose Flickr face dataset comprised of 19,590 high-quality real large-pose portrait images. We utilize our dataset to train a 2D face generator that can process large-pose face images, as well as a 3D-aware generator that can generate realistic human face geometry. To better validate our pose-conditional 3D-aware generators, we develop a new FID measure to evaluate the 3D-level performance. Through this novel FID measure and other experiments, we show that LPFF can help 2D face generators extend their latent space and better manipulate the large-pose data, and help 3D-aware face generators achieve better view consistency and more realistic 3D reconstruction results.
### Available sources
Notice: We have uploaded all the data using OneDrive, and the shared link should be updated every two months. If you find that the link is not working, please contact us to update it.
| | Description |
| ------------------------------------------------------------ | ------------------------------------------------------------ |
| [dataset](https://github.com/oneThousand1000/LPFF-dataset/tree/master/dataset_download) | Dataset download. |
| [data_processing](https://github.com/oneThousand1000/LPFF-dataset/tree/master/data_processing) | Data processing codes and data download links. Including image alignment, camera parameters extraction, and dataset rebalance. |
| [training](https://github.com/oneThousand1000/LPFF-dataset/tree/master/training) | Model training and FID computation guidance. |
| [networks](https://github.com/oneThousand1000/LPFF-dataset/tree/master/networks) | Pretrained StyleGAN2-ada and EG3D models trained on the LPFF+FFHQ dataset. |
### Contact
[onethousand@zju.edu.cn](mailto:onethousand@zju.edu.cn) / [onethousand1250@gmail.com](mailto:onethousand1250@gmail.com)
### Citation
If you find this project helpful to your research, please consider citing:
```
@inproceedings{wu2023iccvlpff,
author = {Yiqian Wu and Jing Zhang and Hongbo Fu and Xiaogang Jin},
title = {LPFF: A Portrait Dataset for Face Generators Across Large Poses},
booktitle = {2023 {IEEE/CVF} International Conference on Computer Vision, {ICCV}, France, October 2-3, 2023},
publisher = {{IEEE}},
year = {2023},
}
```
|
atmallen/fever | ---
dataset_info:
features:
- name: id
dtype: int32
- name: label
dtype:
class_label:
names:
'0': REFUTES
'1': SUPPORTS
- name: claim
dtype: string
- name: evidence_annotation_id
dtype: int32
- name: evidence_id
dtype: int32
- name: evidence_wiki_url
dtype: string
- name: evidence_sentence_id
dtype: int32
- name: ev_sentence
dtype: string
- name: ev_paragraph
dtype: string
splits:
- name: train
num_bytes: 45894925.26486
num_examples: 27129
- name: validation
num_bytes: 6624298.64
num_examples: 4912
- name: test
num_bytes: 10877370.514204947
num_examples: 7199
download_size: 20846819
dataset_size: 63396594.41906495
---
# Dataset Card for "fever"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
PurCL/bincorp-26m-all | ---
viewer: true
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: valid
path: data/valid-*
dataset_info:
features:
- name: code
dtype: string
- name: data_dep
dtype: string
splits:
- name: train
num_bytes: 39826202125.70429
num_examples: 14019961
- name: test
num_bytes: 11713589027.6
num_examples: 4123518
- name: valid
num_bytes: 7028153984.695704
num_examples: 2474111
download_size: 19420221346
dataset_size: 58567945137.99999
---
# Dataset Card for "bincorp-26m-all"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
simustar/stackmathqa50k-instruct | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 76046968
num_examples: 50000
download_size: 39336427
dataset_size: 76046968
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
zhangyue/test-one | ---
dataset_info:
features:
- name: id
dtype: string
- name: package_name
dtype: string
- name: review
dtype: string
- name: date
dtype: string
- name: star
dtype: int64
- name: version_id
dtype: int64
splits:
- name: train
num_bytes: 1508
num_examples: 5
- name: test
num_bytes: 956
num_examples: 5
download_size: 9453
dataset_size: 2464
---
# Dataset Card for "test-one"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
davidaponte/dreambooth-hackathon-images-miko | ---
dataset_info:
features:
- name: image
dtype: image
splits:
- name: train
num_bytes: 42574511.0
num_examples: 14
download_size: 42573847
dataset_size: 42574511.0
---
# Dataset Card for "dreambooth-hackathon-images-miko"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
YoungPanda/swag1 | ---
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: neg
dtype: string
- name: answer
dtype: string
splits:
- name: train
num_bytes: 1153881
num_examples: 485
download_size: 530487
dataset_size: 1153881
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
liuyanchen1015/MULTI_VALUE_rte_flat_adj_for_adv | ---
dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: label
dtype: int64
- name: idx
dtype: int64
- name: value_score
dtype: int64
splits:
- name: test
num_bytes: 24239
num_examples: 54
- name: train
num_bytes: 23018
num_examples: 53
download_size: 42970
dataset_size: 47257
---
# Dataset Card for "MULTI_VALUE_rte_flat_adj_for_adv"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
yeajinmin/NER-News-BIDataset | ---
dataset_info:
features:
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 76440290.15811698
num_examples: 120113
- name: test
num_bytes: 19110549.84188302
num_examples: 30029
download_size: 16997872
dataset_size: 95550840
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
task_categories:
- token-classification
language:
- ko
size_categories:
- 100K<n<1M
---
## Dataset Summary
NER-News-BIDataset is a dataset for named entity recognition (NER) in news articles, publicly released by the National Institute of Korean Language in 2023.
The dataset is labeled with named entities specifically for news data.
It consists of a total of 150,142 sentences, and entities are categorized into 150 labels for recognition.
## Languages
Korean
## Data Structure
DatasetDict({
train: Dataset({
features: ['input_ids', 'attention_mask', 'labels'],
num_rows: 120113
})
test: Dataset({
features: ['input_ids', 'attention_mask', 'labels'],
num_rows: 30029
})
})
### Data Instances
The dataset is provided in text format with train/test sets.
Each instance represents a news article, and if there is an entity in the sentence, it is appropriately tagged with the corresponding label.
In cases where a single entity is separated into multiple tokens, the first token is labeled as "B-entity" and the subsequent tokens are labeled as "I-entity" until the end.
### Data Fields
input_ids: "A processed named entity corpus of news articles constructed in 2022" has been tokenized and represented with numerical values.
label: Identified a total of 151 entities, including the 0th label (not an entity). If counting both "B-entity" and "I-entity" labels for each entity, there are a total of 301 labels.
The labeling is done with numerical values.
The 151 types of labels are as follows:
|index|0|1|2|3|4|5|6|7|8|9|10|11|12|13|14|15|16|17|18|19|20|21|22|23|24|25|26|27|28|29|30|31|32|33|34|35|36|37|38|39|40|41|42|43|44|45|46|47|48|49|50|51|52|53|54|55|56|57|58|59|60|61|62|63|64|65|66|67|68|69|70|71|72|73|74|75|76|77|78|79|80|81|82|83|84|85|86|87|88|89|90|91|92|93|94|95|96|97|98|99|100|101|102|103|104|105|106|107|108|109|110|111|112|113|114|115|116|117|118|119|120|121|122|123|124|125|126|127|128|129|130|131|132|133|134|135|136|137|138|139|140|141|142|143|144|145|146|147|148|149|150|151|152|153|154|155|156|157|158|159|160|161|162|163|164|165|166|167|168|169|170|171|172|173|174|175|176|177|178|179|180|181|182|183|184|185|186|187|188|189|190|191|192|193|194|195|196|197|198|199|200|201|202|203|204|205|206|207|208|209|210|211|212|213|214|215|216|217|218|219|220|221|222|223|224|225|226|227|228|229|230|231|232|233|234|235|236|237|238|239|240|241|242|243|244|245|246|247|248|249|250|251|252|253|254|255|256|257|258|259|260|261|262|263|264|265|266|267|268|269|270|271|272|273|274|275|276|277|278|279|280|281|282|283|284|285|286|287|288|289|290|291|292|293|294|295|296|297|298|299|300|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Label|O|B-PS\_NAME|B-PS\_CHARACTER|B-PS\_PET|B-FD\_SCIENCE|B-FD\_SOCIAL\_SCIENCE|B-FD\_MEDICINE|B-FD\_ART|B-FD\_HUMANITIES|B-FD\_OTHERS|B-TR\_SCIENCE|B-TR\_SOCIAL\_SCIENCE|B-TR\_MEDICINE|B-TR\_ART|B-TR\_HUMANITIES|B-TR\_OTHERS|B-AF\_BUILDING|B-AF\_CULTURAL\_ASSET|B-AF\_ROAD|B-AF\_TRANSPORT|B-AF\_MUSICAL\_INSTRUMENT|B-AF\_WEAPON|B-AFA\_DOCUMENT|B-AFA\_PERFORMANCE|B-AFA\_VIDEO|B-AFA\_ART\_CRAFT|B-AFA\_MUSIC|B-AFW\_SERVICE\_PRODUCTS|B-AFW\_OTHER\_PRODUCTS|B-OGG\_ECONOMY|B-OGG\_EDUCATION|B-OGG\_MILITARY|B-OGG\_MEDIA|B-OGG\_SPORTS|B-OGG\_ART|B-OGG\_MEDICINE|B-OGG\_RELIGION|B-OGG\_SCIENCE|B-OGG\_LIBRARY|B-OGG\_LAW|B-OGG\_POLITICS|B-OGG\_FOOD|B-OGG\_HOTEL|B-OGG\_OTHERS|B-LCP\_COUNTRY|B-LCP\_PROVINCE|B-LCP\_COUNTY|B-LCP\_CITY|B-LCP\_CAPITALCITY|B-LCG\_RIVER|B-LCG\_OCEAN|B-LCG\_BAY|B-LCG\_MOUNTAIN|B-LCG\_ISLAND|B-LCG\_CONTINENT|B-LC\_SPACE|B-LC\_OTHERS|B-CV\_CULTURE|B-CV\_TRIBE|B-CV\_LANGUAGE|B-CV\_POLICY|B-CV\_LAW|B-CV\_CURRENCY|B-CV\_TAX|B-CV\_FUNDS|B-CV\_ART|B-CV\_SPORTS|B-CV\_SPORTS\_POSITION|B-CV\_SPORTS\_INST|B-CV\_PRIZE|B-CV\_RELATION|B-CV\_OCCUPATION|B-CV\_POSITION|B-CV\_FOOD|B-CV\_DRINK|B-CV\_FOOD\_STYLE|B-CV\_CLOTHING|B-CV\_BUILDING\_TYPE|B-DT\_DURATION|B-DT\_DAY|B-DT\_WEEK|B-DT\_MONTH|B-DT\_YEAR|B-DT\_SEASON|B-DT\_GEOAGE|B-DT\_DYNASTY|B-DT\_OTHERS|B-TI\_DURATION|B-TI\_HOUR|B-TI\_MINUTE|B-TI\_SECOND|B-TI\_OTHERS|B-QT\_AGE|B-QT\_SIZE|B-QT\_LENGTH|B-QT\_COUNT|B-QT\_MAN\_COUNT|B-QT\_WEIGHT|B-QT\_PERCENTAGE|B-QT\_SPEED|B-QT\_TEMPERATURE|B-QT\_VOLUME|B-QT\_ORDER|B-QT\_PRICE|B-QT\_PHONE|B-QT\_SPORTS|B-QT\_CHANNEL|B-QT\_ALBUM|B-QT\_ADDRESS|B-QT\_OTHERS|B-EV\_ACTIVITY|B-EV\_WAR\_REVOLUTION|B-EV\_SPORTS|B-EV\_FESTIVAL|B-EV\_OTHERS|B-AM\_INSECT|B-AM\_BIRD|B-AM\_FISH|B-AM\_MAMMALIA|B-AM\_AMPHIBIA|B-AM\_REPTILIA|B-AM\_TYPE|B-AM\_PART|B-AM\_OTHERS|B-PT\_FRUIT|B-PT\_FLOWER|B-PT\_TREE|B-PT\_GRASS|B-PT\_TYPE|B-PT\_PART|B-PT\_OTHERS|B-MT\_ELEMENT|B-MT\_METAL|B-MT\_ROCK|B-MT\_CHEMICAL|B-TM\_COLOR|B-TM\_DIRECTION|B-TM\_CLIMATE|B-TM\_SHAPE|B-TM\_CELL\_TISSUE\_ORGAN|B-TMM\_DISEASE|B-TMM\_DRUG|B-TMI\_HW|B-TMI\_SW|B-TMI\_SITE|B-TMI\_EMAIL|B-TMI\_MODEL|B-TMI\_SERVICE|B-TMI\_PROJECT|B-TMIG\_GENRE|B-TM\_SPORTS|I-PS\_NAME|I-PS\_CHARACTER|I-PS\_PET|I-FD\_SCIENCE|I-FD\_SOCIAL\_SCIENCE|I-FD\_MEDICINE|I-FD\_ART|I-FD\_HUMANITIES|I-FD\_OTHERS|I-TR\_SCIENCE|I-TR\_SOCIAL\_SCIENCE|I-TR\_MEDICINE|I-TR\_ART|I-TR\_HUMANITIES|I-TR\_OTHERS|I-AF\_BUILDING|I-AF\_CULTURAL\_ASSET|I-AF\_ROAD|I-AF\_TRANSPORT|I-AF\_MUSICAL\_INSTRUMENT|I-AF\_WEAPON|I-AFA\_DOCUMENT|I-AFA\_PERFORMANCE|I-AFA\_VIDEO|I-AFA\_ART\_CRAFT|I-AFA\_MUSIC|I-AFW\_SERVICE\_PRODUCTS|I-AFW\_OTHER\_PRODUCTS|I-OGG\_ECONOMY|I-OGG\_EDUCATION|I-OGG\_MILITARY|I-OGG\_MEDIA|I-OGG\_SPORTS|I-OGG\_ART|I-OGG\_MEDICINE|I-OGG\_RELIGION|I-OGG\_SCIENCE|I-OGG\_LIBRARY|I-OGG\_LAW|I-OGG\_POLITICS|I-OGG\_FOOD|I-OGG\_HOTEL|I-OGG\_OTHERS|I-LCP\_COUNTRY|I-LCP\_PROVINCE|I-LCP\_COUNTY|I-LCP\_CITY|I-LCP\_CAPITALCITY|I-LCG\_RIVER|I-LCG\_OCEAN|I-LCG\_BAY|I-LCG\_MOUNTAIN|I-LCG\_ISLAND|I-LCG\_CONTINENT|I-LC\_SPACE|I-LC\_OTHERS|I-CV\_CULTURE|I-CV\_TRIBE|I-CV\_LANGUAGE|I-CV\_POLICY|I-CV\_LAW|I-CV\_CURRENCY|I-CV\_TAX|I-CV\_FUNDS|I-CV\_ART|I-CV\_SPORTS|I-CV\_SPORTS\_POSITION|I-CV\_SPORTS\_INST|I-CV\_PRIZE|I-CV\_RELATION|I-CV\_OCCUPATION|I-CV\_POSITION|I-CV\_FOOD|I-CV\_DRINK|I-CV\_FOOD\_STYLE|I-CV\_CLOTHING|I-CV\_BUILDING\_TYPE|I-DT\_DURATION|I-DT\_DAY|I-DT\_WEEK|I-DT\_MONTH|I-DT\_YEAR|I-DT\_SEASON|I-DT\_GEOAGE|I-DT\_DYNASTY|I-DT\_OTHERS|I-TI\_DURATION|I-TI\_HOUR|I-TI\_MINUTE|I-TI\_SECOND|I-TI\_OTHERS|I-QT\_AGE|I-QT\_SIZE|I-QT\_LENGTH|I-QT\_COUNT|I-QT\_MAN\_COUNT|I-QT\_WEIGHT|I-QT\_PERCENTAGE|I-QT\_SPEED|I-QT\_TEMPERATURE|I-QT\_VOLUME|I-QT\_ORDER|I-QT\_PRICE|I-QT\_PHONE|I-QT\_SPORTS|I-QT\_CHANNEL|I-QT\_ALBUM|I-QT\_ADDRESS|I-QT\_OTHERS|I-EV\_ACTIVITY|I-EV\_WAR\_REVOLUTION|I-EV\_SPORTS|I-EV\_FESTIVAL|I-EV\_OTHERS|I-AM\_INSECT|I-AM\_BIRD|I-AM\_FISH|I-AM\_MAMMALIA|I-AM\_AMPHIBIA|I-AM\_REPTILIA|I-AM\_TYPE|I-AM\_PART|I-AM\_OTHERS|I-PT\_FRUIT|I-PT\_FLOWER|I-PT\_TREE|I-PT\_GRASS|I-PT\_TYPE|I-PT\_PART|I-PT\_OTHERS|I-MT\_ELEMENT|I-MT\_METAL|I-MT\_ROCK|I-MT\_CHEMICAL|I-TM\_COLOR|I-TM\_DIRECTION|I-TM\_CLIMATE|I-TM\_SHAPE|I-TM\_CELL\_TISSUE\_ORGAN|I-TMM\_DISEASE|I-TMM\_DRUG|I-TMI\_HW|I-TMI\_SW|I-TMI\_SITE|I-TMI\_EMAIL|I-TMI\_MODEL|I-TMI\_SERVICE|I-TMI\_PROJECT|I-TMIG\_GENRE|I-TM\_SPORTS|
|Number|0|1|2|3|4|5|6|7|8|9|10|11|12|13|14|15|16|17|18|19|20|21|22|23|24|25|26|27|28|29|30|31|32|33|34|35|36|37|38|39|40|41|42|43|44|45|46|47|48|49|50|51|52|53|54|55|56|57|58|59|60|61|62|63|64|65|66|67|68|69|70|71|72|73|74|75|76|77|78|79|80|81|82|83|84|85|86|87|88|89|90|91|92|93|94|95|96|97|98|99|100|101|102|103|104|105|106|107|108|109|110|111|112|113|114|115|116|117|118|119|120|121|122|123|124|125|126|127|128|129|130|131|132|133|134|135|136|137|138|139|140|141|142|143|144|145|146|147|148|149|150|151|152|153|154|155|156|157|158|159|160|161|162|163|164|165|166|167|168|169|170|171|172|173|174|175|176|177|178|179|180|181|182|183|184|185|186|187|188|189|190|191|192|193|194|195|196|197|198|199|200|201|202|203|204|205|206|207|208|209|210|211|212|213|214|215|216|217|218|219|220|221|222|223|224|225|226|227|228|229|230|231|232|233|234|235|236|237|238|239|240|241|242|243|244|245|246|247|248|249|250|251|252|253|254|255|256|257|258|259|260|261|262|263|264|265|266|267|268|269|270|271|272|273|274|275|276|277|278|279|280|281|282|283|284|285|286|287|288|289|290|291|292|293|294|295|296|297|298|299|300|
Frequency Statistics
|index|0|1|2|3|4|5|6|7|8|9|10|11|12|13|14|15|16|17|18|19|20|21|22|23|24|25|26|27|28|29|30|31|32|33|34|35|36|37|38|39|40|41|42|43|44|45|46|47|48|49|50|51|52|53|54|55|56|57|58|59|60|61|62|63|64|65|66|67|68|69|70|71|72|73|74|75|76|77|78|79|80|81|82|83|84|85|86|87|88|89|90|91|92|93|94|95|96|97|98|99|100|101|102|103|104|105|106|107|108|109|110|111|112|113|114|115|116|117|118|119|120|121|122|123|124|125|126|127|128|129|130|131|132|133|134|135|136|137|138|139|140|141|142|143|144|145|146|147|148|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Label|OGG\_POLITICS|CV\_POSITION|PS\_NAME|QT\_COUNT|LCP\_CITY|DT\_DAY|DT\_YEAR|LCP\_COUNTY|QT\_ORDER|DT\_OTHERS|TMM\_DISEASE|QT\_PRICE|QT\_MAN\_COUNT|DT\_DURATION|CV\_OCCUPATION|LC\_OTHERS|OGG\_ECONOMY|QT\_PERCENTAGE|OGG\_OTHERS|TMI\_PROJECT|LCP\_PROVINCE|AF\_TRANSPORT|OGG\_EDUCATION|LCP\_COUNTRY|EV\_OTHERS|AF\_BUILDING|CV\_LAW|TMI\_HW|OGG\_SPORTS|DT\_MONTH|CV\_RELATION|CV\_POLICY|CV\_FOOD|TI\_DURATION|TMI\_SERVICE|OGG\_MEDICINE|QT\_AGE|QT\_SIZE|AF\_ROAD|EV\_FESTIVAL|AM\_PART|EV\_SPORTS|CV\_PRIZE|TR\_SCIENCE|TM\_DIRECTION|OGG\_ART|QT\_OTHERS|PT\_GRASS|QT\_LENGTH|MT\_CHEMICAL|OGG\_SCIENCE|PT\_FRUIT|LCP\_CAPITALCITY|CV\_SPORTS|TMM\_DRUG|CV\_ART|LCG\_RIVER|AF\_CULTURAL\_ASSET|TM\_CELL\_TISSUE\_ORGAN|OGG\_RELIGION|QT\_SPORTS|QT\_WEIGHT|DT\_SEASON|AFA\_DOCUMENT|OGG\_MEDIA|TI\_OTHERS|TI\_HOUR|OGG\_MILITARY|LCG\_ISLAND|CV\_DRINK|LCG\_MOUNTAIN|CV\_TAX|CV\_FUNDS|TR\_MEDICINE|AFA\_VIDEO|AM\_MAMMALIA|OGG\_FOOD|MT\_ELEMENT|TM\_SPORTS|AM\_OTHERS|LCG\_CONTINENT|PT\_PART|OGG\_LAW|AFW\_OTHER\_PRODUCTS|CV\_CULTURE|AFW\_SERVICE\_PRODUCTS|CV\_CLOTHING|DT\_DYNASTY|FD\_MEDICINE|PT\_FLOWER|CV\_TRIBE|PT\_TREE|FD\_SCIENCE|TM\_COLOR|AM\_BIRD|QT\_ADDRESS|QT\_PHONE|CV\_LANGUAGE|TR\_SOCIAL\_SCIENCE|EV\_ACTIVITY|EV\_WAR\_REVOLUTION|CV\_SPORTS\_POSITION|OGG\_LIBRARY|AM\_TYPE|TMI\_SW|AFA\_MUSIC|DT\_WEEK|AFA\_PERFORMANCE|AFA\_ART\_CRAFT|FD\_HUMANITIES|QT\_VOLUME|TMI\_SITE|OGG\_HOTEL|LCG\_BAY|PS\_CHARACTER|LCG\_OCEAN|AM\_INSECT|AM\_FISH|QT\_TEMPERATURE|PT\_OTHERS|TM\_SHAPE|MT\_METAL|MT\_ROCK|AF\_MUSICAL\_INSTRUMENT|PT\_TYPE|QT\_SPEED|AF\_WEAPON|CV\_FOOD\_STYLE|LC\_SPACE|FD\_SOCIAL\_SCIENCE|CV\_SPORTS\_INST|TR\_ART|FD\_OTHERS|AM\_AMPHIBIA|AM\_REPTILIA|TMIG\_GENRE|TR\_OTHERS|TMI\_EMAIL|CV\_BUILDING\_TYPE|PS\_PET|TR\_HUMANITIES|DT\_GEOAGE|FD\_ART|CV\_CURRENCY|TMI\_MODEL|TI\_SECOND|QT\_CHANNEL|TM\_CLIMATE|TI\_MINUTE|
|Frequency|69683|43695|42060|30949|24791|19994|19836|19376|17908|17768|17622|15686|15460|15385|13634|13473|12744|12129|9912|9249|9084|8689|7475|7378|6144|5193|4875|4458|4440|4360|4002|3944|3537|3277|2993|2803|2659|2523|2465|2407|2401|2400|2231|2145|1999|1914|1911|1617|1615|1602|1589|1515|1395|1322|1307|1289|1258|1244|1165|1157|1145|1110|1097|987|980|979|976|967|937|884|869|859|857|855|837|775|752|720|715|689|688|683|667|631|583|505|467|453|445|441|437|410|395|391|391|388|383|370|367|367|362|337|304|296|285|283|275|273|265|245|240|229|222|220|220|204|192|191|188|158|151|149|148|130|126|124|113|110|107|82|52|43|42|41|40|37|35|34|30|25|22|19|19|11|8|8|5|3|2|
### Data Splits
The dataset, consisting of 150,142 sentences, has been split in a ratio of 8:2. There are 120,113 sentences in the training set and 3,029 sentences in the test set.
## Source Data
This dataset is based on the 'National Institute of Korean Language Named Entity Analysis Corpus 2022 (Version 1.1)' released by the National Institute of Korean Language in September 2023.
For more detailed information, please refer to the National Institute of Korean Language website > Resources > Research Materials > '2022 Corpus Named Entity Analysis and Entity Linking' project report.
### Citation
(국문) 국립국어원(2023). 국립국어원 개체명 분석 말뭉치 2022(버전 1.1) URL: https://corpus.korean.go.kr
(Eng) National Institute of Korean Language(2023). NIKL Named Entity Corpus 2022 (v.1.1) URL: https://corpus.korean.go.kr |
NickyNicky/Code-290k-labels-programming_languages-NO_Chatgpt | ---
dataset_info:
features:
- name: conversations
list:
- name: from
dtype: string
- name: value
dtype: string
- name: lenguaje_detectado
dtype: string
- name: puntuaciones
struct:
- name: C
dtype: int64
- name: C#
dtype: int64
- name: C++
dtype: int64
- name: Go
dtype: int64
- name: HTML
dtype: int64
- name: Java
dtype: int64
- name: JavaScript
dtype: int64
- name: Kotlin
dtype: int64
- name: PHP
dtype: int64
- name: Python
dtype: int64
- name: Ruby
dtype: int64
- name: Rust
dtype: int64
- name: Scala
dtype: int64
- name: Swift
dtype: int64
- name: TypeScript
dtype: int64
splits:
- name: train
num_bytes: 580134842
num_examples: 289094
download_size: 271854323
dataset_size: 580134842
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
language:
- en
---
Para etiquetar los lenguajes de programación en un conjunto de datos extenso de fragmentos de código, se aplicaron técnicas automatizadas de procesamiento de texto y patrones específicos de cada lenguaje, sin recurrir al uso de modelos de lenguaje avanzados como ChatGPT o LLMs. Se inició con la extracción y preparación de datos usando pandas, una biblioteca de análisis de datos en Python, que facilitó la manipulación y el procesamiento del conjunto de datos obtenido de Hugging Face's datasets.
Se definieron criterios específicos para identificar cada lenguaje de programación, basados en las palabras clave y sintaxis única de estos lenguajes. Esta metodología implicó la creación de una lista detallada de palabras clave para cada lenguaje, como estructuras de control, tipos de datos, y sintaxis de definición de funciones y clases, que son indicadores fuertes del lenguaje utilizado en un fragmento de código.
Para la implementación, se utilizó expresiones regulares y búsqueda de patrones dentro del texto del código, permitiendo así una primera aproximación a la clasificación de los fragmentos de código. El proceso fue escalado para manejar miles de fragmentos mediante la ejecución paralela de tareas, utilizando el módulo concurrent.futures de Python, lo que permitió mejorar significativamente la eficiencia del procesamiento.
Una vez procesados y clasificados los fragmentos de código según el lenguaje de programación, se realizó un análisis cuantitativo del conjunto de datos resultante. Esto incluyó el conteo de la frecuencia de cada lenguaje identificado, ofreciendo una visión general de la distribución de lenguajes dentro del conjunto de datos. Para visualizar estos resultados de manera intuitiva, se generó un gráfico de pastel utilizando la biblioteca matplotlib, la cual proporcionó una representación gráfica clara de la prevalencia de cada lenguaje de programación en el conjunto de datos analizado.
Este enfoque metodológico demuestra que, mediante el uso de técnicas de procesamiento de texto y análisis de datos, es posible etiquetar eficazmente lenguajes de programación en grandes conjuntos de datos de código, sin necesidad de recurrir a modelos de lenguaje avanzados como ChatGPT.
Nota:
No es 100% fiable pero logra acertar en su mayoria
<!--Code-->
<!--https://colab.research.google.com/drive/1u7HeVeT9tAGcQC73ABEOvvA-yWkxxsZz#scrollTo=WeltUYpCMKJA--> |
alexandrainst/scandi-qa | ---
pretty_name: ScandiQA
language:
- da
- sv
- no
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
size_categories:
- 1K<n<10K
source_datasets:
- mkqa
- natural_questions
task_categories:
- question-answering
task_ids:
- extractive-qa
---
# Dataset Card for ScandiQA
## Dataset Description
- **Repository:** <https://github.com/alexandrainst/scandi-qa>
- **Point of Contact:** [Dan Saattrup Nielsen](mailto:dan.nielsen@alexandra.dk)
- **Size of downloaded dataset files:** 69 MB
- **Size of the generated dataset:** 67 MB
- **Total amount of disk used:** 136 MB
### Dataset Summary
ScandiQA is a dataset of questions and answers in the Danish, Norwegian, and Swedish
languages. All samples come from the Natural Questions (NQ) dataset, which is a large
question answering dataset from Google searches. The Scandinavian questions and answers
come from the MKQA dataset, where 10,000 NQ samples were manually translated into,
among others, Danish, Norwegian, and Swedish. However, this did not include a
translated context, hindering the training of extractive question answering models.
We merged the NQ dataset with the MKQA dataset, and extracted contexts as either "long
answers" from the NQ dataset, being the paragraph in which the answer was found, or
otherwise we extract the context by locating the paragraphs which have the largest
cosine similarity to the question, and which contains the desired answer.
Further, many answers in the MKQA dataset were "language normalised": for instance, all
date answers were converted to the format "YYYY-MM-DD", meaning that in most cases
these answers are not appearing in any paragraphs. We solve this by extending the MKQA
answers with plausible "answer candidates", being slight perturbations or translations
of the answer.
With the contexts extracted, we translated these to Danish, Swedish and Norwegian using
the [DeepL translation service](https://www.deepl.com/pro-api?cta=header-pro-api) for
Danish and Swedish, and the [Google Translation
service](https://cloud.google.com/translate/docs/reference/rest/) for Norwegian. After
translation we ensured that the Scandinavian answers do indeed occur in the translated
contexts.
As we are filtering the MKQA samples at both the "merging stage" and the "translation
stage", we are not able to fully convert the 10,000 samples to the Scandinavian
languages, and instead get roughly 8,000 samples per language. These have further been
split into a training, validation and test split, with the latter two containing
roughly 750 samples. The splits have been created in such a way that the proportion of
samples without an answer is roughly the same in each split.
### Supported Tasks and Leaderboards
Training machine learning models for extractive question answering is the intended task
for this dataset. No leaderboard is active at this point.
### Languages
The dataset is available in Danish (`da`), Swedish (`sv`) and Norwegian (`no`).
## Dataset Structure
### Data Instances
- **Size of downloaded dataset files:** 69 MB
- **Size of the generated dataset:** 67 MB
- **Total amount of disk used:** 136 MB
An example from the `train` split of the `da` subset looks as follows.
```
{
'example_id': 123,
'question': 'Er dette en test?',
'answer': 'Dette er en test',
'answer_start': 0,
'context': 'Dette er en testkontekst.',
'answer_en': 'This is a test',
'answer_start_en': 0,
'context_en': "This is a test context.",
'title_en': 'Train test'
}
```
### Data Fields
The data fields are the same among all splits.
- `example_id`: an `int64` feature.
- `question`: a `string` feature.
- `answer`: a `string` feature.
- `answer_start`: an `int64` feature.
- `context`: a `string` feature.
- `answer_en`: a `string` feature.
- `answer_start_en`: an `int64` feature.
- `context_en`: a `string` feature.
- `title_en`: a `string` feature.
### Data Splits
| name | train | validation | test |
|----------|------:|-----------:|-----:|
| da | 6311 | 749 | 750 |
| sv | 6299 | 750 | 749 |
| no | 6314 | 749 | 750 |
## Dataset Creation
### Curation Rationale
The Scandinavian languages does not have any gold standard question answering dataset.
This is not quite gold standard, but the fact both the questions and answers are all
manually translated, it is a solid silver standard dataset.
### Source Data
The original data was collected from the [MKQA](https://github.com/apple/ml-mkqa/) and
[Natural Questions](https://ai.google.com/research/NaturalQuestions) datasets from
Apple and Google, respectively.
## Additional Information
### Dataset Curators
[Dan Saattrup Nielsen](https://saattrupdan.github.io/) from the [The Alexandra
Institute](https://alexandra.dk/) curated this dataset.
### Licensing Information
The dataset is licensed under the [CC BY-SA 4.0
license](https://creativecommons.org/licenses/by-sa/4.0/).
|
automated-research-group/llama2_7b_chat-hellaswag_0_label-results | ---
dataset_info:
- config_name: '{''do_sample''=False, ''beams''=1}'
features:
- name: id
dtype: string
- name: prediction
dtype: string
- name: hellaswag_accuracy
dtype: bool
splits:
- name: train
num_bytes: 958459
num_examples: 10042
download_size: 234627
dataset_size: 958459
- config_name: '{''do_sample''=False, ''beams''=5}'
features:
- name: id
dtype: string
- name: prediction
dtype: string
- name: hellaswag_accuracy
dtype: bool
splits:
- name: train
num_bytes: 958459
num_examples: 10042
download_size: 234627
dataset_size: 958459
configs:
- config_name: '{''do_sample''=False, ''beams''=1}'
data_files:
- split: train
path: '{''do_sample''=False, ''beams''=1}/train-*'
- config_name: '{''do_sample''=False, ''beams''=5}'
data_files:
- split: train
path: '{''do_sample''=False, ''beams''=5}/train-*'
---
|
projecte-aina/catalan_general_crawling | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- ca
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Catalan General Crawling
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- fill-mask
task_ids: []
---
# Dataset Card for Catalan General Crawling
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** https://zenodo.org/record/5483031
- **Paper:** [Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan](https://arxiv.org/abs/2107.07903)
- **Point of Contact:** langtech@bsc.es
### Dataset Summary
The Catalan General Crawling Corpus is a 435-million-token web corpus of Catalan built from the web. It has been obtained by crawling the 500 most popular .cat and .ad domains during July 2020. It consists of 434,817,705 tokens, 19,451,691 sentences and 1,016,114 documents. Documents are separated by single new lines. It is a subcorpus of the Catalan Textual Corpus.
This work is licensed under a [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/) license.
### Supported Tasks and Leaderboards
This corpus is mainly intended to pretrain language models and word representations.
### Languages
The dataset is in Catalan (`ca-ES`).
## Dataset Structure
### Data Instances
```
{
'text': 'Reduïu els costos dels processos administratius al vostre organisme públic\nEviteu els desplaçaments i pèrdua de temps als ciutadans en les seves gestions\nOferiu una administració més transparent a
ciutadans i empreses\nEns grans i petits experimenten aquesta transformació amb èxit, gràcies al suport de l\'AOC\nDepartament de Sistemes d\'Informació i Processos\n" Via Oberta ens ha permès fer efectiu el d
ret dels ciutadans a no aportar documents, eliminant paper i simplificant procediments"\n" e.FACT proporciona informació indispensable per a la realització de les auditories del registre comptable de factures d
e les Administracions Públiques Catalanes"\nCoordinador del departament d\'Informàtica\n"El servei VIA OBERTA és el que ha aportat majors avantatges per als ciutadans"\n"Amb l\' e-NOTUM hem escurçat els procedi
ments en 12 dies, quasi un 40% menys!"\nCoordinadora d\'organització de persones i e-administració\n" Via Oberta ofereix millores per als ciutadans al no haver d\'aportar cap document"\nResponsable d\'Informàti
ca i Administració Electrònica\n" e-TRAM ens ha permès implantar un servei de tramitació electrònica per als ciutadans de forma ràpida, senzilla i amb un cost reduït"\n"Els municipis amb pocs habitants trobem e
n els serveis de l\'AOC la gratuïtat i la comoditat necessàries per dur a terme el nostre dia a dia"\n"Les T-CAT han permès incorporar de forma segura la signatura electrònica dins dels nostres procediments afa
vorint la transformació digital de la nostra activitat"\nCap de Departament de Sistemes i Tecnologies de la Informació\n"Amb el desplegament de l\' idCAT hem apropat l\'Ajuntament a la ciutadania"\n"Mitjançant
els serveis de Govern Obert de l\'AOC hem pogut fer fàcil el que sembla difícil"\n"Al tauler electrònic pots penjar fins i tot el projecte sencer i al final et permet fer també la diligència"\nÀrea de Promoció
Econòmica, Administració i Hisenda\n"El Sobre Digital i la PSCP han aconseguit una comunió senzilla entre empreses i administració per universalitzar la compra pública electrònica"\n"L\' e-SET és la implantació
d\'un nou sistema de treball que facilita la feina del dia a dia"\nCap del servei de contractació i compres\n"El Sobre Digital, una experiència imprescindible per a la bona administració amb estalvi de recurso
s i millora de la seguretat jurídica i la transparència"\nÀrea d\'Organització i Administració Electrònica\n"El desplegament de la valisa electrònica ha estat clau en el procés de transformació digital dels nos
tres procediments interns"\n"L\' Hèstia permet el treball en temps real i des de qualsevol lloc, així com sistematitzar la pràctica professional, recollir la informació ordenadament i amb el mateix llenguatge"\
nConsulta els materials del Congrés de Govern Digital 2019\nGoverns transparents, fluids, dinàmics, líquids... un bon lema pel principal objectiu de la governança del segle XXI: democratitzar-ho tot.\nConfluènc
ies, rius, cooperació.\nCatalunya, Mediterrània, mar de drets.\nA favor: totes les Administracions movent-se per posar-se al dia i millorar, tot aprofitant la revolució digital.\nEn contra: quants cops estem re
inventant la roda i quantes quantes oportunitats perdudes de fer-ho una única vegada i de forma coordinada i col·laborativa?\n"La transparència és una oportunitat.\nHem de perdre tota por a explicar què fem": l
a conclusió de la taula d\'alcaldies de la Jornada de Govern Obert pic.twitter.com/ERbgLSIXZM\nEl director general de Participació Ciutadana ens convida a transformar les administracions públiques a partir de l
a participació ciutadana\nEns cal que allò que preocupa i ocupa els governants formi part d\'allò en què participa la ciutadania pic.twitter.com/NwQr4EZSCS: "A moltes institucions encara els sona xinés això de
les dades obertes i la transparència.\nDe que serveix que hi hagi un portal, si llavors no hi ha dades?\nLlavors l\'accés a la informació pels periodistes és molt parcial".\nOferim eines que, conjuntament amb l
a metodologia i el suport necessari, fan possible l\'assoliment d\'un govern digital\nPosem al vostre abast tot el coneixement: formació, guies, normatives, etc.\nTenim eines per gestionar àgilment part del pro
cés administratiu del vostre ens\nEl nostre equip farà tot el possible per resoldre les vostres incidències\nSabem que es tracta d\'una decisió molt important per al vostre ens i és per això que us ho volem pos
ar fàcil.\nLa selecció de l\'actualitat d\'Administració Oberta a la vostra safata.'
}
```
### Data Fields
- `text` (str): Text.
### Data Splits
The dataset contains a single split: `train`.
## Dataset Creation
### Curation Rationale
We created this corpus to contribute to the development of language models in Catalan, a low-resource language.
### Source Data
#### Initial Data Collection and Normalization
The corpus has been obtained by crawling the 500 most popular .cat and .ad domains during July 2020.
For preprocessing we used [Corpus-Cleaner](https://github.com/TeMU-BSC/corpus-cleaner-acl), a modular Python-based toolkit to clean raw text corpora through generator pipelines.
#### Who are the source language producers?
The data comes from multiple web pages in Catalan.
### Annotations
The dataset is unannotated.
#### Annotation process
[N/A]
#### Who are the annotators?
[N/A]
### Personal and Sensitive Information
Since all data comes from public websites, no anonymisation process was performed.
## Considerations for Using the Data
### Social Impact of Dataset
We hope this corpus contributes to the development of language models in Catalan, a low-resource language.
### Discussion of Biases
We are aware that since the data comes from unreliable web pages, some biases may be present in the dataset. Nonetheless, we have not applied any steps to reduce their impact.
### Other Known Limitations
[N/A]
## Additional Information
### Dataset Curators
Text Mining Unit (TeMU) at the Barcelona Supercomputing Center (bsc-temu@bsc.es)
This work was funded by the [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).
### Licensing Information
This work is licensed under a [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/) license.
### Citation Information
```
@inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
author = "Armengol-Estap{\'e}, Jordi and
Carrino, Casimiro Pio and
Rodriguez-Penagos, Carlos and
de Gibert Bonet, Ona and
Armentano-Oller, Carme and
Gonzalez-Agirre, Aitor and
Melero, Maite and
Villegas, Marta",
booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.findings-acl.437",
doi = "10.18653/v1/2021.findings-acl.437",
pages = "4933--4946",
eprint={2107.07903},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
### Contributions
Thanks to [@albertvillanova](https://github.com/albertvillanova) for adding this dataset.
|
zedfum/long-summarization-persian | ---
task_categories:
- summarization
language:
- fa
size_categories:
- 10K<n<100K
dataset_info:
features:
- name: 'Unnamed: 0'
dtype: int64
- name: id
dtype: string
- name: article
dtype: string
- name: summary
dtype: string
splits:
- name: train
num_bytes: 2678493527.0838547
num_examples: 49478
- name: test
num_bytes: 148817225.9580726
num_examples: 2749
- name: validation
num_bytes: 148817225.9580726
num_examples: 2749
download_size: 1456639377
dataset_size: 2976127979
tags:
- persian
- فارسی
---
# Dataset Card for Long-Summarization-Persian
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This dataset was created by crawling all categories of ensani.ir
### Supported Tasks and Leaderboards
This dataset can use in Text Summarization Tasks.
### Languages
Persian language
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
id , summary , article
### 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] |
Ales21/Workss | ---
license: openrail
pretty_name: model_for_all_44
size_categories:
- 1K<n<10K
--- |
NotFenixio/meower-dataset | ---
license: apache-2.0
---
|
RescueCat1100/Mikumo-Guynemer | ---
license: mit
---
## RAW DATA
TODO: Parse image in reasonable format |
sankarip/blue_berry_data | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype: image
splits:
- name: train
num_bytes: 21411958.0
num_examples: 91
- name: validation
num_bytes: 2339871.0
num_examples: 10
download_size: 23697580
dataset_size: 23751829.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
---
|
amir7d0/laion2B-fa-images | ---
dataset_info:
features:
- name: SAMPLE_ID
dtype: int64
- name: TEXT
dtype: string
- name: URL
dtype: string
- name: IMAGE_PATH
dtype: string
- name: IMAGE
dtype: image
splits:
- name: train
num_bytes: 21488547.0
num_examples: 1000
download_size: 21283656
dataset_size: 21488547.0
---
# Dataset Card for "laion2B-fa-images"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
sharren/processedSkin | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': akiec
'1': bcc
'2': bkl
'3': df
'4': mel
'5': nv
'6': vasc
splits:
- name: train
num_bytes: 343480940.704
num_examples: 5128
- name: validation
num_bytes: 196512624.876
num_examples: 2884
- name: test
num_bytes: 135696277.958
num_examples: 2003
download_size: 666159202
dataset_size: 675689843.5379999
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
|
open-llm-leaderboard/details_louisbrulenaudet__Pearl-7B-0211-ties | ---
pretty_name: Evaluation run of louisbrulenaudet/Pearl-7B-0211-ties
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [louisbrulenaudet/Pearl-7B-0211-ties](https://huggingface.co/louisbrulenaudet/Pearl-7B-0211-ties)\
\ 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_louisbrulenaudet__Pearl-7B-0211-ties\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-02-11T17:47:26.168272](https://huggingface.co/datasets/open-llm-leaderboard/details_louisbrulenaudet__Pearl-7B-0211-ties/blob/main/results_2024-02-11T17-47-26.168272.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\": 0.6456432854764532,\n\
\ \"acc_stderr\": 0.03218918772125075,\n \"acc_norm\": 0.644583259854297,\n\
\ \"acc_norm_stderr\": 0.03286610473883484,\n \"mc1\": 0.5593635250917993,\n\
\ \"mc1_stderr\": 0.017379697555437446,\n \"mc2\": 0.7146037286866871,\n\
\ \"mc2_stderr\": 0.01481600451729246\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6868600682593856,\n \"acc_stderr\": 0.013552671543623494,\n\
\ \"acc_norm\": 0.7141638225255973,\n \"acc_norm_stderr\": 0.013203196088537377\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7193786098386775,\n\
\ \"acc_stderr\": 0.004483845735187828,\n \"acc_norm\": 0.888568014339773,\n\
\ \"acc_norm_stderr\": 0.0031402323925687962\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695236,\n \
\ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695236\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\": 0.7171052631578947,\n \"acc_stderr\": 0.03665349695640767,\n\
\ \"acc_norm\": 0.7171052631578947,\n \"acc_norm_stderr\": 0.03665349695640767\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.61,\n\
\ \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.61,\n \
\ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.7018867924528301,\n \"acc_stderr\": 0.028152837942493857,\n\
\ \"acc_norm\": 0.7018867924528301,\n \"acc_norm_stderr\": 0.028152837942493857\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\": 0.47,\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\": 0.53,\n \"acc_stderr\": 0.05016135580465919,\n \"acc_norm\"\
: 0.53,\n \"acc_norm_stderr\": 0.05016135580465919\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \
\ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6416184971098265,\n\
\ \"acc_stderr\": 0.036563436533531585,\n \"acc_norm\": 0.6416184971098265,\n\
\ \"acc_norm_stderr\": 0.036563436533531585\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.39215686274509803,\n \"acc_stderr\": 0.04858083574266344,\n\
\ \"acc_norm\": 0.39215686274509803,\n \"acc_norm_stderr\": 0.04858083574266344\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.76,\n \"acc_stderr\": 0.04292346959909283,\n \"acc_norm\": 0.76,\n\
\ \"acc_norm_stderr\": 0.04292346959909283\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.574468085106383,\n \"acc_stderr\": 0.03232146916224468,\n\
\ \"acc_norm\": 0.574468085106383,\n \"acc_norm_stderr\": 0.03232146916224468\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5087719298245614,\n\
\ \"acc_stderr\": 0.04702880432049615,\n \"acc_norm\": 0.5087719298245614,\n\
\ \"acc_norm_stderr\": 0.04702880432049615\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5241379310344828,\n \"acc_stderr\": 0.0416180850350153,\n\
\ \"acc_norm\": 0.5241379310344828,\n \"acc_norm_stderr\": 0.0416180850350153\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.40476190476190477,\n \"acc_stderr\": 0.025279850397404904,\n \"\
acc_norm\": 0.40476190476190477,\n \"acc_norm_stderr\": 0.025279850397404904\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.46825396825396826,\n\
\ \"acc_stderr\": 0.04463112720677171,\n \"acc_norm\": 0.46825396825396826,\n\
\ \"acc_norm_stderr\": 0.04463112720677171\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252604,\n \
\ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252604\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7677419354838709,\n\
\ \"acc_stderr\": 0.024022256130308235,\n \"acc_norm\": 0.7677419354838709,\n\
\ \"acc_norm_stderr\": 0.024022256130308235\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.5024630541871922,\n \"acc_stderr\": 0.035179450386910616,\n\
\ \"acc_norm\": 0.5024630541871922,\n \"acc_norm_stderr\": 0.035179450386910616\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.68,\n \"acc_stderr\": 0.04688261722621505,\n \"acc_norm\"\
: 0.68,\n \"acc_norm_stderr\": 0.04688261722621505\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.7636363636363637,\n \"acc_stderr\": 0.03317505930009182,\n\
\ \"acc_norm\": 0.7636363636363637,\n \"acc_norm_stderr\": 0.03317505930009182\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.7929292929292929,\n \"acc_stderr\": 0.028869778460267045,\n \"\
acc_norm\": 0.7929292929292929,\n \"acc_norm_stderr\": 0.028869778460267045\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.9015544041450777,\n \"acc_stderr\": 0.021500249576033484,\n\
\ \"acc_norm\": 0.9015544041450777,\n \"acc_norm_stderr\": 0.021500249576033484\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6564102564102564,\n \"acc_stderr\": 0.024078696580635477,\n\
\ \"acc_norm\": 0.6564102564102564,\n \"acc_norm_stderr\": 0.024078696580635477\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.32592592592592595,\n \"acc_stderr\": 0.02857834836547308,\n \
\ \"acc_norm\": 0.32592592592592595,\n \"acc_norm_stderr\": 0.02857834836547308\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.6638655462184874,\n \"acc_stderr\": 0.03068473711513537,\n \
\ \"acc_norm\": 0.6638655462184874,\n \"acc_norm_stderr\": 0.03068473711513537\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\"\
: 0.8293577981651377,\n \"acc_stderr\": 0.016129271025099867,\n \"\
acc_norm\": 0.8293577981651377,\n \"acc_norm_stderr\": 0.016129271025099867\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.46296296296296297,\n \"acc_stderr\": 0.03400603625538272,\n \"\
acc_norm\": 0.46296296296296297,\n \"acc_norm_stderr\": 0.03400603625538272\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.8382352941176471,\n \"acc_stderr\": 0.025845017986926917,\n \"\
acc_norm\": 0.8382352941176471,\n \"acc_norm_stderr\": 0.025845017986926917\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.7932489451476793,\n \"acc_stderr\": 0.026361651668389094,\n \
\ \"acc_norm\": 0.7932489451476793,\n \"acc_norm_stderr\": 0.026361651668389094\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\": 0.7633587786259542,\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\":\
\ 0.7603305785123967,\n \"acc_stderr\": 0.03896878985070416,\n \"\
acc_norm\": 0.7603305785123967,\n \"acc_norm_stderr\": 0.03896878985070416\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7962962962962963,\n\
\ \"acc_stderr\": 0.03893542518824847,\n \"acc_norm\": 0.7962962962962963,\n\
\ \"acc_norm_stderr\": 0.03893542518824847\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.7668711656441718,\n \"acc_stderr\": 0.03322015795776741,\n\
\ \"acc_norm\": 0.7668711656441718,\n \"acc_norm_stderr\": 0.03322015795776741\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.45535714285714285,\n\
\ \"acc_stderr\": 0.047268355537191,\n \"acc_norm\": 0.45535714285714285,\n\
\ \"acc_norm_stderr\": 0.047268355537191\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.7669902912621359,\n \"acc_stderr\": 0.04185832598928315,\n\
\ \"acc_norm\": 0.7669902912621359,\n \"acc_norm_stderr\": 0.04185832598928315\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8717948717948718,\n\
\ \"acc_stderr\": 0.021901905115073325,\n \"acc_norm\": 0.8717948717948718,\n\
\ \"acc_norm_stderr\": 0.021901905115073325\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.72,\n \"acc_stderr\": 0.04512608598542128,\n \
\ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.04512608598542128\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8212005108556832,\n\
\ \"acc_stderr\": 0.013702643715368983,\n \"acc_norm\": 0.8212005108556832,\n\
\ \"acc_norm_stderr\": 0.013702643715368983\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7485549132947977,\n \"acc_stderr\": 0.02335736578587403,\n\
\ \"acc_norm\": 0.7485549132947977,\n \"acc_norm_stderr\": 0.02335736578587403\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\": 0.6993464052287581,\n \"acc_stderr\": 0.026256053835718964,\n\
\ \"acc_norm\": 0.6993464052287581,\n \"acc_norm_stderr\": 0.026256053835718964\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\": 0.7191358024691358,\n \"acc_stderr\": 0.02500646975579921,\n\
\ \"acc_norm\": 0.7191358024691358,\n \"acc_norm_stderr\": 0.02500646975579921\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.46808510638297873,\n \"acc_stderr\": 0.029766675075873862,\n \
\ \"acc_norm\": 0.46808510638297873,\n \"acc_norm_stderr\": 0.029766675075873862\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4667535853976532,\n\
\ \"acc_stderr\": 0.012741974333897229,\n \"acc_norm\": 0.4667535853976532,\n\
\ \"acc_norm_stderr\": 0.012741974333897229\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6654411764705882,\n \"acc_stderr\": 0.028661996202335303,\n\
\ \"acc_norm\": 0.6654411764705882,\n \"acc_norm_stderr\": 0.028661996202335303\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6683006535947712,\n \"acc_stderr\": 0.019047485239360378,\n \
\ \"acc_norm\": 0.6683006535947712,\n \"acc_norm_stderr\": 0.019047485239360378\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\": 0.7142857142857143,\n \"acc_stderr\": 0.0289205832206756,\n\
\ \"acc_norm\": 0.7142857142857143,\n \"acc_norm_stderr\": 0.0289205832206756\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8258706467661692,\n\
\ \"acc_stderr\": 0.026814951200421603,\n \"acc_norm\": 0.8258706467661692,\n\
\ \"acc_norm_stderr\": 0.026814951200421603\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.87,\n \"acc_stderr\": 0.03379976689896308,\n \
\ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.03379976689896308\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\": 0.5593635250917993,\n\
\ \"mc1_stderr\": 0.017379697555437446,\n \"mc2\": 0.7146037286866871,\n\
\ \"mc2_stderr\": 0.01481600451729246\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8437253354380426,\n \"acc_stderr\": 0.010205351791873502\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.7065959059893859,\n \
\ \"acc_stderr\": 0.012541830815461492\n }\n}\n```"
repo_url: https://huggingface.co/louisbrulenaudet/Pearl-7B-0211-ties
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|arc:challenge|25_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|gsm8k|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hellaswag|10_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-02-11T17-47-26.168272.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-management|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-virology|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|truthfulqa:mc|0_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-02-11T17-47-26.168272.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- '**/details_harness|winogrande|5_2024-02-11T17-47-26.168272.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-02-11T17-47-26.168272.parquet'
- config_name: results
data_files:
- split: 2024_02_11T17_47_26.168272
path:
- results_2024-02-11T17-47-26.168272.parquet
- split: latest
path:
- results_2024-02-11T17-47-26.168272.parquet
---
# Dataset Card for Evaluation run of louisbrulenaudet/Pearl-7B-0211-ties
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [louisbrulenaudet/Pearl-7B-0211-ties](https://huggingface.co/louisbrulenaudet/Pearl-7B-0211-ties) 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_louisbrulenaudet__Pearl-7B-0211-ties",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-02-11T17:47:26.168272](https://huggingface.co/datasets/open-llm-leaderboard/details_louisbrulenaudet__Pearl-7B-0211-ties/blob/main/results_2024-02-11T17-47-26.168272.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": 0.6456432854764532,
"acc_stderr": 0.03218918772125075,
"acc_norm": 0.644583259854297,
"acc_norm_stderr": 0.03286610473883484,
"mc1": 0.5593635250917993,
"mc1_stderr": 0.017379697555437446,
"mc2": 0.7146037286866871,
"mc2_stderr": 0.01481600451729246
},
"harness|arc:challenge|25": {
"acc": 0.6868600682593856,
"acc_stderr": 0.013552671543623494,
"acc_norm": 0.7141638225255973,
"acc_norm_stderr": 0.013203196088537377
},
"harness|hellaswag|10": {
"acc": 0.7193786098386775,
"acc_stderr": 0.004483845735187828,
"acc_norm": 0.888568014339773,
"acc_norm_stderr": 0.0031402323925687962
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.34,
"acc_stderr": 0.04760952285695236,
"acc_norm": 0.34,
"acc_norm_stderr": 0.04760952285695236
},
"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": 0.7171052631578947,
"acc_stderr": 0.03665349695640767,
"acc_norm": 0.7171052631578947,
"acc_norm_stderr": 0.03665349695640767
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.61,
"acc_stderr": 0.04902071300001975,
"acc_norm": 0.61,
"acc_norm_stderr": 0.04902071300001975
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.7018867924528301,
"acc_stderr": 0.028152837942493857,
"acc_norm": 0.7018867924528301,
"acc_norm_stderr": 0.028152837942493857
},
"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": 0.47,
"acc_stderr": 0.050161355804659205,
"acc_norm": 0.47,
"acc_norm_stderr": 0.050161355804659205
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.53,
"acc_stderr": 0.05016135580465919,
"acc_norm": 0.53,
"acc_norm_stderr": 0.05016135580465919
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.3,
"acc_stderr": 0.046056618647183814,
"acc_norm": 0.3,
"acc_norm_stderr": 0.046056618647183814
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.6416184971098265,
"acc_stderr": 0.036563436533531585,
"acc_norm": 0.6416184971098265,
"acc_norm_stderr": 0.036563436533531585
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.39215686274509803,
"acc_stderr": 0.04858083574266344,
"acc_norm": 0.39215686274509803,
"acc_norm_stderr": 0.04858083574266344
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.76,
"acc_stderr": 0.04292346959909283,
"acc_norm": 0.76,
"acc_norm_stderr": 0.04292346959909283
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.574468085106383,
"acc_stderr": 0.03232146916224468,
"acc_norm": 0.574468085106383,
"acc_norm_stderr": 0.03232146916224468
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.5087719298245614,
"acc_stderr": 0.04702880432049615,
"acc_norm": 0.5087719298245614,
"acc_norm_stderr": 0.04702880432049615
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.5241379310344828,
"acc_stderr": 0.0416180850350153,
"acc_norm": 0.5241379310344828,
"acc_norm_stderr": 0.0416180850350153
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.40476190476190477,
"acc_stderr": 0.025279850397404904,
"acc_norm": 0.40476190476190477,
"acc_norm_stderr": 0.025279850397404904
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.46825396825396826,
"acc_stderr": 0.04463112720677171,
"acc_norm": 0.46825396825396826,
"acc_norm_stderr": 0.04463112720677171
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.33,
"acc_stderr": 0.04725815626252604,
"acc_norm": 0.33,
"acc_norm_stderr": 0.04725815626252604
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.7677419354838709,
"acc_stderr": 0.024022256130308235,
"acc_norm": 0.7677419354838709,
"acc_norm_stderr": 0.024022256130308235
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.5024630541871922,
"acc_stderr": 0.035179450386910616,
"acc_norm": 0.5024630541871922,
"acc_norm_stderr": 0.035179450386910616
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.68,
"acc_stderr": 0.04688261722621505,
"acc_norm": 0.68,
"acc_norm_stderr": 0.04688261722621505
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.7636363636363637,
"acc_stderr": 0.03317505930009182,
"acc_norm": 0.7636363636363637,
"acc_norm_stderr": 0.03317505930009182
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.7929292929292929,
"acc_stderr": 0.028869778460267045,
"acc_norm": 0.7929292929292929,
"acc_norm_stderr": 0.028869778460267045
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.9015544041450777,
"acc_stderr": 0.021500249576033484,
"acc_norm": 0.9015544041450777,
"acc_norm_stderr": 0.021500249576033484
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.6564102564102564,
"acc_stderr": 0.024078696580635477,
"acc_norm": 0.6564102564102564,
"acc_norm_stderr": 0.024078696580635477
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.32592592592592595,
"acc_stderr": 0.02857834836547308,
"acc_norm": 0.32592592592592595,
"acc_norm_stderr": 0.02857834836547308
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.6638655462184874,
"acc_stderr": 0.03068473711513537,
"acc_norm": 0.6638655462184874,
"acc_norm_stderr": 0.03068473711513537
},
"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": 0.8293577981651377,
"acc_stderr": 0.016129271025099867,
"acc_norm": 0.8293577981651377,
"acc_norm_stderr": 0.016129271025099867
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.46296296296296297,
"acc_stderr": 0.03400603625538272,
"acc_norm": 0.46296296296296297,
"acc_norm_stderr": 0.03400603625538272
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.8382352941176471,
"acc_stderr": 0.025845017986926917,
"acc_norm": 0.8382352941176471,
"acc_norm_stderr": 0.025845017986926917
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.7932489451476793,
"acc_stderr": 0.026361651668389094,
"acc_norm": 0.7932489451476793,
"acc_norm_stderr": 0.026361651668389094
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.6816143497757847,
"acc_stderr": 0.03126580522513713,
"acc_norm": 0.6816143497757847,
"acc_norm_stderr": 0.03126580522513713
},
"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": 0.7603305785123967,
"acc_stderr": 0.03896878985070416,
"acc_norm": 0.7603305785123967,
"acc_norm_stderr": 0.03896878985070416
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.7962962962962963,
"acc_stderr": 0.03893542518824847,
"acc_norm": 0.7962962962962963,
"acc_norm_stderr": 0.03893542518824847
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.7668711656441718,
"acc_stderr": 0.03322015795776741,
"acc_norm": 0.7668711656441718,
"acc_norm_stderr": 0.03322015795776741
},
"harness|hendrycksTest-machine_learning|5": {
"acc": 0.45535714285714285,
"acc_stderr": 0.047268355537191,
"acc_norm": 0.45535714285714285,
"acc_norm_stderr": 0.047268355537191
},
"harness|hendrycksTest-management|5": {
"acc": 0.7669902912621359,
"acc_stderr": 0.04185832598928315,
"acc_norm": 0.7669902912621359,
"acc_norm_stderr": 0.04185832598928315
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.8717948717948718,
"acc_stderr": 0.021901905115073325,
"acc_norm": 0.8717948717948718,
"acc_norm_stderr": 0.021901905115073325
},
"harness|hendrycksTest-medical_genetics|5": {
"acc": 0.72,
"acc_stderr": 0.04512608598542128,
"acc_norm": 0.72,
"acc_norm_stderr": 0.04512608598542128
},
"harness|hendrycksTest-miscellaneous|5": {
"acc": 0.8212005108556832,
"acc_stderr": 0.013702643715368983,
"acc_norm": 0.8212005108556832,
"acc_norm_stderr": 0.013702643715368983
},
"harness|hendrycksTest-moral_disputes|5": {
"acc": 0.7485549132947977,
"acc_stderr": 0.02335736578587403,
"acc_norm": 0.7485549132947977,
"acc_norm_stderr": 0.02335736578587403
},
"harness|hendrycksTest-moral_scenarios|5": {
"acc": 0.42681564245810055,
"acc_stderr": 0.016542401954631917,
"acc_norm": 0.42681564245810055,
"acc_norm_stderr": 0.016542401954631917
},
"harness|hendrycksTest-nutrition|5": {
"acc": 0.6993464052287581,
"acc_stderr": 0.026256053835718964,
"acc_norm": 0.6993464052287581,
"acc_norm_stderr": 0.026256053835718964
},
"harness|hendrycksTest-philosophy|5": {
"acc": 0.7170418006430869,
"acc_stderr": 0.02558306248998481,
"acc_norm": 0.7170418006430869,
"acc_norm_stderr": 0.02558306248998481
},
"harness|hendrycksTest-prehistory|5": {
"acc": 0.7191358024691358,
"acc_stderr": 0.02500646975579921,
"acc_norm": 0.7191358024691358,
"acc_norm_stderr": 0.02500646975579921
},
"harness|hendrycksTest-professional_accounting|5": {
"acc": 0.46808510638297873,
"acc_stderr": 0.029766675075873862,
"acc_norm": 0.46808510638297873,
"acc_norm_stderr": 0.029766675075873862
},
"harness|hendrycksTest-professional_law|5": {
"acc": 0.4667535853976532,
"acc_stderr": 0.012741974333897229,
"acc_norm": 0.4667535853976532,
"acc_norm_stderr": 0.012741974333897229
},
"harness|hendrycksTest-professional_medicine|5": {
"acc": 0.6654411764705882,
"acc_stderr": 0.028661996202335303,
"acc_norm": 0.6654411764705882,
"acc_norm_stderr": 0.028661996202335303
},
"harness|hendrycksTest-professional_psychology|5": {
"acc": 0.6683006535947712,
"acc_stderr": 0.019047485239360378,
"acc_norm": 0.6683006535947712,
"acc_norm_stderr": 0.019047485239360378
},
"harness|hendrycksTest-public_relations|5": {
"acc": 0.6727272727272727,
"acc_stderr": 0.0449429086625209,
"acc_norm": 0.6727272727272727,
"acc_norm_stderr": 0.0449429086625209
},
"harness|hendrycksTest-security_studies|5": {
"acc": 0.7142857142857143,
"acc_stderr": 0.0289205832206756,
"acc_norm": 0.7142857142857143,
"acc_norm_stderr": 0.0289205832206756
},
"harness|hendrycksTest-sociology|5": {
"acc": 0.8258706467661692,
"acc_stderr": 0.026814951200421603,
"acc_norm": 0.8258706467661692,
"acc_norm_stderr": 0.026814951200421603
},
"harness|hendrycksTest-us_foreign_policy|5": {
"acc": 0.87,
"acc_stderr": 0.03379976689896308,
"acc_norm": 0.87,
"acc_norm_stderr": 0.03379976689896308
},
"harness|hendrycksTest-virology|5": {
"acc": 0.5421686746987951,
"acc_stderr": 0.0387862677100236,
"acc_norm": 0.5421686746987951,
"acc_norm_stderr": 0.0387862677100236
},
"harness|hendrycksTest-world_religions|5": {
"acc": 0.8362573099415205,
"acc_stderr": 0.028380919596145866,
"acc_norm": 0.8362573099415205,
"acc_norm_stderr": 0.028380919596145866
},
"harness|truthfulqa:mc|0": {
"mc1": 0.5593635250917993,
"mc1_stderr": 0.017379697555437446,
"mc2": 0.7146037286866871,
"mc2_stderr": 0.01481600451729246
},
"harness|winogrande|5": {
"acc": 0.8437253354380426,
"acc_stderr": 0.010205351791873502
},
"harness|gsm8k|5": {
"acc": 0.7065959059893859,
"acc_stderr": 0.012541830815461492
}
}
```
## 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. -->
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iulia-elisa/AstroArtefactToolkit_XMMoptical | ---
source_datasets:
- original
pretty_name: AstroArtefactToolkit_XMMoptical
size_categories:
- 1K<N<10K
tags:
- COCO format
- Astronomy
- XMM-Newton
task_categories:
- image-segmentation
task_ids:
- instance-segmentation
configs:
- config_name: default
data_files:
- split: train
path: data/train-00000-of-00001.parquet
- split: valid
path: data/valid-00000-of-00001.parquet
- split: test
path: data/test-00000-of-00001.parquet
---
# AstroArtefactToolkit_XMMoptical
The XMM-Newton Optical Monitor (OM) image catalogue is a valuable resource contain-
ing approximately 9 million detections of around 6 million distinct sources observed over the
mission baseline. The OM catalogue plays a pivotal role in individual object analyses and
contributes significantly to survey science, including the construction of luminosity functions.
One aspect of the OM data analysis contributing to the catalogue that necessitates en-
hancing is the process of source flagging. The presence of various artefacts in OM images
poses challenges, potentially leading to false detections or affecting the photometric preci-
sion of genuine sources. Artefacts in XMM-OM images can emerge due to light scattering
within the detector.
The dataset is splited into train/validation/test categories and contains annotated artefacts in COCO format for Instance Segmentation. The dataset can be downloaded following this script:
```python
from huggingface_hub import hf_hub_download
import pandas as pd
train_parquet = "data/train-00000-of-00001.parquet"
valid_parquet = "data/valid-00000-of-00001.parquet"
test_parquet = "data/test-00000-of-00001.parquet"
# example of downlaoding train split
train_dataset = pd.read_parquet(
hf_hub_download(
repo_id="iulia-elisa/AstroArtefactToolkit_XMMoptical",
filename=train_parquet,
repo_type="dataset")
)
```
## Licence |
arieg/bw_spec_cls_80_29 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': '67784'
'1': '67793'
'2': '67829'
'3': '68353'
'4': '68354'
'5': '68355'
'6': '68356'
'7': '68407'
'8': '68410'
'9': '68444'
'10': '68531'
'11': '68539'
'12': '68540'
'13': '68541'
'14': '68543'
'15': '68549'
'16': '68573'
'17': '68579'
'18': '68592'
'19': '68600'
'20': '68601'
'21': '68680'
'22': '68682'
'23': '68683'
'24': '68820'
'25': '68821'
'26': '68837'
'27': '68838'
'28': '68839'
'29': '68840'
'30': '68841'
'31': '68842'
'32': '68843'
'33': '68844'
'34': '68851'
'35': '68852'
'36': '68853'
'37': '68854'
'38': '68860'
'39': '68861'
'40': '68862'
'41': '68869'
'42': '68872'
'43': '68875'
'44': '69001'
'45': '69002'
'46': '69170'
'47': '69181'
'48': '69182'
'49': '69188'
'50': '69193'
'51': '69195'
'52': '69196'
'53': '69197'
'54': '69198'
'55': '69199'
'56': '69200'
'57': '69201'
'58': '69202'
'59': '69203'
'60': '69204'
'61': '69205'
'62': '69206'
'63': '69207'
'64': '69208'
'65': '69209'
'66': '69210'
'67': '69211'
'68': '69554'
'69': '69555'
'70': '69561'
'71': '69563'
'72': '69564'
'73': '69567'
'74': '69682'
'75': '69723'
'76': '69726'
'77': '69727'
'78': '69732'
'79': '69744'
splits:
- name: train
num_bytes: 88025524.8
num_examples: 1600
- name: test
num_bytes: 21927703.0
num_examples: 400
download_size: 109110671
dataset_size: 109953227.8
---
# Dataset Card for "bw_spec_cls_80_29"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
datawealthy/logo-classification | ---
license: cc-by-sa-4.0
---
|
vollerei-id/anime | ---
license: cc-by-nc-4.0
---
|
aimsks/satellite-coral-mapping | ---
dataset_info:
features:
- name: label
dtype: image
- name: Coral-Sea_S2_R2
dtype: image
- name: Coral-Sea_L8_R1
dtype: image
- name: Coral-Sea_S2_R1
dtype: image
splits:
- name: training
num_bytes: 13963277.0
num_examples: 15
- name: test
num_bytes: 16455480.0
num_examples: 18
download_size: 30431394
dataset_size: 30418757.0
---
# Dataset Card for "satellite-coral-mapping"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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