Datasets:
davanstrien
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summary-test

Dataset card Data Studio Files
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AlekseyKorshuk/crowdsource-v2.0
--- dataset_info: features: - name: bot_id dtype: string - name: conversation_id dtype: string - name: conversation list: - name: content dtype: string - name: do_train dtype: bool - name: role dtype: string - name: bot_config struct: - name: bot_label dtype: string - name: description dtype: string - name: developer_uid dtype: string - name: first_message dtype: string - name: image_url dtype: string - name: introduction dtype: string - name: max_history dtype: int64 - name: memory dtype: string - name: model dtype: string - name: name dtype: string - name: prompt dtype: string - name: repetition_penalty dtype: float64 - name: response_length dtype: int64 - name: temperature dtype: float64 - name: theme dtype: 'null' - name: top_k dtype: int64 - name: top_p dtype: float64 - name: user_label dtype: string - name: conversation_history dtype: string - name: system dtype: string - name: text dtype: string splits: - name: train num_bytes: 106588734 num_examples: 19541 download_size: 65719430 dataset_size: 106588734 --- # Dataset Card for "crowdsource-v2.0" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
HangenYuu/gutenberg-english-train
--- dataset_info: features: - name: input_ids sequence: int32 - name: ratio_char_token dtype: float64 splits: - name: train num_bytes: 21730024796 num_examples: 48284 download_size: 0 dataset_size: 21730024796 --- # Dataset Card for "gutenberg-english-train" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
hfaus/CelebA_bbox_and_facepoints
--- size_categories: - n<1K --- # CelebA Dataset CelebA Dataset is a large-scale face attributes dataset with more than 200K celebrity images, each with 40 attribute annotations. The images in this dataset cover large pose variations and background clutter. CelebA has large diversities, large quantities, and rich annotations, including 10,177 number of identities, 202,599 number of face images, and 5 landmark locations, 40 binary attributes annotations per image. ## Usage It is composed of 3 sets of images: * Training * Validation * Test ## Example The dataset returns each item as a dictionary with the following fields: ``` { "image": image, "bbox": [x1, y1, w, h], "facial_landmarks": { "lefteye": [x1, y1], "righteye": [x2, y2], "nose": [x3, y3], "leftmouth": [x4, y4], "rightmouth": [x5, y5] } } ``` ## License CelebA Dataset is licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).
zicsx/indic-align-hindi
--- dataset_info: features: - name: interactions sequence: sequence: string - name: num_turns dtype: int64 splits: - name: train num_bytes: 12940934287 num_examples: 13310858 download_size: 2105451389 dataset_size: 12940934287 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "indic-align-hindi" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
FanChen0116/bus_few4_50x
--- dataset_info: features: - name: id dtype: int64 - name: tokens sequence: string - name: labels sequence: class_label: names: '0': O '1': I-from_location '2': B-from_location '3': B-leaving_date '4': I-leaving_date '5': I-to_location '6': B-to_location - name: request_slot sequence: string splits: - name: train num_bytes: 677514 num_examples: 3500 - name: validation num_bytes: 6900 num_examples: 35 - name: test num_bytes: 70618 num_examples: 377 download_size: 0 dataset_size: 755032 --- # Dataset Card for "bus_few4_50x" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
NX2411/mydataset-only-test
--- license: apache-2.0 ---
OzoneAsai/wikibooks
--- license: wtfpl ---
nlpso/m1_qualitative_analysis_ref_ptrn_cmbert_iob2
--- language: - fr multilinguality: - monolingual task_categories: - token-classification --- # m1_qualitative_analysis_ref_ptrn_cmbert_iob2 ## Introduction This dataset was used to perform **qualitative analysis** of [HueyNemud/das22-10-camembert_pretrained](https://huggingface.co/HueyNemud/das22-10-camembert_pretrained) on **nested NER task** using Independant NER layers approach [M1]. It contains Paris trade directories entries from the 19th century. ## Dataset parameters * Approach : M1 * Dataset type : ground-truth * Tokenizer : [HueyNemud/das22-10-camembert_pretrained](https://huggingface.co/HueyNemud/das22-10-camembert_pretrained) * Tagging format : IOB2 * Counts : * Train : 6084 * Dev : 676 * Test : 1685 * Associated fine-tuned models : * Level-1 : [nlpso/m1_ind_layers_ref_ptrn_cmbert_iob2_level_1](https://huggingface.co/nlpso/m1_ind_layers_ref_ptrn_cmbert_iob2_level_1) * Level 2 : [nlpso/m1_ind_layers_ref_ptrn_cmbert_iob2_level_2](https://huggingface.co/nlpso/m1_ind_layers_ref_ptrn_cmbert_iob2_level_2) ## Entity types Abbreviation|Entity group (level)|Description -|-|- O |1 & 2|Outside of a named entity PER |1|Person or company name ACT |1 & 2|Person or company professional activity TITREH |2|Military or civil distinction DESC |1|Entry full description TITREP |2|Professionnal reward SPAT |1|Address LOC |2|Street name CARDINAL |2|Street number FT |2|Geographical feature ## How to use this dataset ```python from datasets import load_dataset train_dev_test = load_dataset("nlpso/m1_qualitative_analysis_ref_ptrn_cmbert_iob2")
griffin/chain_of_density
--- dataset_info: - config_name: annotated features: - name: article dtype: string - name: highlights dtype: string - name: id dtype: string - name: prediction sequence: string - name: missing sequence: string - name: model dtype: string - name: annotations sequence: int64 - name: num_tokens sequence: int64 - name: num_entities sequence: int64 - name: fusion sequence: float64 - name: entity_density sequence: float64 - name: inverse_lead_bias sequence: float64 - name: extractive_density sequence: float64 - name: extractive_coverage sequence: float64 - name: unique_unigrams sequence: float64 - name: unique_bigrams sequence: float64 - name: unique_trigrams sequence: float64 - name: rouge1 sequence: float64 - name: rouge2 sequence: float64 - name: rougeL sequence: float64 - name: rougeLsum sequence: float64 - name: gpt4_informative sequence: float64 - name: gpt4_quality sequence: float64 - name: gpt4_attributable sequence: float64 - name: gpt4_coherence sequence: float64 - name: gpt4_overall sequence: float64 splits: - name: test num_bytes: 750471 num_examples: 100 download_size: 452599 dataset_size: 750471 - config_name: unannotated features: - name: article dtype: string - name: highlights dtype: string - name: id dtype: string - name: prediction sequence: string - name: missing sequence: string - name: model dtype: string - name: num_tokens sequence: int64 - name: num_entities sequence: int64 - name: fusion sequence: float64 - name: entity_density sequence: float64 - name: inverse_lead_bias sequence: float64 - name: extractive_density sequence: float64 - name: extractive_coverage sequence: float64 - name: unique_unigrams sequence: float64 - name: unique_bigrams sequence: float64 - name: unique_trigrams sequence: float64 - name: rouge1 sequence: float64 - name: rouge2 sequence: float64 - name: rougeL sequence: float64 - name: rougeLsum sequence: float64 splits: - name: train num_bytes: 6948744 num_examples: 1000 download_size: 3719092 dataset_size: 6948744 configs: - config_name: annotated data_files: - split: test path: annotated/test-* - config_name: unannotated data_files: - split: train path: unannotated/train-* --- # Dataset Card for "chain_of_density" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
anilguven/turkish_tweet_emotion_dataset
--- license: unknown task_categories: - text-classification language: - tr tags: - tweet - turkish - sentiment - emotion size_categories: - 1K<n<10K --- ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** @INPROCEEDINGS{8946435, author={Güven, Zekeriya Anıl and Diri, Banu and Çakaloğlu, Tolgahan}, booktitle={2019 Innovations in Intelligent Systems and Applications Conference (ASYU)}, title={Comparison Method for Emotion Detection of Twitter Users}, year={2019}, volume={}, number={}, pages={1-5}, keywords={Twitter;Resource management;Machine learning algorithms;Computer science;Media;Advertising;Topic Modelling;Latent Dirichlet Allocation;Natural Language Processing;Emotion Detection;Sentiment Analysis;Machine Learning}, doi={10.1109/ASYU48272.2019.8946435}} **APA:** Güven, Z. A., Diri, B., & Çakaloğlu, T. (2019, October). Comparison Method for Emotion Detection of Twitter Users. In 2019 Innovations in Intelligent Systems and Applications Conference (ASYU) (pp. 1-5). IEEE.
KayEe/flipkart_sentiment_analysis
--- language: - en pretty_name: sa configs: - config_name: default data_files: - split: train path: "train.json" - split: test path: "test.json" default: true ---
AdapterOcean/med_alpaca_standardized_cluster_54_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: 12656152 num_examples: 21288 download_size: 6558110 dataset_size: 12656152 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "med_alpaca_standardized_cluster_54_std" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Treza12/all_dataset
--- license: apache-2.0 ---
benayas/banking_llm_v4
--- dataset_info: features: - name: text dtype: string - name: category dtype: string splits: - name: train num_bytes: 21973867 num_examples: 10003 - name: test num_bytes: 6745410 num_examples: 3080 download_size: 2573335 dataset_size: 28719277 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
PNLPhub/C-ExaPPC
--- license: mit ---
Isotonic/open-instruct-v1
--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: text dtype: string splits: - name: train num_bytes: 693502500.8465096 num_examples: 399050 - name: test num_bytes: 173376494.1534904 num_examples: 99763 download_size: 369952246 dataset_size: 866878995.0 task_categories: - text-generation - conversational language: - en size_categories: - 100K<n<1M --- # Dataset Card for "open-instruct-v1" Open Instruct V1 is an amalgamation of different datasets which are cleaned and then collated into a singular format for training. Uses Stability AI's System Prompt. ``` ### System: StableLM Tuned (Alpha version) - StableLM is a helpful and harmless open-source AI language model developed by StabilityAI. - StableLM is excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user. - StableLM is more than just an information source, StableLM is also able to write poetry, short stories, and make jokes. - StableLM will refuse to participate in anything that could harm a human. ``` ## Dataset Breakdown | Dataset | Amount of Samples | |----------------|-------------------| | [Alpaca](https://github.com/tatsu-lab/stanford_alpaca) | 51759 | | [Self Instruct](https://github.com/yizhongw/self-instruct) | 82599 | | [GPT-4 Instruct](https://github.com/teknium1/GPTeacher) | 18194 | | [Code Alpaca](https://huggingface.co/datasets/HuggingFaceH4/CodeAlpaca_20K) | 18019 | | [Dolly](https://huggingface.co/datasets/HuggingFaceH4/databricks_dolly_15k) | 15015 | | [Synthetic](https://huggingface.co/datasets/Dahoas/synthetic-instruct-gptj-pairwise) | 33143 | | [Roleplay](https://github.com/teknium1/GPTeacher) | 3146 | | [asss](https://huggingface.co/datasets/HuggingFaceH4/asss) | 448 | | [instruction-dataset](https://huggingface.co/datasets/HuggingFaceH4/instruction-dataset) | 327 | | [Human assistant deduped](https://huggingface.co/datasets/Isotonic/human_assistant_conversation_deduped) | 209350 | Total | 432000 |
open-llm-leaderboard/details_openthaigpt__openthaigpt-1.0.0-beta-13b-chat-hf
--- pretty_name: Evaluation run of openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf](https://huggingface.co/openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf)\ \ 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 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the 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_openthaigpt__openthaigpt-1.0.0-beta-13b-chat-hf\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-29T13:17:24.378047](https://huggingface.co/datasets/open-llm-leaderboard/details_openthaigpt__openthaigpt-1.0.0-beta-13b-chat-hf/blob/main/results_2023-12-29T13-17-24.378047.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\": 0.5079906839832642,\n\ \ \"acc_stderr\": 0.03424315613001413,\n \"acc_norm\": 0.516456403503363,\n\ \ \"acc_norm_stderr\": 0.03513746029855274,\n \"mc1\": 0.2802937576499388,\n\ \ \"mc1_stderr\": 0.015723139524608763,\n \"mc2\": 0.4416133249202012,\n\ \ \"mc2_stderr\": 0.01548425276508773\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.4974402730375427,\n \"acc_stderr\": 0.014611199329843784,\n\ \ \"acc_norm\": 0.5358361774744027,\n \"acc_norm_stderr\": 0.01457381366473572\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5986855208125871,\n\ \ \"acc_stderr\": 0.004891626718097025,\n \"acc_norm\": 0.7908783110934077,\n\ \ \"acc_norm_stderr\": 0.0040585031572305955\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252605,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252605\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.45185185185185184,\n\ \ \"acc_stderr\": 0.04299268905480864,\n \"acc_norm\": 0.45185185185185184,\n\ \ \"acc_norm_stderr\": 0.04299268905480864\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.45394736842105265,\n \"acc_stderr\": 0.04051646342874143,\n\ \ \"acc_norm\": 0.45394736842105265,\n \"acc_norm_stderr\": 0.04051646342874143\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.52,\n\ \ \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.52,\n \ \ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.5320754716981132,\n \"acc_stderr\": 0.03070948699255655,\n\ \ \"acc_norm\": 0.5320754716981132,\n \"acc_norm_stderr\": 0.03070948699255655\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5694444444444444,\n\ \ \"acc_stderr\": 0.04140685639111503,\n \"acc_norm\": 0.5694444444444444,\n\ \ \"acc_norm_stderr\": 0.04140685639111503\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \ \ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\ acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \"acc_norm\"\ : 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n },\n \"harness|hendrycksTest-college_mathematics|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-college_medicine|5\": {\n \"acc\": 0.49710982658959535,\n\ \ \"acc_stderr\": 0.038124005659748335,\n \"acc_norm\": 0.49710982658959535,\n\ \ \"acc_norm_stderr\": 0.038124005659748335\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3235294117647059,\n \"acc_stderr\": 0.046550104113196177,\n\ \ \"acc_norm\": 0.3235294117647059,\n \"acc_norm_stderr\": 0.046550104113196177\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.64,\n \"acc_stderr\": 0.048241815132442176,\n \"acc_norm\": 0.64,\n\ \ \"acc_norm_stderr\": 0.048241815132442176\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.4425531914893617,\n \"acc_stderr\": 0.03246956919789958,\n\ \ \"acc_norm\": 0.4425531914893617,\n \"acc_norm_stderr\": 0.03246956919789958\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.30701754385964913,\n\ \ \"acc_stderr\": 0.0433913832257986,\n \"acc_norm\": 0.30701754385964913,\n\ \ \"acc_norm_stderr\": 0.0433913832257986\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.46206896551724136,\n \"acc_stderr\": 0.041546596717075474,\n\ \ \"acc_norm\": 0.46206896551724136,\n \"acc_norm_stderr\": 0.041546596717075474\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.30687830687830686,\n \"acc_stderr\": 0.023752928712112143,\n \"\ acc_norm\": 0.30687830687830686,\n \"acc_norm_stderr\": 0.023752928712112143\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.29365079365079366,\n\ \ \"acc_stderr\": 0.040735243221471255,\n \"acc_norm\": 0.29365079365079366,\n\ \ \"acc_norm_stderr\": 0.040735243221471255\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.6,\n\ \ \"acc_stderr\": 0.027869320571664632,\n \"acc_norm\": 0.6,\n \ \ \"acc_norm_stderr\": 0.027869320571664632\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.4187192118226601,\n \"acc_stderr\": 0.034711928605184676,\n\ \ \"acc_norm\": 0.4187192118226601,\n \"acc_norm_stderr\": 0.034711928605184676\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \"acc_norm\"\ : 0.5,\n \"acc_norm_stderr\": 0.050251890762960605\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.6363636363636364,\n \"acc_stderr\": 0.03756335775187897,\n\ \ \"acc_norm\": 0.6363636363636364,\n \"acc_norm_stderr\": 0.03756335775187897\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.6464646464646465,\n \"acc_stderr\": 0.03406086723547155,\n \"\ acc_norm\": 0.6464646464646465,\n \"acc_norm_stderr\": 0.03406086723547155\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.7046632124352331,\n \"acc_stderr\": 0.032922966391551414,\n\ \ \"acc_norm\": 0.7046632124352331,\n \"acc_norm_stderr\": 0.032922966391551414\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.4794871794871795,\n \"acc_stderr\": 0.025329663163489943,\n\ \ \"acc_norm\": 0.4794871794871795,\n \"acc_norm_stderr\": 0.025329663163489943\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.2851851851851852,\n \"acc_stderr\": 0.027528599210340496,\n \ \ \"acc_norm\": 0.2851851851851852,\n \"acc_norm_stderr\": 0.027528599210340496\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.5042016806722689,\n \"acc_stderr\": 0.03247734334448111,\n \ \ \"acc_norm\": 0.5042016806722689,\n \"acc_norm_stderr\": 0.03247734334448111\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.31125827814569534,\n \"acc_stderr\": 0.03780445850526733,\n \"\ acc_norm\": 0.31125827814569534,\n \"acc_norm_stderr\": 0.03780445850526733\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.6642201834862386,\n \"acc_stderr\": 0.020248081396752923,\n \"\ acc_norm\": 0.6642201834862386,\n \"acc_norm_stderr\": 0.020248081396752923\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.33796296296296297,\n \"acc_stderr\": 0.03225941352631295,\n \"\ acc_norm\": 0.33796296296296297,\n \"acc_norm_stderr\": 0.03225941352631295\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.6470588235294118,\n \"acc_stderr\": 0.03354092437591519,\n \"\ acc_norm\": 0.6470588235294118,\n \"acc_norm_stderr\": 0.03354092437591519\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.679324894514768,\n \"acc_stderr\": 0.030381931949990407,\n \ \ \"acc_norm\": 0.679324894514768,\n \"acc_norm_stderr\": 0.030381931949990407\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6098654708520179,\n\ \ \"acc_stderr\": 0.03273766725459157,\n \"acc_norm\": 0.6098654708520179,\n\ \ \"acc_norm_stderr\": 0.03273766725459157\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.5725190839694656,\n \"acc_stderr\": 0.043389203057924,\n\ \ \"acc_norm\": 0.5725190839694656,\n \"acc_norm_stderr\": 0.043389203057924\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7024793388429752,\n \"acc_stderr\": 0.04173349148083499,\n \"\ acc_norm\": 0.7024793388429752,\n \"acc_norm_stderr\": 0.04173349148083499\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.6203703703703703,\n\ \ \"acc_stderr\": 0.04691521224077742,\n \"acc_norm\": 0.6203703703703703,\n\ \ \"acc_norm_stderr\": 0.04691521224077742\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.5766871165644172,\n \"acc_stderr\": 0.038818912133343826,\n\ \ \"acc_norm\": 0.5766871165644172,\n \"acc_norm_stderr\": 0.038818912133343826\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\": 0.6893203883495146,\n \"acc_stderr\": 0.04582124160161549,\n\ \ \"acc_norm\": 0.6893203883495146,\n \"acc_norm_stderr\": 0.04582124160161549\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7564102564102564,\n\ \ \"acc_stderr\": 0.028120966503914407,\n \"acc_norm\": 0.7564102564102564,\n\ \ \"acc_norm_stderr\": 0.028120966503914407\n },\n \"harness|hendrycksTest-medical_genetics|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-miscellaneous|5\": {\n \"acc\": 0.6896551724137931,\n\ \ \"acc_stderr\": 0.016543785026048304,\n \"acc_norm\": 0.6896551724137931,\n\ \ \"acc_norm_stderr\": 0.016543785026048304\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6011560693641619,\n \"acc_stderr\": 0.026362437574546545,\n\ \ \"acc_norm\": 0.6011560693641619,\n \"acc_norm_stderr\": 0.026362437574546545\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.3687150837988827,\n\ \ \"acc_stderr\": 0.016135759015030122,\n \"acc_norm\": 0.3687150837988827,\n\ \ \"acc_norm_stderr\": 0.016135759015030122\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.6013071895424836,\n \"acc_stderr\": 0.028036092273891765,\n\ \ \"acc_norm\": 0.6013071895424836,\n \"acc_norm_stderr\": 0.028036092273891765\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.5980707395498392,\n\ \ \"acc_stderr\": 0.027846476005930473,\n \"acc_norm\": 0.5980707395498392,\n\ \ \"acc_norm_stderr\": 0.027846476005930473\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.5709876543209876,\n \"acc_stderr\": 0.027538925613470863,\n\ \ \"acc_norm\": 0.5709876543209876,\n \"acc_norm_stderr\": 0.027538925613470863\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.36879432624113473,\n \"acc_stderr\": 0.028782227561347237,\n \ \ \"acc_norm\": 0.36879432624113473,\n \"acc_norm_stderr\": 0.028782227561347237\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3878748370273794,\n\ \ \"acc_stderr\": 0.012444998309675617,\n \"acc_norm\": 0.3878748370273794,\n\ \ \"acc_norm_stderr\": 0.012444998309675617\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.3897058823529412,\n \"acc_stderr\": 0.0296246635811597,\n\ \ \"acc_norm\": 0.3897058823529412,\n \"acc_norm_stderr\": 0.0296246635811597\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.4820261437908497,\n \"acc_stderr\": 0.020214761037872408,\n \ \ \"acc_norm\": 0.4820261437908497,\n \"acc_norm_stderr\": 0.020214761037872408\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6,\n\ \ \"acc_stderr\": 0.0469237132203465,\n \"acc_norm\": 0.6,\n \ \ \"acc_norm_stderr\": 0.0469237132203465\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.5877551020408164,\n \"acc_stderr\": 0.03151236044674268,\n\ \ \"acc_norm\": 0.5877551020408164,\n \"acc_norm_stderr\": 0.03151236044674268\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.6467661691542289,\n\ \ \"acc_stderr\": 0.03379790611796777,\n \"acc_norm\": 0.6467661691542289,\n\ \ \"acc_norm_stderr\": 0.03379790611796777\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.71,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.71,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.41566265060240964,\n\ \ \"acc_stderr\": 0.03836722176598052,\n \"acc_norm\": 0.41566265060240964,\n\ \ \"acc_norm_stderr\": 0.03836722176598052\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.7426900584795322,\n \"acc_stderr\": 0.03352799844161865,\n\ \ \"acc_norm\": 0.7426900584795322,\n \"acc_norm_stderr\": 0.03352799844161865\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2802937576499388,\n\ \ \"mc1_stderr\": 0.015723139524608763,\n \"mc2\": 0.4416133249202012,\n\ \ \"mc2_stderr\": 0.01548425276508773\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7387529597474349,\n \"acc_stderr\": 0.01234691486341531\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.008339651250947688,\n \ \ \"acc_stderr\": 0.002504942226860527\n }\n}\n```" repo_url: https://huggingface.co/openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|arc:challenge|25_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|arc:challenge|25_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-29T13-17-24.378047.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|gsm8k|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|gsm8k|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hellaswag|10_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hellaswag|10_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-27T14-26-13.560554.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-29T13-17-24.378047.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-management|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-management|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T13-17-24.378047.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|truthfulqa:mc|0_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|truthfulqa:mc|0_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-29T13-17-24.378047.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_27T14_26_13.560554 path: - '**/details_harness|winogrande|5_2023-12-27T14-26-13.560554.parquet' - split: 2023_12_29T13_17_24.378047 path: - '**/details_harness|winogrande|5_2023-12-29T13-17-24.378047.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-29T13-17-24.378047.parquet' - config_name: results data_files: - split: 2023_12_27T14_26_13.560554 path: - results_2023-12-27T14-26-13.560554.parquet - split: 2023_12_29T13_17_24.378047 path: - results_2023-12-29T13-17-24.378047.parquet - split: latest path: - results_2023-12-29T13-17-24.378047.parquet --- # Dataset Card for Evaluation run of openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf](https://huggingface.co/openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf) 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 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the 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_openthaigpt__openthaigpt-1.0.0-beta-13b-chat-hf", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-29T13:17:24.378047](https://huggingface.co/datasets/open-llm-leaderboard/details_openthaigpt__openthaigpt-1.0.0-beta-13b-chat-hf/blob/main/results_2023-12-29T13-17-24.378047.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": 0.5079906839832642, "acc_stderr": 0.03424315613001413, "acc_norm": 0.516456403503363, "acc_norm_stderr": 0.03513746029855274, "mc1": 0.2802937576499388, "mc1_stderr": 0.015723139524608763, "mc2": 0.4416133249202012, "mc2_stderr": 0.01548425276508773 }, "harness|arc:challenge|25": { "acc": 0.4974402730375427, "acc_stderr": 0.014611199329843784, "acc_norm": 0.5358361774744027, "acc_norm_stderr": 0.01457381366473572 }, "harness|hellaswag|10": { "acc": 0.5986855208125871, "acc_stderr": 0.004891626718097025, "acc_norm": 0.7908783110934077, "acc_norm_stderr": 0.0040585031572305955 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.45185185185185184, "acc_stderr": 0.04299268905480864, "acc_norm": 0.45185185185185184, "acc_norm_stderr": 0.04299268905480864 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.45394736842105265, "acc_stderr": 0.04051646342874143, "acc_norm": 0.45394736842105265, "acc_norm_stderr": 0.04051646342874143 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5320754716981132, "acc_stderr": 0.03070948699255655, "acc_norm": 0.5320754716981132, "acc_norm_stderr": 0.03070948699255655 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5694444444444444, "acc_stderr": 0.04140685639111503, "acc_norm": 0.5694444444444444, "acc_norm_stderr": 0.04140685639111503 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.49710982658959535, "acc_stderr": 0.038124005659748335, "acc_norm": 0.49710982658959535, "acc_norm_stderr": 0.038124005659748335 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3235294117647059, "acc_stderr": 0.046550104113196177, "acc_norm": 0.3235294117647059, "acc_norm_stderr": 0.046550104113196177 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.64, "acc_stderr": 0.048241815132442176, "acc_norm": 0.64, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4425531914893617, "acc_stderr": 0.03246956919789958, "acc_norm": 0.4425531914893617, "acc_norm_stderr": 0.03246956919789958 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.30701754385964913, "acc_stderr": 0.0433913832257986, "acc_norm": 0.30701754385964913, "acc_norm_stderr": 0.0433913832257986 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.46206896551724136, "acc_stderr": 0.041546596717075474, "acc_norm": 0.46206896551724136, "acc_norm_stderr": 0.041546596717075474 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.30687830687830686, "acc_stderr": 0.023752928712112143, "acc_norm": 0.30687830687830686, "acc_norm_stderr": 0.023752928712112143 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.29365079365079366, "acc_stderr": 0.040735243221471255, "acc_norm": 0.29365079365079366, "acc_norm_stderr": 0.040735243221471255 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6, "acc_stderr": 0.027869320571664632, "acc_norm": 0.6, "acc_norm_stderr": 0.027869320571664632 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4187192118226601, "acc_stderr": 0.034711928605184676, "acc_norm": 0.4187192118226601, "acc_norm_stderr": 0.034711928605184676 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6363636363636364, "acc_stderr": 0.03756335775187897, "acc_norm": 0.6363636363636364, "acc_norm_stderr": 0.03756335775187897 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6464646464646465, "acc_stderr": 0.03406086723547155, "acc_norm": 0.6464646464646465, "acc_norm_stderr": 0.03406086723547155 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7046632124352331, "acc_stderr": 0.032922966391551414, "acc_norm": 0.7046632124352331, "acc_norm_stderr": 0.032922966391551414 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4794871794871795, "acc_stderr": 0.025329663163489943, "acc_norm": 0.4794871794871795, "acc_norm_stderr": 0.025329663163489943 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2851851851851852, "acc_stderr": 0.027528599210340496, "acc_norm": 0.2851851851851852, "acc_norm_stderr": 0.027528599210340496 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.5042016806722689, "acc_stderr": 0.03247734334448111, "acc_norm": 0.5042016806722689, "acc_norm_stderr": 0.03247734334448111 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.31125827814569534, "acc_stderr": 0.03780445850526733, "acc_norm": 0.31125827814569534, "acc_norm_stderr": 0.03780445850526733 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.6642201834862386, "acc_stderr": 0.020248081396752923, "acc_norm": 0.6642201834862386, "acc_norm_stderr": 0.020248081396752923 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.33796296296296297, "acc_stderr": 0.03225941352631295, "acc_norm": 0.33796296296296297, "acc_norm_stderr": 0.03225941352631295 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.6470588235294118, "acc_stderr": 0.03354092437591519, "acc_norm": 0.6470588235294118, "acc_norm_stderr": 0.03354092437591519 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.679324894514768, "acc_stderr": 0.030381931949990407, "acc_norm": 0.679324894514768, "acc_norm_stderr": 0.030381931949990407 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6098654708520179, "acc_stderr": 0.03273766725459157, "acc_norm": 0.6098654708520179, "acc_norm_stderr": 0.03273766725459157 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.5725190839694656, "acc_stderr": 0.043389203057924, "acc_norm": 0.5725190839694656, "acc_norm_stderr": 0.043389203057924 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7024793388429752, "acc_stderr": 0.04173349148083499, "acc_norm": 0.7024793388429752, "acc_norm_stderr": 0.04173349148083499 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.6203703703703703, "acc_stderr": 0.04691521224077742, "acc_norm": 0.6203703703703703, "acc_norm_stderr": 0.04691521224077742 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.5766871165644172, "acc_stderr": 0.038818912133343826, "acc_norm": 0.5766871165644172, "acc_norm_stderr": 0.038818912133343826 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.33035714285714285, "acc_stderr": 0.04464285714285714, "acc_norm": 0.33035714285714285, "acc_norm_stderr": 0.04464285714285714 }, "harness|hendrycksTest-management|5": { "acc": 0.6893203883495146, "acc_stderr": 0.04582124160161549, "acc_norm": 0.6893203883495146, "acc_norm_stderr": 0.04582124160161549 }, "harness|hendrycksTest-marketing|5": { "acc": 0.7564102564102564, "acc_stderr": 0.028120966503914407, "acc_norm": 0.7564102564102564, "acc_norm_stderr": 0.028120966503914407 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.6896551724137931, "acc_stderr": 0.016543785026048304, "acc_norm": 0.6896551724137931, "acc_norm_stderr": 0.016543785026048304 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.6011560693641619, "acc_stderr": 0.026362437574546545, "acc_norm": 0.6011560693641619, "acc_norm_stderr": 0.026362437574546545 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.3687150837988827, "acc_stderr": 0.016135759015030122, "acc_norm": 0.3687150837988827, "acc_norm_stderr": 0.016135759015030122 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.6013071895424836, "acc_stderr": 0.028036092273891765, "acc_norm": 0.6013071895424836, "acc_norm_stderr": 0.028036092273891765 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.5980707395498392, "acc_stderr": 0.027846476005930473, "acc_norm": 0.5980707395498392, "acc_norm_stderr": 0.027846476005930473 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.5709876543209876, "acc_stderr": 0.027538925613470863, "acc_norm": 0.5709876543209876, "acc_norm_stderr": 0.027538925613470863 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.36879432624113473, "acc_stderr": 0.028782227561347237, "acc_norm": 0.36879432624113473, "acc_norm_stderr": 0.028782227561347237 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.3878748370273794, "acc_stderr": 0.012444998309675617, "acc_norm": 0.3878748370273794, "acc_norm_stderr": 0.012444998309675617 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.3897058823529412, "acc_stderr": 0.0296246635811597, "acc_norm": 0.3897058823529412, "acc_norm_stderr": 0.0296246635811597 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.4820261437908497, "acc_stderr": 0.020214761037872408, "acc_norm": 0.4820261437908497, "acc_norm_stderr": 0.020214761037872408 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6, "acc_stderr": 0.0469237132203465, "acc_norm": 0.6, "acc_norm_stderr": 0.0469237132203465 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.5877551020408164, "acc_stderr": 0.03151236044674268, "acc_norm": 0.5877551020408164, "acc_norm_stderr": 0.03151236044674268 }, "harness|hendrycksTest-sociology|5": { "acc": 0.6467661691542289, "acc_stderr": 0.03379790611796777, "acc_norm": 0.6467661691542289, "acc_norm_stderr": 0.03379790611796777 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-virology|5": { "acc": 0.41566265060240964, "acc_stderr": 0.03836722176598052, "acc_norm": 0.41566265060240964, "acc_norm_stderr": 0.03836722176598052 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.7426900584795322, "acc_stderr": 0.03352799844161865, "acc_norm": 0.7426900584795322, "acc_norm_stderr": 0.03352799844161865 }, "harness|truthfulqa:mc|0": { "mc1": 0.2802937576499388, "mc1_stderr": 0.015723139524608763, "mc2": 0.4416133249202012, "mc2_stderr": 0.01548425276508773 }, "harness|winogrande|5": { "acc": 0.7387529597474349, "acc_stderr": 0.01234691486341531 }, "harness|gsm8k|5": { "acc": 0.008339651250947688, "acc_stderr": 0.002504942226860527 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
mboth/waermeErzeugen-100-undersampled
--- 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: Datatype dtype: string - name: Beschreibung dtype: string - name: Name dtype: string - name: Unit dtype: string - name: text dtype: string - name: Grundfunktion dtype: string - name: ZweiteGrundfunktion dtype: string - name: label dtype: class_label: names: '0': BHKW '1': Kessel '2': Pelletkessel '3': Waermepumpe '4': WaermeversorgerAllgemein splits: - name: train num_bytes: 64185.247706422015 num_examples: 359 - name: test num_bytes: 38880 num_examples: 218 - name: valid num_bytes: 38880 num_examples: 218 download_size: 61981 dataset_size: 141945.247706422 --- # Dataset Card for "waermeErzeugen-100-undersampled" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
PY007/slimpajama_llama_tokenized_upsample_4096_chunk_1M
--- dataset_info: features: - name: input_ids sequence: int64 - name: labels dtype: int64 - name: source list: - name: end dtype: int64 - name: source dtype: string - name: start dtype: int64 splits: - name: train num_bytes: 40394155659 num_examples: 5041 download_size: 9203916526 dataset_size: 40394155659 configs: - config_name: default data_files: - split: train path: data/train-* --- Generated using https://github.com/FranxYao/Long-Context-Data-Engineering with the below command: ```bash mkdir logs mkdir data mkdir data/slimpajama mkdir data/slimpajama/per_source_downsample cd data_engineering PATH_TO_SLIMPAJAMA=rokset3/slim_pajama_chunk_1 nohup python -u slimpajama_packing.py\ --dataset_size=100m\ --print_interval=100 --num_process=200\ --chunk_size=1000001 \ --dataset_path=$PATH_TO_SLIMPAJAMA\ --output_path=../data/slimpajama/per_source_downsample/ --down_sample_ratio=0.1 --down_sample_mode=per_source\ > ../logs/slimpajama_packing_dist_per_source_downsample_0.1.log 2>&1 & tail -f ../logs/slimpajama_packing_dist_per_source_downsample_0.1.log ```
tyzhu/squad_instruction_v1_train_100
--- dataset_info: features: - name: inputs dtype: string - name: targets dtype: string - name: question dtype: string - name: context dtype: string - name: answers struct: - name: answer_start sequence: int64 - name: text sequence: string - name: id dtype: string splits: - name: train num_bytes: 177041.73335312048 num_examples: 100 - name: validation num_bytes: 1888548.7582781457 num_examples: 1000 download_size: 1184787 dataset_size: 2065590.4916312662 --- # Dataset Card for "squad_instruction_v1_train_100" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
anakib1/synth-rag
--- dataset_info: - config_name: MWP-ru features: - name: audio dtype: audio - name: theme dtype: string - name: transcription dtype: string - name: summary dtype: string - name: noise dtype: string splits: - name: train num_bytes: 34334807.0 num_examples: 20 download_size: 34328238 dataset_size: 34334807.0 - config_name: concept features: - name: audio dtype: audio - name: theme dtype: string - name: transcription dtype: string splits: - name: train num_bytes: 7900550.0 num_examples: 5 download_size: 6952224 dataset_size: 7900550.0 - config_name: dummy features: - name: audio dtype: audio - name: theme dtype: string - name: transcription dtype: string splits: - name: train num_bytes: 39684356.0 num_examples: 20 download_size: 38522196 dataset_size: 39684356.0 - config_name: working-example features: - name: audio dtype: audio - name: theme dtype: string - name: transcription dtype: string splits: - name: train num_bytes: 104460945.0 num_examples: 51 download_size: 91278093 dataset_size: 104460945.0 configs: - config_name: MWP-ru data_files: - split: train path: MWP-ru/train-* - config_name: concept data_files: - split: train path: concept/train-* - config_name: dummy data_files: - split: train path: dummy/train-* - config_name: working-example data_files: - split: train path: working-example/train-* ---
Nadav/pixel_glue_mrpc_low_noise
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': '0' '1': '1' splits: - name: validation num_bytes: 14592360.0 num_examples: 408 download_size: 14571167 dataset_size: 14592360.0 --- # Dataset Card for "pixel_glue_mrpc_low_noise" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Nexdata/93_Hours_Korean_Children_Real_world_Casual_Conversation_and_Monologue_speech_dataset
--- license: cc-by-nc-nd-4.0 --- ## Description Korean(Korea) Children Real-world Casual Conversation and Monologue speech dataset, covers self-media, conversation, live, lecture, variety show and other generic domains, mirrors real-world interactions. Transcribed with text content, speaker's ID, gender, age, accent and other attributes. Our dataset was collected from extensive and diversify speakers(12 years old and younger children), geographicly speaking, enhancing model performance in real and complex tasks.rnQuality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied. For more details, please refer to the link: https://www.nexdata.ai/dataset/1329?source=Huggingface ## Format 16kHz, 16 bit, wav, mono channel ## Age 12 years old and younger children ## Content category including interview, self-meida,variety show, etc. ## Recording environment Low background noise ## Country South Korea(KOR) ## Language(Region) Code ko-KR ## Language Korean ## Features of annotation Transcription text, timestamp, speaker ID, gender, noise ## Accuracy Word Accuracy Rate (WAR) 98% # Licensing Information Commercial License
nadsoft/Arabic-dialect-2-English
--- dataset_info: features: - name: id dtype: string - name: Arabic dtype: string - name: English dtype: string splits: - name: train num_bytes: 15467913.665420653 num_examples: 16051 - name: test num_bytes: 3867219.3345793462 num_examples: 4013 download_size: 9835505 dataset_size: 19335133.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
open-llm-leaderboard/details_uukuguy__speechless-llama2-hermes-orca-platypus-wizardlm-13b
--- pretty_name: Evaluation run of uukuguy/speechless-llama2-hermes-orca-platypus-wizardlm-13b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [uukuguy/speechless-llama2-hermes-orca-platypus-wizardlm-13b](https://huggingface.co/uukuguy/speechless-llama2-hermes-orca-platypus-wizardlm-13b)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 3 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_uukuguy__speechless-llama2-hermes-orca-platypus-wizardlm-13b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-15T13:11:43.680043](https://huggingface.co/datasets/open-llm-leaderboard/details_uukuguy__speechless-llama2-hermes-orca-platypus-wizardlm-13b/blob/main/results_2023-10-15T13-11-43.680043.json)(note\ \ that their might be results for other tasks in the repos if successive evals didn't\ \ cover the same tasks. You find each in the results and the \"latest\" split for\ \ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.057466442953020135,\n\ \ \"em_stderr\": 0.0023833905882384896,\n \"f1\": 0.17808829697986514,\n\ \ \"f1_stderr\": 0.002972308703760267,\n \"acc\": 0.44245449154575855,\n\ \ \"acc_stderr\": 0.010703432271512695\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.057466442953020135,\n \"em_stderr\": 0.0023833905882384896,\n\ \ \"f1\": 0.17808829697986514,\n \"f1_stderr\": 0.002972308703760267\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.13115996967399546,\n \ \ \"acc_stderr\": 0.009298499235587858\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7537490134175217,\n \"acc_stderr\": 0.012108365307437531\n\ \ }\n}\n```" repo_url: https://huggingface.co/uukuguy/speechless-llama2-hermes-orca-platypus-wizardlm-13b 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_02T00_07_11.850382 path: - '**/details_harness|arc:challenge|25_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-09-02T00:07:11.850382.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_15T13_11_43.680043 path: - '**/details_harness|drop|3_2023-10-15T13-11-43.680043.parquet' - split: latest path: - '**/details_harness|drop|3_2023-10-15T13-11-43.680043.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_15T13_11_43.680043 path: - '**/details_harness|gsm8k|5_2023-10-15T13-11-43.680043.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-10-15T13-11-43.680043.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hellaswag|10_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-02T00:07:11.850382.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-management|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-virology|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-02T00:07:11.850382.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_02T00_07_11.850382 path: - '**/details_harness|truthfulqa:mc|0_2023-09-02T00:07:11.850382.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-09-02T00:07:11.850382.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_15T13_11_43.680043 path: - '**/details_harness|winogrande|5_2023-10-15T13-11-43.680043.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-10-15T13-11-43.680043.parquet' - config_name: results data_files: - split: 2023_09_02T00_07_11.850382 path: - results_2023-09-02T00:07:11.850382.parquet - split: 2023_09_12T15_48_02.156025 path: - results_2023-09-12T15-48-02.156025.parquet - split: 2023_10_15T13_11_43.680043 path: - results_2023-10-15T13-11-43.680043.parquet - split: latest path: - results_2023-10-15T13-11-43.680043.parquet --- # Dataset Card for Evaluation run of uukuguy/speechless-llama2-hermes-orca-platypus-wizardlm-13b ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/uukuguy/speechless-llama2-hermes-orca-platypus-wizardlm-13b - **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 [uukuguy/speechless-llama2-hermes-orca-platypus-wizardlm-13b](https://huggingface.co/uukuguy/speechless-llama2-hermes-orca-platypus-wizardlm-13b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 3 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_uukuguy__speechless-llama2-hermes-orca-platypus-wizardlm-13b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-15T13:11:43.680043](https://huggingface.co/datasets/open-llm-leaderboard/details_uukuguy__speechless-llama2-hermes-orca-platypus-wizardlm-13b/blob/main/results_2023-10-15T13-11-43.680043.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval): ```python { "all": { "em": 0.057466442953020135, "em_stderr": 0.0023833905882384896, "f1": 0.17808829697986514, "f1_stderr": 0.002972308703760267, "acc": 0.44245449154575855, "acc_stderr": 0.010703432271512695 }, "harness|drop|3": { "em": 0.057466442953020135, "em_stderr": 0.0023833905882384896, "f1": 0.17808829697986514, "f1_stderr": 0.002972308703760267 }, "harness|gsm8k|5": { "acc": 0.13115996967399546, "acc_stderr": 0.009298499235587858 }, "harness|winogrande|5": { "acc": 0.7537490134175217, "acc_stderr": 0.012108365307437531 } } ``` ### 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]
open-llm-leaderboard/details_abacusai__Slerp-CM-mist-dpo
--- pretty_name: Evaluation run of abacusai/Slerp-CM-mist-dpo dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [abacusai/Slerp-CM-mist-dpo](https://huggingface.co/abacusai/Slerp-CM-mist-dpo)\ \ 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_abacusai__Slerp-CM-mist-dpo\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-05T00:32:34.951153](https://huggingface.co/datasets/open-llm-leaderboard/details_abacusai__Slerp-CM-mist-dpo/blob/main/results_2024-01-05T00-32-34.951153.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\": 0.6532042094380237,\n\ \ \"acc_stderr\": 0.03203963454702555,\n \"acc_norm\": 0.6527369993047523,\n\ \ \"acc_norm_stderr\": 0.032706226155307466,\n \"mc1\": 0.46511627906976744,\n\ \ \"mc1_stderr\": 0.017460849975873965,\n \"mc2\": 0.6281840008276592,\n\ \ \"mc2_stderr\": 0.01521885509426602\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6715017064846417,\n \"acc_stderr\": 0.013724978465537302,\n\ \ \"acc_norm\": 0.6962457337883959,\n \"acc_norm_stderr\": 0.013438909184778768\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6873132842063334,\n\ \ \"acc_stderr\": 0.004626404491616958,\n \"acc_norm\": 0.8709420434176459,\n\ \ \"acc_norm_stderr\": 0.0033457889052629563\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6518518518518519,\n\ \ \"acc_stderr\": 0.041153246103369526,\n \"acc_norm\": 0.6518518518518519,\n\ \ \"acc_norm_stderr\": 0.041153246103369526\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6776315789473685,\n \"acc_stderr\": 0.03803510248351585,\n\ \ \"acc_norm\": 0.6776315789473685,\n \"acc_norm_stderr\": 0.03803510248351585\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.63,\n\ \ \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\": 0.63,\n \ \ \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.7245283018867924,\n \"acc_stderr\": 0.027495663683724057,\n\ \ \"acc_norm\": 0.7245283018867924,\n \"acc_norm_stderr\": 0.027495663683724057\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7777777777777778,\n\ \ \"acc_stderr\": 0.03476590104304134,\n \"acc_norm\": 0.7777777777777778,\n\ \ \"acc_norm_stderr\": 0.03476590104304134\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.46,\n \"acc_stderr\": 0.05009082659620333,\n \ \ \"acc_norm\": 0.46,\n \"acc_norm_stderr\": 0.05009082659620333\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.53,\n \"acc_stderr\": 0.050161355804659205,\n \"acc_norm\": 0.53,\n\ \ \"acc_norm_stderr\": 0.050161355804659205\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6878612716763006,\n\ \ \"acc_stderr\": 0.035331333893236574,\n \"acc_norm\": 0.6878612716763006,\n\ \ \"acc_norm_stderr\": 0.035331333893236574\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.43137254901960786,\n \"acc_stderr\": 0.04928099597287534,\n\ \ \"acc_norm\": 0.43137254901960786,\n \"acc_norm_stderr\": 0.04928099597287534\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.76,\n \"acc_stderr\": 0.042923469599092816,\n \"acc_norm\": 0.76,\n\ \ \"acc_norm_stderr\": 0.042923469599092816\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5829787234042553,\n \"acc_stderr\": 0.03223276266711712,\n\ \ \"acc_norm\": 0.5829787234042553,\n \"acc_norm_stderr\": 0.03223276266711712\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.47368421052631576,\n\ \ \"acc_stderr\": 0.046970851366478626,\n \"acc_norm\": 0.47368421052631576,\n\ \ \"acc_norm_stderr\": 0.046970851366478626\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5586206896551724,\n \"acc_stderr\": 0.04137931034482757,\n\ \ \"acc_norm\": 0.5586206896551724,\n \"acc_norm_stderr\": 0.04137931034482757\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.41005291005291006,\n \"acc_stderr\": 0.02533120243894444,\n \"\ acc_norm\": 0.41005291005291006,\n \"acc_norm_stderr\": 0.02533120243894444\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.46825396825396826,\n\ \ \"acc_stderr\": 0.04463112720677172,\n \"acc_norm\": 0.46825396825396826,\n\ \ \"acc_norm_stderr\": 0.04463112720677172\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.33,\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\": 0.7870967741935484,\n\ \ \"acc_stderr\": 0.023287665127268545,\n \"acc_norm\": 0.7870967741935484,\n\ \ \"acc_norm_stderr\": 0.023287665127268545\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.4876847290640394,\n \"acc_stderr\": 0.035169204442208966,\n\ \ \"acc_norm\": 0.4876847290640394,\n \"acc_norm_stderr\": 0.035169204442208966\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\": 0.7696969696969697,\n \"acc_stderr\": 0.0328766675860349,\n\ \ \"acc_norm\": 0.7696969696969697,\n \"acc_norm_stderr\": 0.0328766675860349\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\": 0.9067357512953368,\n \"acc_stderr\": 0.02098685459328973,\n\ \ \"acc_norm\": 0.9067357512953368,\n \"acc_norm_stderr\": 0.02098685459328973\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.658974358974359,\n \"acc_stderr\": 0.024035489676335082,\n \ \ \"acc_norm\": 0.658974358974359,\n \"acc_norm_stderr\": 0.024035489676335082\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.35555555555555557,\n \"acc_stderr\": 0.029185714949857416,\n \ \ \"acc_norm\": 0.35555555555555557,\n \"acc_norm_stderr\": 0.029185714949857416\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6764705882352942,\n \"acc_stderr\": 0.03038835355188679,\n \ \ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.03038835355188679\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\"\ : 0.8568807339449541,\n \"acc_stderr\": 0.01501446249716859,\n \"\ acc_norm\": 0.8568807339449541,\n \"acc_norm_stderr\": 0.01501446249716859\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5185185185185185,\n \"acc_stderr\": 0.03407632093854051,\n \"\ acc_norm\": 0.5185185185185185,\n \"acc_norm_stderr\": 0.03407632093854051\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8480392156862745,\n \"acc_stderr\": 0.0251956584289318,\n \"acc_norm\"\ : 0.8480392156862745,\n \"acc_norm_stderr\": 0.0251956584289318\n },\n\ \ \"harness|hendrycksTest-high_school_world_history|5\": {\n \"acc\":\ \ 0.7890295358649789,\n \"acc_stderr\": 0.026558372502661916,\n \"\ acc_norm\": 0.7890295358649789,\n \"acc_norm_stderr\": 0.026558372502661916\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.695067264573991,\n\ \ \"acc_stderr\": 0.030898610882477515,\n \"acc_norm\": 0.695067264573991,\n\ \ \"acc_norm_stderr\": 0.030898610882477515\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7938931297709924,\n \"acc_stderr\": 0.03547771004159465,\n\ \ \"acc_norm\": 0.7938931297709924,\n \"acc_norm_stderr\": 0.03547771004159465\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7933884297520661,\n \"acc_stderr\": 0.03695980128098823,\n \"\ acc_norm\": 0.7933884297520661,\n \"acc_norm_stderr\": 0.03695980128098823\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7870370370370371,\n\ \ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\ \ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7791411042944786,\n \"acc_stderr\": 0.03259177392742178,\n\ \ \"acc_norm\": 0.7791411042944786,\n \"acc_norm_stderr\": 0.03259177392742178\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.44642857142857145,\n\ \ \"acc_stderr\": 0.04718471485219588,\n \"acc_norm\": 0.44642857142857145,\n\ \ \"acc_norm_stderr\": 0.04718471485219588\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7669902912621359,\n \"acc_stderr\": 0.04185832598928315,\n\ \ \"acc_norm\": 0.7669902912621359,\n \"acc_norm_stderr\": 0.04185832598928315\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8803418803418803,\n\ \ \"acc_stderr\": 0.021262719400406957,\n \"acc_norm\": 0.8803418803418803,\n\ \ \"acc_norm_stderr\": 0.021262719400406957\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8263090676883781,\n\ \ \"acc_stderr\": 0.01354741565866226,\n \"acc_norm\": 0.8263090676883781,\n\ \ \"acc_norm_stderr\": 0.01354741565866226\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\": 0.43798882681564244,\n\ \ \"acc_stderr\": 0.016593394227564843,\n \"acc_norm\": 0.43798882681564244,\n\ \ \"acc_norm_stderr\": 0.016593394227564843\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7189542483660131,\n \"acc_stderr\": 0.025738854797818737,\n\ \ \"acc_norm\": 0.7189542483660131,\n \"acc_norm_stderr\": 0.025738854797818737\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7106109324758842,\n\ \ \"acc_stderr\": 0.02575586592263295,\n \"acc_norm\": 0.7106109324758842,\n\ \ \"acc_norm_stderr\": 0.02575586592263295\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7530864197530864,\n \"acc_stderr\": 0.023993501709042107,\n\ \ \"acc_norm\": 0.7530864197530864,\n \"acc_norm_stderr\": 0.023993501709042107\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4787234042553192,\n \"acc_stderr\": 0.029800481645628693,\n \ \ \"acc_norm\": 0.4787234042553192,\n \"acc_norm_stderr\": 0.029800481645628693\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.46740547588005216,\n\ \ \"acc_stderr\": 0.012743072942653349,\n \"acc_norm\": 0.46740547588005216,\n\ \ \"acc_norm_stderr\": 0.012743072942653349\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6764705882352942,\n \"acc_stderr\": 0.028418208619406755,\n\ \ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.028418208619406755\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6715686274509803,\n \"acc_stderr\": 0.018999707383162673,\n \ \ \"acc_norm\": 0.6715686274509803,\n \"acc_norm_stderr\": 0.018999707383162673\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6545454545454545,\n\ \ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\ \ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7387755102040816,\n \"acc_stderr\": 0.028123429335142777,\n\ \ \"acc_norm\": 0.7387755102040816,\n \"acc_norm_stderr\": 0.028123429335142777\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8507462686567164,\n\ \ \"acc_stderr\": 0.025196929874827072,\n \"acc_norm\": 0.8507462686567164,\n\ \ \"acc_norm_stderr\": 0.025196929874827072\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.87,\n \"acc_stderr\": 0.03379976689896309,\n \ \ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.03379976689896309\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5421686746987951,\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\": 0.46511627906976744,\n\ \ \"mc1_stderr\": 0.017460849975873965,\n \"mc2\": 0.6281840008276592,\n\ \ \"mc2_stderr\": 0.01521885509426602\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8145224940805051,\n \"acc_stderr\": 0.010923965303140505\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.7278241091736164,\n \ \ \"acc_stderr\": 0.012259714035164545\n }\n}\n```" repo_url: https://huggingface.co/abacusai/Slerp-CM-mist-dpo leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|arc:challenge|25_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-01-05T00-32-34.951153.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|gsm8k|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hellaswag|10_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-05T00-32-34.951153.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-management|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-virology|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-05T00-32-34.951153.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|truthfulqa:mc|0_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-01-05T00-32-34.951153.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_05T00_32_34.951153 path: - '**/details_harness|winogrande|5_2024-01-05T00-32-34.951153.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-01-05T00-32-34.951153.parquet' - config_name: results data_files: - split: 2024_01_05T00_32_34.951153 path: - results_2024-01-05T00-32-34.951153.parquet - split: latest path: - results_2024-01-05T00-32-34.951153.parquet --- # Dataset Card for Evaluation run of abacusai/Slerp-CM-mist-dpo <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [abacusai/Slerp-CM-mist-dpo](https://huggingface.co/abacusai/Slerp-CM-mist-dpo) 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_abacusai__Slerp-CM-mist-dpo", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-05T00:32:34.951153](https://huggingface.co/datasets/open-llm-leaderboard/details_abacusai__Slerp-CM-mist-dpo/blob/main/results_2024-01-05T00-32-34.951153.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": 0.6532042094380237, "acc_stderr": 0.03203963454702555, "acc_norm": 0.6527369993047523, "acc_norm_stderr": 0.032706226155307466, "mc1": 0.46511627906976744, "mc1_stderr": 0.017460849975873965, "mc2": 0.6281840008276592, "mc2_stderr": 0.01521885509426602 }, "harness|arc:challenge|25": { "acc": 0.6715017064846417, "acc_stderr": 0.013724978465537302, "acc_norm": 0.6962457337883959, "acc_norm_stderr": 0.013438909184778768 }, "harness|hellaswag|10": { "acc": 0.6873132842063334, "acc_stderr": 0.004626404491616958, "acc_norm": 0.8709420434176459, "acc_norm_stderr": 0.0033457889052629563 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6518518518518519, "acc_stderr": 0.041153246103369526, "acc_norm": 0.6518518518518519, "acc_norm_stderr": 0.041153246103369526 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6776315789473685, "acc_stderr": 0.03803510248351585, "acc_norm": 0.6776315789473685, "acc_norm_stderr": 0.03803510248351585 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.63, "acc_stderr": 0.04852365870939099, "acc_norm": 0.63, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7245283018867924, "acc_stderr": 0.027495663683724057, "acc_norm": 0.7245283018867924, "acc_norm_stderr": 0.027495663683724057 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7777777777777778, "acc_stderr": 0.03476590104304134, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.03476590104304134 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.53, "acc_stderr": 0.050161355804659205, "acc_norm": 0.53, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6878612716763006, "acc_stderr": 0.035331333893236574, "acc_norm": 0.6878612716763006, "acc_norm_stderr": 0.035331333893236574 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.43137254901960786, "acc_stderr": 0.04928099597287534, "acc_norm": 0.43137254901960786, "acc_norm_stderr": 0.04928099597287534 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.76, "acc_stderr": 0.042923469599092816, "acc_norm": 0.76, "acc_norm_stderr": 0.042923469599092816 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5829787234042553, "acc_stderr": 0.03223276266711712, "acc_norm": 0.5829787234042553, "acc_norm_stderr": 0.03223276266711712 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.47368421052631576, "acc_stderr": 0.046970851366478626, "acc_norm": 0.47368421052631576, "acc_norm_stderr": 0.046970851366478626 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5586206896551724, "acc_stderr": 0.04137931034482757, "acc_norm": 0.5586206896551724, "acc_norm_stderr": 0.04137931034482757 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.41005291005291006, "acc_stderr": 0.02533120243894444, "acc_norm": 0.41005291005291006, "acc_norm_stderr": 0.02533120243894444 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.46825396825396826, "acc_stderr": 0.04463112720677172, "acc_norm": 0.46825396825396826, "acc_norm_stderr": 0.04463112720677172 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7870967741935484, "acc_stderr": 0.023287665127268545, "acc_norm": 0.7870967741935484, "acc_norm_stderr": 0.023287665127268545 }, 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"mc1": 0.46511627906976744, "mc1_stderr": 0.017460849975873965, "mc2": 0.6281840008276592, "mc2_stderr": 0.01521885509426602 }, "harness|winogrande|5": { "acc": 0.8145224940805051, "acc_stderr": 0.010923965303140505 }, "harness|gsm8k|5": { "acc": 0.7278241091736164, "acc_stderr": 0.012259714035164545 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
KyleLin/Parse-Then-Place
--- license: ms-pl --- This repository provides the datasets and checkpoints for the paper "A Parse-Then-Place Approach for Generating Graphic Layouts from Textual Descriptions". Please see our [paper](https://arxiv.org/abs/2308.12700) and [code](https://github.com/microsoft/LayoutGeneration/).
autoevaluate/autoeval-eval-xglue-mlqa-02a2ef-48376145243
--- type: predictions tags: - autotrain - evaluation datasets: - xglue eval_info: task: summarization model: google/roberta2roberta_L-24_bbc metrics: ['bleu', 'f1', 'accuracy'] dataset_name: xglue dataset_config: mlqa dataset_split: test.ar col_mapping: text: context target: question --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Summarization * Model: google/roberta2roberta_L-24_bbc * Dataset: xglue * Config: mlqa * Split: test.ar To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@Anwaarma](https://huggingface.co/Anwaarma) for evaluating this model.
emea
--- annotations_creators: - found language_creators: - found language: - bg - cs - da - de - el - en - es - et - fi - fr - hu - it - lt - lv - mt - nl - pl - pt - ro - sk - sl - sv license: - unknown multilinguality: - multilingual size_categories: - 1M<n<10M source_datasets: - original task_categories: - translation task_ids: [] paperswithcode_id: null pretty_name: EMEA dataset_info: - config_name: bg-el features: - name: id dtype: string - name: translation dtype: translation: languages: - bg - el splits: - name: train num_bytes: 296160562 num_examples: 1044065 download_size: 54531690 dataset_size: 296160562 - config_name: cs-et features: - name: id dtype: string - name: translation dtype: translation: languages: - cs - et splits: - name: train num_bytes: 180261167 num_examples: 1053164 download_size: 36065651 dataset_size: 180261167 - config_name: de-mt features: - name: id dtype: string - name: translation dtype: translation: languages: - de - mt splits: - name: train num_bytes: 182976918 num_examples: 1000532 download_size: 36665427 dataset_size: 182976918 - config_name: fr-sk features: - name: id dtype: string - name: translation dtype: translation: languages: - fr - sk splits: - name: train num_bytes: 193605247 num_examples: 1062753 download_size: 38916074 dataset_size: 193605247 - config_name: es-lt features: - name: id dtype: string - name: translation dtype: translation: languages: - es - lt splits: - name: train num_bytes: 182623676 num_examples: 1051370 download_size: 35329033 dataset_size: 182623676 config_names: - bg-el - cs-et - de-mt - es-lt - fr-sk --- # Dataset Card for EMEA ## 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:** http://opus.nlpl.eu/EMEA.php - **Repository:** None - **Paper:** http://www.lrec-conf.org/proceedings/lrec2012/pdf/463_Paper.pdf - **Leaderboard:** [More Information Needed] - **Point of Contact:** [More Information Needed] ### Dataset Summary To load a language pair which isn't part of the config, all you need to do is specify the language code as pairs. You can find the valid pairs in Homepage section of Dataset Description: http://opus.nlpl.eu/EMEA.php E.g. `dataset = load_dataset("emea", lang1="en", lang2="nl")` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances Here is an example of the `en-nl` configuration: ``` {'id': '4', 'translation': {'en': 'EPAR summary for the public', 'nl': 'EPAR-samenvatting voor het publiek'}} ``` ### Data Fields The data fields are: - id: id of the sentence pair - translation: a dictionary of the form {lang1: text_in_lang1, lang2: text_in_lang2} ### Data Splits Sizes of some language pairs: | name |train| |----------|----:| |bg-el|1044065| |cs-et|1053164| |de-mt|1000532| |fr-sk|1062753| |es-lt|1051370| ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data [More Information Needed] #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations [More Information Needed] #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information ```bibtex @InProceedings{TIEDEMANN12.463, author = {J{\"o}rg Tiedemann}, title = {Parallel Data, Tools and Interfaces in OPUS}, booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)}, year = {2012}, month = {may}, date = {23-25}, address = {Istanbul, Turkey}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Ugur Dogan and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-7-7}, language = {english} } ``` ### Contributions Thanks to [@abhishekkrthakur](https://github.com/abhishekkrthakur) for adding this dataset.
kblw/ft-images
--- dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 348235189.17 num_examples: 4730 download_size: 127651795 dataset_size: 348235189.17 configs: - config_name: default data_files: - split: train path: data/train-* --- update: use different shapes
Andyrasika/prompt-recommendation
--- dataset_info: features: - name: id dtype: int64 - name: source dtype: string - name: target dtype: string splits: - name: train num_bytes: 64111 num_examples: 100 - name: eval num_bytes: 13427 num_examples: 21 download_size: 18652 dataset_size: 77538 --- # Dataset Card for "prompt-recommendation" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ovior/twitter_dataset_1713063700
--- 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: 2287161 num_examples: 7097 download_size: 1288578 dataset_size: 2287161 configs: - config_name: default data_files: - split: train path: data/train-* ---
AdapterOcean/data-standardized_cluster_19
--- dataset_info: features: - name: text dtype: string - name: conversation_id dtype: int64 - name: embedding sequence: float64 - name: cluster dtype: int64 splits: - name: train num_bytes: 43899388 num_examples: 4277 download_size: 12613003 dataset_size: 43899388 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "data-standardized_cluster_19" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ibranze/araproje_hellaswag_en_conf_llama_worstscore
--- dataset_info: features: - name: ind dtype: int32 - name: activity_label dtype: string - name: ctx_a dtype: string - name: ctx_b dtype: string - name: ctx dtype: string - name: endings sequence: string - name: source_id dtype: string - name: split dtype: string - name: split_type dtype: string - name: label dtype: string splits: - name: validation num_bytes: 149738.0 num_examples: 250 download_size: 81192 dataset_size: 149738.0 configs: - config_name: default data_files: - split: validation path: data/validation-* --- # Dataset Card for "araproje_hellaswag_en_conf_llama_worstscore" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
sayan1101/test-krra
--- dataset_info: features: - name: question dtype: string - name: answer dtype: string splits: - name: train num_bytes: 204 num_examples: 1 download_size: 2504 dataset_size: 204 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "test-krra" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
MylesChew/JAX_FACADE_240
--- dataset_info: features: - name: image dtype: image - name: label dtype: image splits: - name: train num_bytes: 3848813.0 num_examples: 214 - name: validation num_bytes: 371632.0 num_examples: 24 download_size: 3438896 dataset_size: 4220445.0 --- # Dataset Card for "JAX_FACADE_240" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Shahzebbb/bookcorpus_tokenized
--- dataset_info: features: - name: tokens dtype: int64 splits: - name: train num_bytes: 8289993464 num_examples: 1036249183 download_size: 3290839503 dataset_size: 8289993464 configs: - config_name: default data_files: - split: train path: data/train-* ---
niltheory/PoeticDevices
--- license: cc-by-sa-4.0 language: - en tags: - creative writing - poetry - poetic devices pretty_name: Poetic Devices size_categories: - n<1K ---
katielink/moleculenet-benchmark
--- license: apache-2.0 tags: - biology - chemistry configs: - config_name: bace data_files: - split: train path: bace/train.csv - split: test path: bace/test.csv - split: val path: bace/valid.csv - config_name: bbbp data_files: - split: train path: bbbp/train.csv - split: test path: bbbp/test.csv - split: val path: bbbp/valid.csv - config_name: clintox data_files: - split: train path: clintox/train.csv - split: test path: clintox/test.csv - split: val path: clintox/valid.csv - config_name: esol data_files: - split: train path: esol/train.csv - split: test path: esol/test.csv - split: val path: esol/valid.csv - config_name: freesolv data_files: - split: train path: freesolv/train.csv - split: test path: freesolv/test.csv - split: val path: freesolv/valid.csv - config_name: hiv data_files: - split: train path: hiv/train.csv - split: test path: hiv/test.csv - split: val path: hiv/valid.csv - config_name: lipo data_files: - split: train path: lipo/train.csv - split: test path: lipo/test.csv - split: val path: lipo/valid.csv - config_name: qm9 data_files: - split: train path: qm9/train.csv - split: test path: qm9/test.csv - split: val path: qm9/valid.csv - config_name: sider data_files: - split: train path: sider/train.csv - split: test path: sider/test.csv - split: val path: sider/valid.csv - config_name: tox21 data_files: - split: train path: tox21/train.csv - split: test path: tox21/test.csv - split: val path: tox21/valid.csv --- # MoleculeNet Benchmark ([website](https://moleculenet.org/)) MoleculeNet is a benchmark specially designed for testing machine learning methods of molecular properties. As we aim to facilitate the development of molecular machine learning method, this work curates a number of dataset collections, creates a suite of software that implements many known featurizations and previously proposed algorithms. All methods and datasets are integrated as parts of the open source DeepChem package(MIT license). MoleculeNet is built upon multiple public databases. The full collection currently includes over 700,000 compounds tested on a range of different properties. We test the performances of various machine learning models with different featurizations on the datasets(detailed descriptions here), with all results reported in AUC-ROC, AUC-PRC, RMSE and MAE scores. For users, please cite: Zhenqin Wu, Bharath Ramsundar, Evan N. Feinberg, Joseph Gomes, Caleb Geniesse, Aneesh S. Pappu, Karl Leswing, Vijay Pande, MoleculeNet: A Benchmark for Molecular Machine Learning, arXiv preprint, arXiv: 1703.00564, 2017.
ArmelR/sharded-pile
--- configs: - config_name: all data_files: - split: train path: - data/ArXiv/train/*.parquet - data/BookCorpus2/train/*.parquet - data/Books3/train/*.arrow - data/DM Mathematics/train/*.parquet - data/Enron Emails/train/*.parquet - data/EuroParl/train/*.parquet - data/FreeLaw/train/*.parquet - data/Github/train/*.parquet - data/Gutenberg (PG-19)/train/*.parquet - data/HackerNews/train/*.parquet - data/NIH ExPorter/train/*.parquet - data/OpenSubtitles/train/*.parquet - data/OpenWebText2/train/*.parquet - data/PhilPapers/train/*.parquet - data/Pile-CC/train/*.parquet - data/PubMed Abstracts/train/*.parquet - data/PubMed Central/train/*.parquet - data/StackExchange/train/*.parquet - data/UPSTO Backgrounds/train/*.parquet - data/Ubuntu IRC/train/*.parquet - data/Wikipedia (en)/train/*.parquet - data/YoutubeSubtitles/train/*.parquet default : true ---
llm-lens/lens_sample_test
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': abyssinian '1': american bulldog '2': american pit bull terrier '3': basset hound '4': beagle '5': bengal '6': birman '7': bombay '8': boxer '9': british shorthair '10': chihuahua '11': egyptian mau '12': english cocker spaniel '13': english setter '14': german shorthaired '15': great pyrenees '16': havanese '17': japanese chin '18': keeshond '19': leonberger '20': maine coon '21': miniature pinscher '22': newfoundland '23': persian '24': pomeranian '25': pug '26': ragdoll '27': russian blue '28': saint bernard '29': samoyed '30': scottish terrier '31': shiba inu '32': siamese '33': sphynx '34': staffordshire bull terrier '35': wheaten terrier '36': yorkshire terrier - name: id dtype: int64 - name: tags_laion-ViT-H-14-2B sequence: string - name: attributes_laion-ViT-H-14-2B sequence: string - name: caption_Salesforce-blip-image-captioning-large dtype: string - name: intensive_captions_Salesforce-blip-image-captioning-large sequence: string splits: - name: test num_bytes: 183543.0 num_examples: 10 download_size: 162581 dataset_size: 183543.0 --- # Dataset Card for "lens_sample_test" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
msaad02/gpt-3.5-data-qa
--- dataset_info: features: - name: url dtype: string - name: data dtype: string - name: api_res dtype: string - name: questions dtype: string splits: - name: train num_bytes: 21127749 num_examples: 2683 download_size: 8837914 dataset_size: 21127749 configs: - config_name: default data_files: - split: train path: data/train-* ---
Tidrael/test2
--- annotations_creators: [] language: - en language_creators: - machine-generated license: - apache-2.0 multilinguality: - monolingual pretty_name: bussiness-news size_categories: - 1K<n<10K source_datasets: - original tags: [] task_categories: - text-classification task_ids: - sentiment-classification --- # Dataset Card for [Dataset Name] ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary Top news headline in finance from bbc-news ### Supported Tasks and Leaderboards [More Information Needed] ### Languages English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields Sentiment label: Using threshold from -2% to 2% for neutral (2), below is negative (1) and above is positive (3) [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
VishalMysore/chankyaNeet2
--- license: apache-2.0 ---
orendar/ultrafeedback_binarized_filtered
--- dataset_info: features: - name: prompt dtype: string - name: prompt_id dtype: string - name: chosen list: - name: content dtype: string - name: role dtype: string - name: rejected list: - name: content dtype: string - name: role dtype: string - name: messages list: - name: content dtype: string - name: role dtype: string - name: score_chosen dtype: float64 - name: score_rejected dtype: float64 - name: score_diff dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 162012105.5442132 num_examples: 27043 - name: test num_bytes: 1198181.4557868077 num_examples: 200 download_size: 90942425 dataset_size: 163210287.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* --- # Dataset Card for "ultrafeedback_binarized_filtered" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
liuyanchen1015/MULTI_VALUE_mrpc_indefinite_for_zero
--- 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: 475331 num_examples: 1683 - name: train num_bytes: 1012397 num_examples: 3580 - name: validation num_bytes: 114567 num_examples: 401 download_size: 1050270 dataset_size: 1602295 --- # Dataset Card for "MULTI_VALUE_mrpc_indefinite_for_zero" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Jackoon/JSON_expert_huy
--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 178537 num_examples: 173 download_size: 40306 dataset_size: 178537 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "JSON_expert_huy" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Bibek1129/nepali_SQuAD_single_qsn
--- license: cc-by-4.0 ---
ethz-spylab/hh-harmless-train-with-rewards
--- dataset_info: features: - name: chosen dtype: string - name: rejected dtype: string - name: chosen_reward dtype: float32 - name: rejected_reward dtype: float32 - name: correct dtype: bool - name: difference dtype: float32 splits: - name: train num_bytes: 56811404 num_examples: 42537 download_size: 32032368 dataset_size: 56811404 --- This dataset is an instance from the `harmless-base` split from the [Anthropic/hh-rlhf dataset](https://huggingface.co/datasets/Anthropic/hh-rlhf). All entries have been assigned a reward with our [custom reward model](https://huggingface.co/ethz-spylab/reward_model). This allows us to identify the most harmful generations and use them to poison models using our oracle attack presented in our paper "[Universal Jailbreak Backdoors from Poisoned Human Feedback](https://arxiv.org/abs/2311.14455)"
tasksource/regset
--- license: unknown ---
CyberHarem/futaba_rio_seishunbutayarou
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Futaba Rio This is the dataset of Futaba Rio, containing 200 images and their tags. 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)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 200 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 448 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 200 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 200 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 200 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 200 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 200 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 448 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 448 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 448 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
BangumiBase/kumakumakumabear
--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Kuma Kuma Kuma Bear This is the image base of bangumi Kuma Kuma Kuma Bear, we detected 99 characters, 6688 images in total. The full dataset is [here](all.zip). **Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: | # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 | |:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------| | 0 | 801 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 135 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 55 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 78 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 22 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 45 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 26 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 17 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 40 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 47 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 25 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 24 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 14 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 21 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 16 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 19 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 128 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 20 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 22 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | 19 | 58 | [Download](19/dataset.zip) | ![preview 1](19/preview_1.png) | ![preview 2](19/preview_2.png) | ![preview 3](19/preview_3.png) | ![preview 4](19/preview_4.png) | ![preview 5](19/preview_5.png) | ![preview 6](19/preview_6.png) | ![preview 7](19/preview_7.png) | ![preview 8](19/preview_8.png) | | 20 | 12 | [Download](20/dataset.zip) | ![preview 1](20/preview_1.png) | ![preview 2](20/preview_2.png) | ![preview 3](20/preview_3.png) | ![preview 4](20/preview_4.png) | ![preview 5](20/preview_5.png) | ![preview 6](20/preview_6.png) | ![preview 7](20/preview_7.png) | ![preview 8](20/preview_8.png) | | 21 | 180 | [Download](21/dataset.zip) | ![preview 1](21/preview_1.png) | ![preview 2](21/preview_2.png) | ![preview 3](21/preview_3.png) | ![preview 4](21/preview_4.png) | ![preview 5](21/preview_5.png) | ![preview 6](21/preview_6.png) | ![preview 7](21/preview_7.png) | ![preview 8](21/preview_8.png) | | 22 | 15 | [Download](22/dataset.zip) | ![preview 1](22/preview_1.png) | ![preview 2](22/preview_2.png) | ![preview 3](22/preview_3.png) | ![preview 4](22/preview_4.png) | ![preview 5](22/preview_5.png) | ![preview 6](22/preview_6.png) | ![preview 7](22/preview_7.png) | ![preview 8](22/preview_8.png) | | 23 | 14 | [Download](23/dataset.zip) | ![preview 1](23/preview_1.png) | ![preview 2](23/preview_2.png) | ![preview 3](23/preview_3.png) | ![preview 4](23/preview_4.png) | ![preview 5](23/preview_5.png) | ![preview 6](23/preview_6.png) | ![preview 7](23/preview_7.png) | ![preview 8](23/preview_8.png) | | 24 | 49 | [Download](24/dataset.zip) | ![preview 1](24/preview_1.png) | ![preview 2](24/preview_2.png) | ![preview 3](24/preview_3.png) | ![preview 4](24/preview_4.png) | ![preview 5](24/preview_5.png) | ![preview 6](24/preview_6.png) | ![preview 7](24/preview_7.png) | ![preview 8](24/preview_8.png) | | 25 | 13 | [Download](25/dataset.zip) | ![preview 1](25/preview_1.png) | ![preview 2](25/preview_2.png) | ![preview 3](25/preview_3.png) | ![preview 4](25/preview_4.png) | ![preview 5](25/preview_5.png) | ![preview 6](25/preview_6.png) | ![preview 7](25/preview_7.png) | ![preview 8](25/preview_8.png) | | 26 | 60 | [Download](26/dataset.zip) | ![preview 1](26/preview_1.png) | ![preview 2](26/preview_2.png) | ![preview 3](26/preview_3.png) | ![preview 4](26/preview_4.png) | ![preview 5](26/preview_5.png) | ![preview 6](26/preview_6.png) | ![preview 7](26/preview_7.png) | ![preview 8](26/preview_8.png) | | 27 | 15 | [Download](27/dataset.zip) | ![preview 1](27/preview_1.png) | ![preview 2](27/preview_2.png) | ![preview 3](27/preview_3.png) | ![preview 4](27/preview_4.png) | ![preview 5](27/preview_5.png) | ![preview 6](27/preview_6.png) | ![preview 7](27/preview_7.png) | ![preview 8](27/preview_8.png) | | 28 | 21 | [Download](28/dataset.zip) | ![preview 1](28/preview_1.png) | ![preview 2](28/preview_2.png) | ![preview 3](28/preview_3.png) | ![preview 4](28/preview_4.png) | ![preview 5](28/preview_5.png) | ![preview 6](28/preview_6.png) | ![preview 7](28/preview_7.png) | ![preview 8](28/preview_8.png) | | 29 | 103 | [Download](29/dataset.zip) | ![preview 1](29/preview_1.png) | ![preview 2](29/preview_2.png) | ![preview 3](29/preview_3.png) | ![preview 4](29/preview_4.png) | ![preview 5](29/preview_5.png) | ![preview 6](29/preview_6.png) | ![preview 7](29/preview_7.png) | ![preview 8](29/preview_8.png) | | 30 | 16 | [Download](30/dataset.zip) | ![preview 1](30/preview_1.png) | ![preview 2](30/preview_2.png) | ![preview 3](30/preview_3.png) | ![preview 4](30/preview_4.png) | ![preview 5](30/preview_5.png) | ![preview 6](30/preview_6.png) | ![preview 7](30/preview_7.png) | ![preview 8](30/preview_8.png) | | 31 | 12 | [Download](31/dataset.zip) | ![preview 1](31/preview_1.png) | ![preview 2](31/preview_2.png) | ![preview 3](31/preview_3.png) | ![preview 4](31/preview_4.png) | ![preview 5](31/preview_5.png) | ![preview 6](31/preview_6.png) | ![preview 7](31/preview_7.png) | ![preview 8](31/preview_8.png) | | 32 | 35 | [Download](32/dataset.zip) | ![preview 1](32/preview_1.png) | ![preview 2](32/preview_2.png) | ![preview 3](32/preview_3.png) | ![preview 4](32/preview_4.png) | ![preview 5](32/preview_5.png) | ![preview 6](32/preview_6.png) | ![preview 7](32/preview_7.png) | ![preview 8](32/preview_8.png) | | 33 | 8 | [Download](33/dataset.zip) | ![preview 1](33/preview_1.png) | ![preview 2](33/preview_2.png) | ![preview 3](33/preview_3.png) | ![preview 4](33/preview_4.png) | ![preview 5](33/preview_5.png) | ![preview 6](33/preview_6.png) | ![preview 7](33/preview_7.png) | ![preview 8](33/preview_8.png) | | 34 | 14 | [Download](34/dataset.zip) | ![preview 1](34/preview_1.png) | ![preview 2](34/preview_2.png) | ![preview 3](34/preview_3.png) | ![preview 4](34/preview_4.png) | ![preview 5](34/preview_5.png) | ![preview 6](34/preview_6.png) | ![preview 7](34/preview_7.png) | ![preview 8](34/preview_8.png) | | 35 | 15 | [Download](35/dataset.zip) | ![preview 1](35/preview_1.png) | ![preview 2](35/preview_2.png) | ![preview 3](35/preview_3.png) | ![preview 4](35/preview_4.png) | ![preview 5](35/preview_5.png) | ![preview 6](35/preview_6.png) | ![preview 7](35/preview_7.png) | ![preview 8](35/preview_8.png) | | 36 | 10 | [Download](36/dataset.zip) | ![preview 1](36/preview_1.png) | ![preview 2](36/preview_2.png) | ![preview 3](36/preview_3.png) | ![preview 4](36/preview_4.png) | ![preview 5](36/preview_5.png) | ![preview 6](36/preview_6.png) | ![preview 7](36/preview_7.png) | ![preview 8](36/preview_8.png) | | 37 | 16 | [Download](37/dataset.zip) | ![preview 1](37/preview_1.png) | ![preview 2](37/preview_2.png) | ![preview 3](37/preview_3.png) | ![preview 4](37/preview_4.png) | ![preview 5](37/preview_5.png) | ![preview 6](37/preview_6.png) | ![preview 7](37/preview_7.png) | ![preview 8](37/preview_8.png) | | 38 | 33 | [Download](38/dataset.zip) | ![preview 1](38/preview_1.png) | ![preview 2](38/preview_2.png) | ![preview 3](38/preview_3.png) | ![preview 4](38/preview_4.png) | ![preview 5](38/preview_5.png) | ![preview 6](38/preview_6.png) | ![preview 7](38/preview_7.png) | ![preview 8](38/preview_8.png) | | 39 | 17 | [Download](39/dataset.zip) | ![preview 1](39/preview_1.png) | ![preview 2](39/preview_2.png) | ![preview 3](39/preview_3.png) | ![preview 4](39/preview_4.png) | ![preview 5](39/preview_5.png) | ![preview 6](39/preview_6.png) | ![preview 7](39/preview_7.png) | ![preview 8](39/preview_8.png) | | 40 | 70 | [Download](40/dataset.zip) | ![preview 1](40/preview_1.png) | ![preview 2](40/preview_2.png) | ![preview 3](40/preview_3.png) | ![preview 4](40/preview_4.png) | ![preview 5](40/preview_5.png) | ![preview 6](40/preview_6.png) | ![preview 7](40/preview_7.png) | ![preview 8](40/preview_8.png) | | 41 | 10 | [Download](41/dataset.zip) | ![preview 1](41/preview_1.png) | ![preview 2](41/preview_2.png) | ![preview 3](41/preview_3.png) | ![preview 4](41/preview_4.png) | ![preview 5](41/preview_5.png) | ![preview 6](41/preview_6.png) | ![preview 7](41/preview_7.png) | ![preview 8](41/preview_8.png) | | 42 | 26 | [Download](42/dataset.zip) | ![preview 1](42/preview_1.png) | ![preview 2](42/preview_2.png) | ![preview 3](42/preview_3.png) | ![preview 4](42/preview_4.png) | ![preview 5](42/preview_5.png) | ![preview 6](42/preview_6.png) | ![preview 7](42/preview_7.png) | ![preview 8](42/preview_8.png) | | 43 | 1939 | [Download](43/dataset.zip) | ![preview 1](43/preview_1.png) | ![preview 2](43/preview_2.png) | ![preview 3](43/preview_3.png) | ![preview 4](43/preview_4.png) | ![preview 5](43/preview_5.png) | ![preview 6](43/preview_6.png) | ![preview 7](43/preview_7.png) | ![preview 8](43/preview_8.png) | | 44 | 105 | [Download](44/dataset.zip) | ![preview 1](44/preview_1.png) | ![preview 2](44/preview_2.png) | ![preview 3](44/preview_3.png) | ![preview 4](44/preview_4.png) | ![preview 5](44/preview_5.png) | ![preview 6](44/preview_6.png) | ![preview 7](44/preview_7.png) | ![preview 8](44/preview_8.png) | | 45 | 22 | [Download](45/dataset.zip) | ![preview 1](45/preview_1.png) | ![preview 2](45/preview_2.png) | ![preview 3](45/preview_3.png) | ![preview 4](45/preview_4.png) | ![preview 5](45/preview_5.png) | ![preview 6](45/preview_6.png) | ![preview 7](45/preview_7.png) | ![preview 8](45/preview_8.png) | | 46 | 36 | [Download](46/dataset.zip) | ![preview 1](46/preview_1.png) | ![preview 2](46/preview_2.png) | ![preview 3](46/preview_3.png) | ![preview 4](46/preview_4.png) | ![preview 5](46/preview_5.png) | ![preview 6](46/preview_6.png) | ![preview 7](46/preview_7.png) | ![preview 8](46/preview_8.png) | | 47 | 38 | [Download](47/dataset.zip) | ![preview 1](47/preview_1.png) | ![preview 2](47/preview_2.png) | ![preview 3](47/preview_3.png) | ![preview 4](47/preview_4.png) | ![preview 5](47/preview_5.png) | ![preview 6](47/preview_6.png) | ![preview 7](47/preview_7.png) | ![preview 8](47/preview_8.png) | | 48 | 8 | [Download](48/dataset.zip) | ![preview 1](48/preview_1.png) | ![preview 2](48/preview_2.png) | ![preview 3](48/preview_3.png) | ![preview 4](48/preview_4.png) | ![preview 5](48/preview_5.png) | ![preview 6](48/preview_6.png) | ![preview 7](48/preview_7.png) | ![preview 8](48/preview_8.png) | | 49 | 7 | [Download](49/dataset.zip) | ![preview 1](49/preview_1.png) | ![preview 2](49/preview_2.png) | ![preview 3](49/preview_3.png) | ![preview 4](49/preview_4.png) | ![preview 5](49/preview_5.png) | ![preview 6](49/preview_6.png) | ![preview 7](49/preview_7.png) | N/A | | 50 | 69 | [Download](50/dataset.zip) | ![preview 1](50/preview_1.png) | ![preview 2](50/preview_2.png) | ![preview 3](50/preview_3.png) | ![preview 4](50/preview_4.png) | ![preview 5](50/preview_5.png) | ![preview 6](50/preview_6.png) | ![preview 7](50/preview_7.png) | ![preview 8](50/preview_8.png) | | 51 | 66 | [Download](51/dataset.zip) | ![preview 1](51/preview_1.png) | ![preview 2](51/preview_2.png) | ![preview 3](51/preview_3.png) | ![preview 4](51/preview_4.png) | ![preview 5](51/preview_5.png) | ![preview 6](51/preview_6.png) | ![preview 7](51/preview_7.png) | ![preview 8](51/preview_8.png) | | 52 | 7 | [Download](52/dataset.zip) | ![preview 1](52/preview_1.png) | ![preview 2](52/preview_2.png) | ![preview 3](52/preview_3.png) | ![preview 4](52/preview_4.png) | ![preview 5](52/preview_5.png) | ![preview 6](52/preview_6.png) | ![preview 7](52/preview_7.png) | N/A | | 53 | 22 | [Download](53/dataset.zip) | ![preview 1](53/preview_1.png) | ![preview 2](53/preview_2.png) | ![preview 3](53/preview_3.png) | ![preview 4](53/preview_4.png) | ![preview 5](53/preview_5.png) | ![preview 6](53/preview_6.png) | ![preview 7](53/preview_7.png) | ![preview 8](53/preview_8.png) | | 54 | 7 | [Download](54/dataset.zip) | ![preview 1](54/preview_1.png) | ![preview 2](54/preview_2.png) | ![preview 3](54/preview_3.png) | ![preview 4](54/preview_4.png) | ![preview 5](54/preview_5.png) | ![preview 6](54/preview_6.png) | ![preview 7](54/preview_7.png) | N/A | | 55 | 14 | [Download](55/dataset.zip) | ![preview 1](55/preview_1.png) | ![preview 2](55/preview_2.png) | ![preview 3](55/preview_3.png) | ![preview 4](55/preview_4.png) | ![preview 5](55/preview_5.png) | ![preview 6](55/preview_6.png) | ![preview 7](55/preview_7.png) | ![preview 8](55/preview_8.png) | | 56 | 197 | [Download](56/dataset.zip) | ![preview 1](56/preview_1.png) | ![preview 2](56/preview_2.png) | ![preview 3](56/preview_3.png) | ![preview 4](56/preview_4.png) | ![preview 5](56/preview_5.png) | ![preview 6](56/preview_6.png) | ![preview 7](56/preview_7.png) | ![preview 8](56/preview_8.png) | | 57 | 52 | [Download](57/dataset.zip) | ![preview 1](57/preview_1.png) | ![preview 2](57/preview_2.png) | ![preview 3](57/preview_3.png) | ![preview 4](57/preview_4.png) | ![preview 5](57/preview_5.png) | ![preview 6](57/preview_6.png) | ![preview 7](57/preview_7.png) | ![preview 8](57/preview_8.png) | | 58 | 8 | [Download](58/dataset.zip) | ![preview 1](58/preview_1.png) | ![preview 2](58/preview_2.png) | ![preview 3](58/preview_3.png) | ![preview 4](58/preview_4.png) | ![preview 5](58/preview_5.png) | ![preview 6](58/preview_6.png) | ![preview 7](58/preview_7.png) | ![preview 8](58/preview_8.png) | | 59 | 29 | [Download](59/dataset.zip) | ![preview 1](59/preview_1.png) | ![preview 2](59/preview_2.png) | ![preview 3](59/preview_3.png) | ![preview 4](59/preview_4.png) | ![preview 5](59/preview_5.png) | ![preview 6](59/preview_6.png) | ![preview 7](59/preview_7.png) | ![preview 8](59/preview_8.png) | | 60 | 62 | [Download](60/dataset.zip) | ![preview 1](60/preview_1.png) | ![preview 2](60/preview_2.png) | ![preview 3](60/preview_3.png) | ![preview 4](60/preview_4.png) | ![preview 5](60/preview_5.png) | ![preview 6](60/preview_6.png) | ![preview 7](60/preview_7.png) | ![preview 8](60/preview_8.png) | | 61 | 26 | [Download](61/dataset.zip) | ![preview 1](61/preview_1.png) | ![preview 2](61/preview_2.png) | ![preview 3](61/preview_3.png) | ![preview 4](61/preview_4.png) | ![preview 5](61/preview_5.png) | ![preview 6](61/preview_6.png) | ![preview 7](61/preview_7.png) | ![preview 8](61/preview_8.png) | | 62 | 69 | [Download](62/dataset.zip) | ![preview 1](62/preview_1.png) | ![preview 2](62/preview_2.png) | ![preview 3](62/preview_3.png) | ![preview 4](62/preview_4.png) | ![preview 5](62/preview_5.png) | ![preview 6](62/preview_6.png) | ![preview 7](62/preview_7.png) | ![preview 8](62/preview_8.png) | | 63 | 30 | [Download](63/dataset.zip) | ![preview 1](63/preview_1.png) | ![preview 2](63/preview_2.png) | ![preview 3](63/preview_3.png) | ![preview 4](63/preview_4.png) | ![preview 5](63/preview_5.png) | ![preview 6](63/preview_6.png) | ![preview 7](63/preview_7.png) | ![preview 8](63/preview_8.png) | | 64 | 11 | [Download](64/dataset.zip) | ![preview 1](64/preview_1.png) | ![preview 2](64/preview_2.png) | ![preview 3](64/preview_3.png) | ![preview 4](64/preview_4.png) | ![preview 5](64/preview_5.png) | ![preview 6](64/preview_6.png) | ![preview 7](64/preview_7.png) | ![preview 8](64/preview_8.png) | | 65 | 55 | [Download](65/dataset.zip) | ![preview 1](65/preview_1.png) | ![preview 2](65/preview_2.png) | ![preview 3](65/preview_3.png) | ![preview 4](65/preview_4.png) | ![preview 5](65/preview_5.png) | ![preview 6](65/preview_6.png) | ![preview 7](65/preview_7.png) | ![preview 8](65/preview_8.png) | | 66 | 15 | [Download](66/dataset.zip) | ![preview 1](66/preview_1.png) | ![preview 2](66/preview_2.png) | ![preview 3](66/preview_3.png) | ![preview 4](66/preview_4.png) | ![preview 5](66/preview_5.png) | ![preview 6](66/preview_6.png) | ![preview 7](66/preview_7.png) | ![preview 8](66/preview_8.png) | | 67 | 204 | [Download](67/dataset.zip) | ![preview 1](67/preview_1.png) | ![preview 2](67/preview_2.png) | ![preview 3](67/preview_3.png) | ![preview 4](67/preview_4.png) | ![preview 5](67/preview_5.png) | ![preview 6](67/preview_6.png) | ![preview 7](67/preview_7.png) | ![preview 8](67/preview_8.png) | | 68 | 283 | [Download](68/dataset.zip) | ![preview 1](68/preview_1.png) | ![preview 2](68/preview_2.png) | ![preview 3](68/preview_3.png) | ![preview 4](68/preview_4.png) | ![preview 5](68/preview_5.png) | ![preview 6](68/preview_6.png) | ![preview 7](68/preview_7.png) | ![preview 8](68/preview_8.png) | | 69 | 26 | [Download](69/dataset.zip) | ![preview 1](69/preview_1.png) | ![preview 2](69/preview_2.png) | ![preview 3](69/preview_3.png) | ![preview 4](69/preview_4.png) | ![preview 5](69/preview_5.png) | ![preview 6](69/preview_6.png) | ![preview 7](69/preview_7.png) | ![preview 8](69/preview_8.png) | | 70 | 40 | [Download](70/dataset.zip) | ![preview 1](70/preview_1.png) | ![preview 2](70/preview_2.png) | ![preview 3](70/preview_3.png) | ![preview 4](70/preview_4.png) | ![preview 5](70/preview_5.png) | ![preview 6](70/preview_6.png) | ![preview 7](70/preview_7.png) | ![preview 8](70/preview_8.png) | | 71 | 17 | [Download](71/dataset.zip) | ![preview 1](71/preview_1.png) | ![preview 2](71/preview_2.png) | ![preview 3](71/preview_3.png) | ![preview 4](71/preview_4.png) | ![preview 5](71/preview_5.png) | ![preview 6](71/preview_6.png) | ![preview 7](71/preview_7.png) | ![preview 8](71/preview_8.png) | | 72 | 8 | [Download](72/dataset.zip) | ![preview 1](72/preview_1.png) | ![preview 2](72/preview_2.png) | ![preview 3](72/preview_3.png) | ![preview 4](72/preview_4.png) | ![preview 5](72/preview_5.png) | ![preview 6](72/preview_6.png) | ![preview 7](72/preview_7.png) | ![preview 8](72/preview_8.png) | | 73 | 13 | [Download](73/dataset.zip) | ![preview 1](73/preview_1.png) | ![preview 2](73/preview_2.png) | ![preview 3](73/preview_3.png) | ![preview 4](73/preview_4.png) | ![preview 5](73/preview_5.png) | ![preview 6](73/preview_6.png) | ![preview 7](73/preview_7.png) | ![preview 8](73/preview_8.png) | | 74 | 18 | [Download](74/dataset.zip) | ![preview 1](74/preview_1.png) | ![preview 2](74/preview_2.png) | ![preview 3](74/preview_3.png) | ![preview 4](74/preview_4.png) | ![preview 5](74/preview_5.png) | ![preview 6](74/preview_6.png) | ![preview 7](74/preview_7.png) | ![preview 8](74/preview_8.png) | | 75 | 16 | [Download](75/dataset.zip) | ![preview 1](75/preview_1.png) | ![preview 2](75/preview_2.png) | ![preview 3](75/preview_3.png) | ![preview 4](75/preview_4.png) | ![preview 5](75/preview_5.png) | ![preview 6](75/preview_6.png) | ![preview 7](75/preview_7.png) | ![preview 8](75/preview_8.png) | | 76 | 8 | [Download](76/dataset.zip) | ![preview 1](76/preview_1.png) | ![preview 2](76/preview_2.png) | ![preview 3](76/preview_3.png) | ![preview 4](76/preview_4.png) | ![preview 5](76/preview_5.png) | ![preview 6](76/preview_6.png) | ![preview 7](76/preview_7.png) | ![preview 8](76/preview_8.png) | | 77 | 10 | [Download](77/dataset.zip) | ![preview 1](77/preview_1.png) | ![preview 2](77/preview_2.png) | ![preview 3](77/preview_3.png) | ![preview 4](77/preview_4.png) | ![preview 5](77/preview_5.png) | ![preview 6](77/preview_6.png) | ![preview 7](77/preview_7.png) | ![preview 8](77/preview_8.png) | | 78 | 51 | [Download](78/dataset.zip) | ![preview 1](78/preview_1.png) | ![preview 2](78/preview_2.png) | ![preview 3](78/preview_3.png) | ![preview 4](78/preview_4.png) | ![preview 5](78/preview_5.png) | ![preview 6](78/preview_6.png) | ![preview 7](78/preview_7.png) | ![preview 8](78/preview_8.png) | | 79 | 135 | [Download](79/dataset.zip) | ![preview 1](79/preview_1.png) | ![preview 2](79/preview_2.png) | ![preview 3](79/preview_3.png) | ![preview 4](79/preview_4.png) | ![preview 5](79/preview_5.png) | ![preview 6](79/preview_6.png) | ![preview 7](79/preview_7.png) | ![preview 8](79/preview_8.png) | | 80 | 62 | [Download](80/dataset.zip) | ![preview 1](80/preview_1.png) | ![preview 2](80/preview_2.png) | ![preview 3](80/preview_3.png) | ![preview 4](80/preview_4.png) | ![preview 5](80/preview_5.png) | ![preview 6](80/preview_6.png) | ![preview 7](80/preview_7.png) | ![preview 8](80/preview_8.png) | | 81 | 14 | [Download](81/dataset.zip) | ![preview 1](81/preview_1.png) | ![preview 2](81/preview_2.png) | ![preview 3](81/preview_3.png) | ![preview 4](81/preview_4.png) | ![preview 5](81/preview_5.png) | ![preview 6](81/preview_6.png) | ![preview 7](81/preview_7.png) | ![preview 8](81/preview_8.png) | | 82 | 48 | [Download](82/dataset.zip) | ![preview 1](82/preview_1.png) | ![preview 2](82/preview_2.png) | ![preview 3](82/preview_3.png) | ![preview 4](82/preview_4.png) | ![preview 5](82/preview_5.png) | ![preview 6](82/preview_6.png) | ![preview 7](82/preview_7.png) | ![preview 8](82/preview_8.png) | | 83 | 15 | [Download](83/dataset.zip) | ![preview 1](83/preview_1.png) | ![preview 2](83/preview_2.png) | ![preview 3](83/preview_3.png) | ![preview 4](83/preview_4.png) | ![preview 5](83/preview_5.png) | ![preview 6](83/preview_6.png) | ![preview 7](83/preview_7.png) | ![preview 8](83/preview_8.png) | | 84 | 14 | [Download](84/dataset.zip) | ![preview 1](84/preview_1.png) | ![preview 2](84/preview_2.png) | ![preview 3](84/preview_3.png) | ![preview 4](84/preview_4.png) | ![preview 5](84/preview_5.png) | ![preview 6](84/preview_6.png) | ![preview 7](84/preview_7.png) | ![preview 8](84/preview_8.png) | | 85 | 38 | [Download](85/dataset.zip) | ![preview 1](85/preview_1.png) | ![preview 2](85/preview_2.png) | ![preview 3](85/preview_3.png) | ![preview 4](85/preview_4.png) | ![preview 5](85/preview_5.png) | ![preview 6](85/preview_6.png) | ![preview 7](85/preview_7.png) | ![preview 8](85/preview_8.png) | | 86 | 6 | [Download](86/dataset.zip) | ![preview 1](86/preview_1.png) | ![preview 2](86/preview_2.png) | ![preview 3](86/preview_3.png) | ![preview 4](86/preview_4.png) | ![preview 5](86/preview_5.png) | ![preview 6](86/preview_6.png) | N/A | N/A | | 87 | 14 | [Download](87/dataset.zip) | ![preview 1](87/preview_1.png) | ![preview 2](87/preview_2.png) | ![preview 3](87/preview_3.png) | ![preview 4](87/preview_4.png) | ![preview 5](87/preview_5.png) | ![preview 6](87/preview_6.png) | ![preview 7](87/preview_7.png) | ![preview 8](87/preview_8.png) | | 88 | 8 | [Download](88/dataset.zip) | ![preview 1](88/preview_1.png) | ![preview 2](88/preview_2.png) | ![preview 3](88/preview_3.png) | ![preview 4](88/preview_4.png) | ![preview 5](88/preview_5.png) | ![preview 6](88/preview_6.png) | ![preview 7](88/preview_7.png) | ![preview 8](88/preview_8.png) | | 89 | 9 | [Download](89/dataset.zip) | ![preview 1](89/preview_1.png) | ![preview 2](89/preview_2.png) | ![preview 3](89/preview_3.png) | ![preview 4](89/preview_4.png) | ![preview 5](89/preview_5.png) | ![preview 6](89/preview_6.png) | ![preview 7](89/preview_7.png) | ![preview 8](89/preview_8.png) | | 90 | 6 | [Download](90/dataset.zip) | ![preview 1](90/preview_1.png) | ![preview 2](90/preview_2.png) | ![preview 3](90/preview_3.png) | ![preview 4](90/preview_4.png) | ![preview 5](90/preview_5.png) | ![preview 6](90/preview_6.png) | N/A | N/A | | 91 | 5 | [Download](91/dataset.zip) | ![preview 1](91/preview_1.png) | ![preview 2](91/preview_2.png) | ![preview 3](91/preview_3.png) | ![preview 4](91/preview_4.png) | ![preview 5](91/preview_5.png) | N/A | N/A | N/A | | 92 | 38 | [Download](92/dataset.zip) | ![preview 1](92/preview_1.png) | ![preview 2](92/preview_2.png) | ![preview 3](92/preview_3.png) | ![preview 4](92/preview_4.png) | ![preview 5](92/preview_5.png) | ![preview 6](92/preview_6.png) | ![preview 7](92/preview_7.png) | ![preview 8](92/preview_8.png) | | 93 | 29 | [Download](93/dataset.zip) | ![preview 1](93/preview_1.png) | ![preview 2](93/preview_2.png) | ![preview 3](93/preview_3.png) | ![preview 4](93/preview_4.png) | ![preview 5](93/preview_5.png) | ![preview 6](93/preview_6.png) | ![preview 7](93/preview_7.png) | ![preview 8](93/preview_8.png) | | 94 | 7 | [Download](94/dataset.zip) | ![preview 1](94/preview_1.png) | ![preview 2](94/preview_2.png) | ![preview 3](94/preview_3.png) | ![preview 4](94/preview_4.png) | ![preview 5](94/preview_5.png) | ![preview 6](94/preview_6.png) | ![preview 7](94/preview_7.png) | N/A | | 95 | 17 | [Download](95/dataset.zip) | ![preview 1](95/preview_1.png) | ![preview 2](95/preview_2.png) | ![preview 3](95/preview_3.png) | ![preview 4](95/preview_4.png) | ![preview 5](95/preview_5.png) | ![preview 6](95/preview_6.png) | ![preview 7](95/preview_7.png) | ![preview 8](95/preview_8.png) | | 96 | 24 | [Download](96/dataset.zip) | ![preview 1](96/preview_1.png) | ![preview 2](96/preview_2.png) | ![preview 3](96/preview_3.png) | ![preview 4](96/preview_4.png) | ![preview 5](96/preview_5.png) | ![preview 6](96/preview_6.png) | ![preview 7](96/preview_7.png) | ![preview 8](96/preview_8.png) | | 97 | 11 | [Download](97/dataset.zip) | ![preview 1](97/preview_1.png) | ![preview 2](97/preview_2.png) | ![preview 3](97/preview_3.png) | ![preview 4](97/preview_4.png) | ![preview 5](97/preview_5.png) | ![preview 6](97/preview_6.png) | ![preview 7](97/preview_7.png) | ![preview 8](97/preview_8.png) | | noise | 223 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |
tyzhu/find_sent_before_sent_train_400_eval_40_random_permute_8
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: inputs dtype: string - name: targets dtype: string - name: title dtype: string - name: context dtype: string splits: - name: train num_bytes: 7719631.487403426 num_examples: 5514 - name: validation num_bytes: 232610 num_examples: 200 download_size: 1303658 dataset_size: 7952241.487403426 --- # Dataset Card for "find_sent_before_sent_train_400_eval_40_random_permute_8" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Multimodal-Fatima/OxfordFlowers_test_facebook_opt_350m_Visclues_ns_6149_random
--- dataset_info: features: - name: id dtype: int64 - name: image dtype: image - name: prompt dtype: string - name: true_label dtype: string - name: prediction dtype: string - name: scores sequence: float64 splits: - name: fewshot_1_bs_16 num_bytes: 270234974.375 num_examples: 6149 - name: fewshot_3_bs_16 num_bytes: 274952857.375 num_examples: 6149 download_size: 534121686 dataset_size: 545187831.75 --- # Dataset Card for "OxfordFlowers_test_facebook_opt_350m_Visclues_ns_6149_random" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
it-at-m/LHM-Dienstleistungen-QA
--- license: mit language: - de tags: - QA dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers struct: - name: answer_start sequence: int64 - name: text sequence: string splits: - name: test num_bytes: 560403 num_examples: 357 - name: train num_bytes: 2826731 num_examples: 1773 download_size: 710027 dataset_size: 3387134 task_categories: - question-answering pretty_name: 'LHM Dienstleistungen: QA' size_categories: - 1K<n<10K --- # LHM-Dienstleistungen-QA - german public domain question-answering dataset Datasets created based on data from Munich city administration. Format inspired by GermanQuAD. ## Annotated by: - Institute for Applied Artificial Intelligence: Leon Marius Schröder - BettercallPaul GmbH: Clemens Gutknecht, Oubada Alkiddeh, Susanne Weiß - Stadt München: Leon Lukas ## Data basis Texts taken from the “Dienstleistungsfinder“ of the city of Munich administration. There information about services offered by city is presented online. Information ranges from applying for an ID card to dispose of garbage. - https://stadt.muenchen.de/service/ (Date 11/2022) ## Dataset statistics - Shortest Question: 13 Characters - Average Question: 68 Characters - Longest Question: 183 Characters ### Distribution of first sentence beginnings ![all_words](alle.jpg " All sentence beginnings ") ### Distribution of first sentence beginnings: Wie ![Wie](Wie.jpg " Wie sentence beginnings") ### Distribution of first sentence beginnings: Wo ![Wo](wo.jpg " Wo sentence beginnings") ### Distribution of first sentence beginnings: Was ![Was](Was.jpg " Was sentence beginnings") ## Models trained using this datset ### QA - cgutknecht/gelectra_large_gsqd-gq-LHM ### DPR - schreon/xnext-lhm_queries_encoder - schreon/xnext-lhm_passages_encoder
darcksky/Ringsofsaturnlugalkien
--- license: artistic-2.0 ---
open-llm-leaderboard/details_bit-dny__MindLLM
--- pretty_name: Evaluation run of bit-dny/MindLLM dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [bit-dny/MindLLM](https://huggingface.co/bit-dny/MindLLM) 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_bit-dny__MindLLM\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-27T12:33:52.223530](https://huggingface.co/datasets/open-llm-leaderboard/details_bit-dny__MindLLM/blob/main/results_2023-12-27T12-33-52.223530.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\": 0.2547315459012399,\n\ \ \"acc_stderr\": 0.030757121924893716,\n \"acc_norm\": 0.2559855532831359,\n\ \ \"acc_norm_stderr\": 0.03153175700940631,\n \"mc1\": 0.26193390452876375,\n\ \ \"mc1_stderr\": 0.015392118805015025,\n \"mc2\": 0.43479871223663846,\n\ \ \"mc2_stderr\": 0.015180815930542027\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.19539249146757678,\n \"acc_stderr\": 0.011586907189952911,\n\ \ \"acc_norm\": 0.22440273037542663,\n \"acc_norm_stderr\": 0.012191404938603838\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.30392352121091415,\n\ \ \"acc_stderr\": 0.004590100050198833,\n \"acc_norm\": 0.34106751643098987,\n\ \ \"acc_norm_stderr\": 0.004730991357194287\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.042295258468165044,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.042295258468165044\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.24444444444444444,\n\ \ \"acc_stderr\": 0.03712537833614866,\n \"acc_norm\": 0.24444444444444444,\n\ \ \"acc_norm_stderr\": 0.03712537833614866\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.20394736842105263,\n \"acc_stderr\": 0.0327900040631005,\n\ \ \"acc_norm\": 0.20394736842105263,\n \"acc_norm_stderr\": 0.0327900040631005\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.26,\n\ \ \"acc_stderr\": 0.044084400227680794,\n \"acc_norm\": 0.26,\n \ \ \"acc_norm_stderr\": 0.044084400227680794\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.27169811320754716,\n \"acc_stderr\": 0.027377706624670713,\n\ \ \"acc_norm\": 0.27169811320754716,\n \"acc_norm_stderr\": 0.027377706624670713\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.2916666666666667,\n\ \ \"acc_stderr\": 0.03800968060554858,\n \"acc_norm\": 0.2916666666666667,\n\ \ \"acc_norm_stderr\": 0.03800968060554858\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.2,\n \"acc_stderr\": 0.040201512610368445,\n \ \ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.040201512610368445\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\": 0.37,\n\ \ \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.23121387283236994,\n\ \ \"acc_stderr\": 0.03214737302029471,\n \"acc_norm\": 0.23121387283236994,\n\ \ \"acc_norm_stderr\": 0.03214737302029471\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.17647058823529413,\n \"acc_stderr\": 0.0379328118530781,\n\ \ \"acc_norm\": 0.17647058823529413,\n \"acc_norm_stderr\": 0.0379328118530781\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.18,\n \"acc_stderr\": 0.038612291966536955,\n \"acc_norm\": 0.18,\n\ \ \"acc_norm_stderr\": 0.038612291966536955\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.2851063829787234,\n \"acc_stderr\": 0.02951319662553935,\n\ \ \"acc_norm\": 0.2851063829787234,\n \"acc_norm_stderr\": 0.02951319662553935\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2631578947368421,\n\ \ \"acc_stderr\": 0.041424397194893624,\n \"acc_norm\": 0.2631578947368421,\n\ \ \"acc_norm_stderr\": 0.041424397194893624\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.27586206896551724,\n \"acc_stderr\": 0.037245636197746325,\n\ \ \"acc_norm\": 0.27586206896551724,\n \"acc_norm_stderr\": 0.037245636197746325\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.26455026455026454,\n \"acc_stderr\": 0.022717467897708617,\n \"\ acc_norm\": 0.26455026455026454,\n \"acc_norm_stderr\": 0.022717467897708617\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.15079365079365079,\n\ \ \"acc_stderr\": 0.03200686497287394,\n \"acc_norm\": 0.15079365079365079,\n\ \ \"acc_norm_stderr\": 0.03200686497287394\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.23870967741935484,\n\ \ \"acc_stderr\": 0.024251071262208837,\n \"acc_norm\": 0.23870967741935484,\n\ \ \"acc_norm_stderr\": 0.024251071262208837\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.2955665024630542,\n \"acc_stderr\": 0.032104944337514575,\n\ \ \"acc_norm\": 0.2955665024630542,\n \"acc_norm_stderr\": 0.032104944337514575\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \"acc_norm\"\ : 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.21818181818181817,\n \"acc_stderr\": 0.03225078108306289,\n\ \ \"acc_norm\": 0.21818181818181817,\n \"acc_norm_stderr\": 0.03225078108306289\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.2828282828282828,\n \"acc_stderr\": 0.03208779558786752,\n \"\ acc_norm\": 0.2828282828282828,\n \"acc_norm_stderr\": 0.03208779558786752\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.35233160621761656,\n \"acc_stderr\": 0.034474782864143586,\n\ \ \"acc_norm\": 0.35233160621761656,\n \"acc_norm_stderr\": 0.034474782864143586\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.2846153846153846,\n \"acc_stderr\": 0.0228783227997063,\n \ \ \"acc_norm\": 0.2846153846153846,\n \"acc_norm_stderr\": 0.0228783227997063\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.27037037037037037,\n \"acc_stderr\": 0.027080372815145668,\n \ \ \"acc_norm\": 0.27037037037037037,\n \"acc_norm_stderr\": 0.027080372815145668\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.24369747899159663,\n \"acc_stderr\": 0.02788682807838057,\n\ \ \"acc_norm\": 0.24369747899159663,\n \"acc_norm_stderr\": 0.02788682807838057\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.271523178807947,\n \"acc_stderr\": 0.03631329803969653,\n \"acc_norm\"\ : 0.271523178807947,\n \"acc_norm_stderr\": 0.03631329803969653\n },\n\ \ \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.3100917431192661,\n\ \ \"acc_stderr\": 0.019830849684439742,\n \"acc_norm\": 0.3100917431192661,\n\ \ \"acc_norm_stderr\": 0.019830849684439742\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\ : {\n \"acc\": 0.4351851851851852,\n \"acc_stderr\": 0.033812000056435254,\n\ \ \"acc_norm\": 0.4351851851851852,\n \"acc_norm_stderr\": 0.033812000056435254\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.25,\n \"acc_stderr\": 0.03039153369274154,\n \"acc_norm\": 0.25,\n\ \ \"acc_norm_stderr\": 0.03039153369274154\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\ : {\n \"acc\": 0.270042194092827,\n \"acc_stderr\": 0.028900721906293426,\n\ \ \"acc_norm\": 0.270042194092827,\n \"acc_norm_stderr\": 0.028900721906293426\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.17040358744394618,\n\ \ \"acc_stderr\": 0.025234593447136165,\n \"acc_norm\": 0.17040358744394618,\n\ \ \"acc_norm_stderr\": 0.025234593447136165\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.22137404580152673,\n \"acc_stderr\": 0.036412970813137276,\n\ \ \"acc_norm\": 0.22137404580152673,\n \"acc_norm_stderr\": 0.036412970813137276\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.19834710743801653,\n \"acc_stderr\": 0.03640118271990945,\n \"\ acc_norm\": 0.19834710743801653,\n \"acc_norm_stderr\": 0.03640118271990945\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.2777777777777778,\n\ \ \"acc_stderr\": 0.043300437496507416,\n \"acc_norm\": 0.2777777777777778,\n\ \ \"acc_norm_stderr\": 0.043300437496507416\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.3006134969325153,\n \"acc_stderr\": 0.03602511318806771,\n\ \ \"acc_norm\": 0.3006134969325153,\n \"acc_norm_stderr\": 0.03602511318806771\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.2767857142857143,\n\ \ \"acc_stderr\": 0.042466243366976256,\n \"acc_norm\": 0.2767857142857143,\n\ \ \"acc_norm_stderr\": 0.042466243366976256\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.23300970873786409,\n \"acc_stderr\": 0.04185832598928315,\n\ \ \"acc_norm\": 0.23300970873786409,\n \"acc_norm_stderr\": 0.04185832598928315\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.24786324786324787,\n\ \ \"acc_stderr\": 0.028286324075564407,\n \"acc_norm\": 0.24786324786324787,\n\ \ \"acc_norm_stderr\": 0.028286324075564407\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.22,\n \"acc_stderr\": 0.041633319989322695,\n \ \ \"acc_norm\": 0.22,\n \"acc_norm_stderr\": 0.041633319989322695\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.26309067688378035,\n\ \ \"acc_stderr\": 0.015745497169049053,\n \"acc_norm\": 0.26309067688378035,\n\ \ \"acc_norm_stderr\": 0.015745497169049053\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.20809248554913296,\n \"acc_stderr\": 0.0218552552634218,\n\ \ \"acc_norm\": 0.20809248554913296,\n \"acc_norm_stderr\": 0.0218552552634218\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.24692737430167597,\n\ \ \"acc_stderr\": 0.014422292204808835,\n \"acc_norm\": 0.24692737430167597,\n\ \ \"acc_norm_stderr\": 0.014422292204808835\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.21568627450980393,\n \"acc_stderr\": 0.02355083135199509,\n\ \ \"acc_norm\": 0.21568627450980393,\n \"acc_norm_stderr\": 0.02355083135199509\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.2733118971061093,\n\ \ \"acc_stderr\": 0.02531176597542611,\n \"acc_norm\": 0.2733118971061093,\n\ \ \"acc_norm_stderr\": 0.02531176597542611\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.2222222222222222,\n \"acc_stderr\": 0.02313237623454334,\n\ \ \"acc_norm\": 0.2222222222222222,\n \"acc_norm_stderr\": 0.02313237623454334\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.2730496453900709,\n \"acc_stderr\": 0.026577860943307857,\n \ \ \"acc_norm\": 0.2730496453900709,\n \"acc_norm_stderr\": 0.026577860943307857\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.2457627118644068,\n\ \ \"acc_stderr\": 0.010996156635142692,\n \"acc_norm\": 0.2457627118644068,\n\ \ \"acc_norm_stderr\": 0.010996156635142692\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.22794117647058823,\n \"acc_stderr\": 0.025483081468029804,\n\ \ \"acc_norm\": 0.22794117647058823,\n \"acc_norm_stderr\": 0.025483081468029804\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.2777777777777778,\n \"acc_stderr\": 0.01812022425148458,\n \ \ \"acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.01812022425148458\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.20909090909090908,\n\ \ \"acc_stderr\": 0.038950910157241364,\n \"acc_norm\": 0.20909090909090908,\n\ \ \"acc_norm_stderr\": 0.038950910157241364\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.18775510204081633,\n \"acc_stderr\": 0.02500025603954621,\n\ \ \"acc_norm\": 0.18775510204081633,\n \"acc_norm_stderr\": 0.02500025603954621\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.263681592039801,\n\ \ \"acc_stderr\": 0.031157150869355558,\n \"acc_norm\": 0.263681592039801,\n\ \ \"acc_norm_stderr\": 0.031157150869355558\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.2,\n \"acc_stderr\": 0.040201512610368466,\n \ \ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.040201512610368466\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.2469879518072289,\n\ \ \"acc_stderr\": 0.03357351982064536,\n \"acc_norm\": 0.2469879518072289,\n\ \ \"acc_norm_stderr\": 0.03357351982064536\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.22807017543859648,\n \"acc_stderr\": 0.03218093795602357,\n\ \ \"acc_norm\": 0.22807017543859648,\n \"acc_norm_stderr\": 0.03218093795602357\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.26193390452876375,\n\ \ \"mc1_stderr\": 0.015392118805015025,\n \"mc2\": 0.43479871223663846,\n\ \ \"mc2_stderr\": 0.015180815930542027\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.49329123914759276,\n \"acc_stderr\": 0.014051220692330346\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.008339651250947688,\n \ \ \"acc_stderr\": 0.002504942226860537\n }\n}\n```" repo_url: https://huggingface.co/bit-dny/MindLLM 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_27T12_33_52.223530 path: - '**/details_harness|arc:challenge|25_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-27T12-33-52.223530.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|gsm8k|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hellaswag|10_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-27T12-33-52.223530.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-management|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-27T12-33-52.223530.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|truthfulqa:mc|0_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-27T12-33-52.223530.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_27T12_33_52.223530 path: - '**/details_harness|winogrande|5_2023-12-27T12-33-52.223530.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-27T12-33-52.223530.parquet' - config_name: results data_files: - split: 2023_12_27T12_33_52.223530 path: - results_2023-12-27T12-33-52.223530.parquet - split: latest path: - results_2023-12-27T12-33-52.223530.parquet --- # Dataset Card for Evaluation run of bit-dny/MindLLM <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [bit-dny/MindLLM](https://huggingface.co/bit-dny/MindLLM) 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_bit-dny__MindLLM", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-27T12:33:52.223530](https://huggingface.co/datasets/open-llm-leaderboard/details_bit-dny__MindLLM/blob/main/results_2023-12-27T12-33-52.223530.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": 0.2547315459012399, "acc_stderr": 0.030757121924893716, "acc_norm": 0.2559855532831359, "acc_norm_stderr": 0.03153175700940631, "mc1": 0.26193390452876375, "mc1_stderr": 0.015392118805015025, "mc2": 0.43479871223663846, "mc2_stderr": 0.015180815930542027 }, "harness|arc:challenge|25": { "acc": 0.19539249146757678, "acc_stderr": 0.011586907189952911, "acc_norm": 0.22440273037542663, "acc_norm_stderr": 0.012191404938603838 }, "harness|hellaswag|10": { "acc": 0.30392352121091415, "acc_stderr": 0.004590100050198833, "acc_norm": 0.34106751643098987, "acc_norm_stderr": 0.004730991357194287 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.23, "acc_stderr": 0.042295258468165044, "acc_norm": 0.23, "acc_norm_stderr": 0.042295258468165044 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.24444444444444444, "acc_stderr": 0.03712537833614866, "acc_norm": 0.24444444444444444, "acc_norm_stderr": 0.03712537833614866 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.20394736842105263, "acc_stderr": 0.0327900040631005, "acc_norm": 0.20394736842105263, "acc_norm_stderr": 0.0327900040631005 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.26, "acc_stderr": 0.044084400227680794, "acc_norm": 0.26, "acc_norm_stderr": 0.044084400227680794 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.27169811320754716, "acc_stderr": 0.027377706624670713, "acc_norm": 0.27169811320754716, "acc_norm_stderr": 0.027377706624670713 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2916666666666667, "acc_stderr": 0.03800968060554858, "acc_norm": 0.2916666666666667, "acc_norm_stderr": 0.03800968060554858 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.2, "acc_stderr": 0.040201512610368445, "acc_norm": 0.2, "acc_norm_stderr": 0.040201512610368445 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.23121387283236994, "acc_stderr": 0.03214737302029471, "acc_norm": 0.23121387283236994, "acc_norm_stderr": 0.03214737302029471 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.17647058823529413, "acc_stderr": 0.0379328118530781, "acc_norm": 0.17647058823529413, "acc_norm_stderr": 0.0379328118530781 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.18, "acc_stderr": 0.038612291966536955, "acc_norm": 0.18, "acc_norm_stderr": 0.038612291966536955 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.2851063829787234, "acc_stderr": 0.02951319662553935, "acc_norm": 0.2851063829787234, "acc_norm_stderr": 0.02951319662553935 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2631578947368421, "acc_stderr": 0.041424397194893624, "acc_norm": 0.2631578947368421, "acc_norm_stderr": 0.041424397194893624 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.27586206896551724, "acc_stderr": 0.037245636197746325, "acc_norm": 0.27586206896551724, "acc_norm_stderr": 0.037245636197746325 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.26455026455026454, "acc_stderr": 0.022717467897708617, "acc_norm": 0.26455026455026454, "acc_norm_stderr": 0.022717467897708617 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.15079365079365079, "acc_stderr": 0.03200686497287394, "acc_norm": 0.15079365079365079, "acc_norm_stderr": 0.03200686497287394 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.23870967741935484, "acc_stderr": 0.024251071262208837, "acc_norm": 0.23870967741935484, "acc_norm_stderr": 0.024251071262208837 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.2955665024630542, "acc_stderr": 0.032104944337514575, "acc_norm": 0.2955665024630542, "acc_norm_stderr": 0.032104944337514575 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.21818181818181817, "acc_stderr": 0.03225078108306289, "acc_norm": 0.21818181818181817, "acc_norm_stderr": 0.03225078108306289 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.2828282828282828, "acc_stderr": 0.03208779558786752, "acc_norm": 0.2828282828282828, "acc_norm_stderr": 0.03208779558786752 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.35233160621761656, "acc_stderr": 0.034474782864143586, "acc_norm": 0.35233160621761656, "acc_norm_stderr": 0.034474782864143586 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.2846153846153846, "acc_stderr": 0.0228783227997063, "acc_norm": 0.2846153846153846, "acc_norm_stderr": 0.0228783227997063 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.27037037037037037, "acc_stderr": 0.027080372815145668, "acc_norm": 0.27037037037037037, "acc_norm_stderr": 0.027080372815145668 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.24369747899159663, "acc_stderr": 0.02788682807838057, "acc_norm": 0.24369747899159663, "acc_norm_stderr": 0.02788682807838057 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.271523178807947, "acc_stderr": 0.03631329803969653, "acc_norm": 0.271523178807947, "acc_norm_stderr": 0.03631329803969653 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.3100917431192661, "acc_stderr": 0.019830849684439742, "acc_norm": 0.3100917431192661, "acc_norm_stderr": 0.019830849684439742 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.4351851851851852, "acc_stderr": 0.033812000056435254, "acc_norm": 0.4351851851851852, "acc_norm_stderr": 0.033812000056435254 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.25, "acc_stderr": 0.03039153369274154, "acc_norm": 0.25, "acc_norm_stderr": 0.03039153369274154 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.270042194092827, "acc_stderr": 0.028900721906293426, "acc_norm": 0.270042194092827, "acc_norm_stderr": 0.028900721906293426 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.17040358744394618, "acc_stderr": 0.025234593447136165, "acc_norm": 0.17040358744394618, "acc_norm_stderr": 0.025234593447136165 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.22137404580152673, "acc_stderr": 0.036412970813137276, "acc_norm": 0.22137404580152673, "acc_norm_stderr": 0.036412970813137276 }, "harness|hendrycksTest-international_law|5": { "acc": 0.19834710743801653, "acc_stderr": 0.03640118271990945, "acc_norm": 0.19834710743801653, "acc_norm_stderr": 0.03640118271990945 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.2777777777777778, "acc_stderr": 0.043300437496507416, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.043300437496507416 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.3006134969325153, "acc_stderr": 0.03602511318806771, "acc_norm": 0.3006134969325153, "acc_norm_stderr": 0.03602511318806771 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.2767857142857143, "acc_stderr": 0.042466243366976256, "acc_norm": 0.2767857142857143, "acc_norm_stderr": 0.042466243366976256 }, "harness|hendrycksTest-management|5": { "acc": 0.23300970873786409, "acc_stderr": 0.04185832598928315, "acc_norm": 0.23300970873786409, "acc_norm_stderr": 0.04185832598928315 }, "harness|hendrycksTest-marketing|5": { "acc": 0.24786324786324787, "acc_stderr": 0.028286324075564407, "acc_norm": 0.24786324786324787, "acc_norm_stderr": 0.028286324075564407 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.22, "acc_stderr": 0.041633319989322695, "acc_norm": 0.22, "acc_norm_stderr": 0.041633319989322695 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.26309067688378035, "acc_stderr": 0.015745497169049053, "acc_norm": 0.26309067688378035, "acc_norm_stderr": 0.015745497169049053 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.20809248554913296, "acc_stderr": 0.0218552552634218, "acc_norm": 0.20809248554913296, "acc_norm_stderr": 0.0218552552634218 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.24692737430167597, "acc_stderr": 0.014422292204808835, "acc_norm": 0.24692737430167597, "acc_norm_stderr": 0.014422292204808835 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.21568627450980393, "acc_stderr": 0.02355083135199509, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.02355083135199509 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.2733118971061093, "acc_stderr": 0.02531176597542611, "acc_norm": 0.2733118971061093, "acc_norm_stderr": 0.02531176597542611 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.2222222222222222, "acc_stderr": 0.02313237623454334, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.02313237623454334 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.2730496453900709, "acc_stderr": 0.026577860943307857, "acc_norm": 0.2730496453900709, "acc_norm_stderr": 0.026577860943307857 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.2457627118644068, "acc_stderr": 0.010996156635142692, "acc_norm": 0.2457627118644068, "acc_norm_stderr": 0.010996156635142692 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.22794117647058823, "acc_stderr": 0.025483081468029804, "acc_norm": 0.22794117647058823, "acc_norm_stderr": 0.025483081468029804 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.2777777777777778, "acc_stderr": 0.01812022425148458, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.01812022425148458 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.20909090909090908, "acc_stderr": 0.038950910157241364, "acc_norm": 0.20909090909090908, "acc_norm_stderr": 0.038950910157241364 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.18775510204081633, "acc_stderr": 0.02500025603954621, "acc_norm": 0.18775510204081633, "acc_norm_stderr": 0.02500025603954621 }, "harness|hendrycksTest-sociology|5": { "acc": 0.263681592039801, "acc_stderr": 0.031157150869355558, "acc_norm": 0.263681592039801, "acc_norm_stderr": 0.031157150869355558 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.2, "acc_stderr": 0.040201512610368466, "acc_norm": 0.2, "acc_norm_stderr": 0.040201512610368466 }, "harness|hendrycksTest-virology|5": { "acc": 0.2469879518072289, "acc_stderr": 0.03357351982064536, "acc_norm": 0.2469879518072289, "acc_norm_stderr": 0.03357351982064536 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.22807017543859648, "acc_stderr": 0.03218093795602357, "acc_norm": 0.22807017543859648, "acc_norm_stderr": 0.03218093795602357 }, "harness|truthfulqa:mc|0": { "mc1": 0.26193390452876375, "mc1_stderr": 0.015392118805015025, "mc2": 0.43479871223663846, "mc2_stderr": 0.015180815930542027 }, "harness|winogrande|5": { "acc": 0.49329123914759276, "acc_stderr": 0.014051220692330346 }, "harness|gsm8k|5": { "acc": 0.008339651250947688, "acc_stderr": 0.002504942226860537 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
lei1211/simple_show
--- license: apache-2.0 ---
roa7n/patched_test_p_40_f_membrane_m1_predictions
--- dataset_info: features: - name: id dtype: string - name: sequence_str dtype: string - name: label dtype: int64 - name: m1_preds dtype: float32 splits: - name: train num_bytes: 1959469283 num_examples: 3134581 download_size: 165870843 dataset_size: 1959469283 --- # Dataset Card for "patched_test_p_40_f_membrane_m1_predictions" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
AdapterOcean/python-code-instructions-18k-alpaca-standardized_cluster_9
--- dataset_info: features: - name: text dtype: string - name: conversation_id dtype: int64 - name: embedding sequence: float64 - name: cluster dtype: int64 splits: - name: train num_bytes: 27114194 num_examples: 3146 download_size: 6998532 dataset_size: 27114194 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "python-code-instructions-18k-alpaca-standardized_cluster_9" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
mangoo111/stt_datasets_mixed
--- dataset_info: features: - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 6146981696 num_examples: 6400 - name: test num_bytes: 768372824 num_examples: 800 - name: valid num_bytes: 768373560 num_examples: 800 download_size: 869391895 dataset_size: 7683728080 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: valid path: data/valid-* ---
Adeeb-qu/New-grooul
--- license: openrail ---
open-llm-leaderboard/details_mediocredev__open-llama-3b-v2-instruct
--- pretty_name: Evaluation run of mediocredev/open-llama-3b-v2-instruct dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mediocredev/open-llama-3b-v2-instruct](https://huggingface.co/mediocredev/open-llama-3b-v2-instruct)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_mediocredev__open-llama-3b-v2-instruct\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-16T15:28:20.399841](https://huggingface.co/datasets/open-llm-leaderboard/details_mediocredev__open-llama-3b-v2-instruct/blob/main/results_2023-12-16T15-28-20.399841.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\": 0.3958981300034306,\n\ \ \"acc_stderr\": 0.034198998112262805,\n \"acc_norm\": 0.4018856544108267,\n\ \ \"acc_norm_stderr\": 0.035129135992579406,\n \"mc1\": 0.2252141982864137,\n\ \ \"mc1_stderr\": 0.014623240768023498,\n \"mc2\": 0.3795634078796446,\n\ \ \"mc2_stderr\": 0.014273839655133331\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.35409556313993173,\n \"acc_stderr\": 0.01397545412275655,\n\ \ \"acc_norm\": 0.3848122866894198,\n \"acc_norm_stderr\": 0.014218371065251104\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5142401911969727,\n\ \ \"acc_stderr\": 0.0049877573147698445,\n \"acc_norm\": 0.7024497112129058,\n\ \ \"acc_norm_stderr\": 0.004562462665505218\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.27,\n \"acc_stderr\": 0.044619604333847415,\n \ \ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.044619604333847415\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.45185185185185184,\n\ \ \"acc_stderr\": 0.04299268905480864,\n \"acc_norm\": 0.45185185185185184,\n\ \ \"acc_norm_stderr\": 0.04299268905480864\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.3815789473684211,\n \"acc_stderr\": 0.03953173377749194,\n\ \ \"acc_norm\": 0.3815789473684211,\n \"acc_norm_stderr\": 0.03953173377749194\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.41,\n\ \ \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.41,\n \ \ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.4377358490566038,\n \"acc_stderr\": 0.03053333843046751,\n\ \ \"acc_norm\": 0.4377358490566038,\n \"acc_norm_stderr\": 0.03053333843046751\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.3680555555555556,\n\ \ \"acc_stderr\": 0.04032999053960719,\n \"acc_norm\": 0.3680555555555556,\n\ \ \"acc_norm_stderr\": 0.04032999053960719\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \"acc_norm\": 0.35,\n\ \ \"acc_norm_stderr\": 0.0479372485441102\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.43352601156069365,\n\ \ \"acc_stderr\": 0.03778621079092055,\n \"acc_norm\": 0.43352601156069365,\n\ \ \"acc_norm_stderr\": 0.03778621079092055\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.19607843137254902,\n \"acc_stderr\": 0.03950581861179961,\n\ \ \"acc_norm\": 0.19607843137254902,\n \"acc_norm_stderr\": 0.03950581861179961\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\": 0.48,\n\ \ \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.3659574468085106,\n \"acc_stderr\": 0.0314895582974553,\n\ \ \"acc_norm\": 0.3659574468085106,\n \"acc_norm_stderr\": 0.0314895582974553\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2894736842105263,\n\ \ \"acc_stderr\": 0.042663394431593935,\n \"acc_norm\": 0.2894736842105263,\n\ \ \"acc_norm_stderr\": 0.042663394431593935\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.3931034482758621,\n \"acc_stderr\": 0.0407032901370707,\n\ \ \"acc_norm\": 0.3931034482758621,\n \"acc_norm_stderr\": 0.0407032901370707\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.2698412698412698,\n \"acc_stderr\": 0.022860838309232072,\n \"\ acc_norm\": 0.2698412698412698,\n \"acc_norm_stderr\": 0.022860838309232072\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.30158730158730157,\n\ \ \"acc_stderr\": 0.041049472699033945,\n \"acc_norm\": 0.30158730158730157,\n\ \ \"acc_norm_stderr\": 0.041049472699033945\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.047609522856952365,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.047609522856952365\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.4161290322580645,\n \"acc_stderr\": 0.028040981380761547,\n \"\ acc_norm\": 0.4161290322580645,\n \"acc_norm_stderr\": 0.028040981380761547\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.2660098522167488,\n \"acc_stderr\": 0.03108982600293753,\n \"\ acc_norm\": 0.2660098522167488,\n \"acc_norm_stderr\": 0.03108982600293753\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939098,\n \"acc_norm\"\ : 0.37,\n \"acc_norm_stderr\": 0.04852365870939098\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.4484848484848485,\n \"acc_stderr\": 0.038835659779569286,\n\ \ \"acc_norm\": 0.4484848484848485,\n \"acc_norm_stderr\": 0.038835659779569286\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.5454545454545454,\n \"acc_stderr\": 0.03547601494006937,\n \"\ acc_norm\": 0.5454545454545454,\n \"acc_norm_stderr\": 0.03547601494006937\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.48186528497409326,\n \"acc_stderr\": 0.03606065001832919,\n\ \ \"acc_norm\": 0.48186528497409326,\n \"acc_norm_stderr\": 0.03606065001832919\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.35128205128205126,\n \"acc_stderr\": 0.024203665177902796,\n\ \ \"acc_norm\": 0.35128205128205126,\n \"acc_norm_stderr\": 0.024203665177902796\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.25925925925925924,\n \"acc_stderr\": 0.026719240783712166,\n \ \ \"acc_norm\": 0.25925925925925924,\n \"acc_norm_stderr\": 0.026719240783712166\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.35714285714285715,\n \"acc_stderr\": 0.031124619309328177,\n\ \ \"acc_norm\": 0.35714285714285715,\n \"acc_norm_stderr\": 0.031124619309328177\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.2980132450331126,\n \"acc_stderr\": 0.037345356767871984,\n \"\ acc_norm\": 0.2980132450331126,\n \"acc_norm_stderr\": 0.037345356767871984\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.4972477064220184,\n \"acc_stderr\": 0.02143699835976532,\n \"\ acc_norm\": 0.4972477064220184,\n \"acc_norm_stderr\": 0.02143699835976532\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.3055555555555556,\n \"acc_stderr\": 0.03141554629402544,\n \"\ acc_norm\": 0.3055555555555556,\n \"acc_norm_stderr\": 0.03141554629402544\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.46078431372549017,\n \"acc_stderr\": 0.03498501649369527,\n \"\ acc_norm\": 0.46078431372549017,\n \"acc_norm_stderr\": 0.03498501649369527\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.5611814345991561,\n \"acc_stderr\": 0.032302649315470375,\n \ \ \"acc_norm\": 0.5611814345991561,\n \"acc_norm_stderr\": 0.032302649315470375\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.4977578475336323,\n\ \ \"acc_stderr\": 0.033557465352232634,\n \"acc_norm\": 0.4977578475336323,\n\ \ \"acc_norm_stderr\": 0.033557465352232634\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.46564885496183206,\n \"acc_stderr\": 0.04374928560599738,\n\ \ \"acc_norm\": 0.46564885496183206,\n \"acc_norm_stderr\": 0.04374928560599738\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.47107438016528924,\n \"acc_stderr\": 0.04556710331269498,\n \"\ acc_norm\": 0.47107438016528924,\n \"acc_norm_stderr\": 0.04556710331269498\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.4166666666666667,\n\ \ \"acc_stderr\": 0.04766075165356461,\n \"acc_norm\": 0.4166666666666667,\n\ \ \"acc_norm_stderr\": 0.04766075165356461\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.4110429447852761,\n \"acc_stderr\": 0.038656978537853624,\n\ \ \"acc_norm\": 0.4110429447852761,\n \"acc_norm_stderr\": 0.038656978537853624\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.3125,\n\ \ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\ \ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.5533980582524272,\n \"acc_stderr\": 0.04922424153458933,\n\ \ \"acc_norm\": 0.5533980582524272,\n \"acc_norm_stderr\": 0.04922424153458933\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.5341880341880342,\n\ \ \"acc_stderr\": 0.03267942734081228,\n \"acc_norm\": 0.5341880341880342,\n\ \ \"acc_norm_stderr\": 0.03267942734081228\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.5261813537675607,\n\ \ \"acc_stderr\": 0.01785543455404199,\n \"acc_norm\": 0.5261813537675607,\n\ \ \"acc_norm_stderr\": 0.01785543455404199\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.4277456647398844,\n \"acc_stderr\": 0.02663653974111608,\n\ \ \"acc_norm\": 0.4277456647398844,\n \"acc_norm_stderr\": 0.02663653974111608\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.25139664804469275,\n\ \ \"acc_stderr\": 0.014508979453553984,\n \"acc_norm\": 0.25139664804469275,\n\ \ \"acc_norm_stderr\": 0.014508979453553984\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.42810457516339867,\n \"acc_stderr\": 0.028332397483664274,\n\ \ \"acc_norm\": 0.42810457516339867,\n \"acc_norm_stderr\": 0.028332397483664274\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.40192926045016075,\n\ \ \"acc_stderr\": 0.027846476005930473,\n \"acc_norm\": 0.40192926045016075,\n\ \ \"acc_norm_stderr\": 0.027846476005930473\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.41358024691358025,\n \"acc_stderr\": 0.027402042040269952,\n\ \ \"acc_norm\": 0.41358024691358025,\n \"acc_norm_stderr\": 0.027402042040269952\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.3049645390070922,\n \"acc_stderr\": 0.027464708442022128,\n \ \ \"acc_norm\": 0.3049645390070922,\n \"acc_norm_stderr\": 0.027464708442022128\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.30964797913950454,\n\ \ \"acc_stderr\": 0.01180859826250332,\n \"acc_norm\": 0.30964797913950454,\n\ \ \"acc_norm_stderr\": 0.01180859826250332\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.3786764705882353,\n \"acc_stderr\": 0.029465133639776132,\n\ \ \"acc_norm\": 0.3786764705882353,\n \"acc_norm_stderr\": 0.029465133639776132\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.36437908496732024,\n \"acc_stderr\": 0.019469518221573702,\n \ \ \"acc_norm\": 0.36437908496732024,\n \"acc_norm_stderr\": 0.019469518221573702\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.5,\n\ \ \"acc_stderr\": 0.04789131426105757,\n \"acc_norm\": 0.5,\n \ \ \"acc_norm_stderr\": 0.04789131426105757\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.32653061224489793,\n \"acc_stderr\": 0.030021056238440286,\n\ \ \"acc_norm\": 0.32653061224489793,\n \"acc_norm_stderr\": 0.030021056238440286\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.4527363184079602,\n\ \ \"acc_stderr\": 0.035197027175769155,\n \"acc_norm\": 0.4527363184079602,\n\ \ \"acc_norm_stderr\": 0.035197027175769155\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.6,\n \"acc_stderr\": 0.049236596391733084,\n \ \ \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.049236596391733084\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.39156626506024095,\n\ \ \"acc_stderr\": 0.03799857454479636,\n \"acc_norm\": 0.39156626506024095,\n\ \ \"acc_norm_stderr\": 0.03799857454479636\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.49707602339181284,\n \"acc_stderr\": 0.03834759370936839,\n\ \ \"acc_norm\": 0.49707602339181284,\n \"acc_norm_stderr\": 0.03834759370936839\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2252141982864137,\n\ \ \"mc1_stderr\": 0.014623240768023498,\n \"mc2\": 0.3795634078796446,\n\ \ \"mc2_stderr\": 0.014273839655133331\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.6574585635359116,\n \"acc_stderr\": 0.013337483579075923\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n }\n}\n```" repo_url: https://huggingface.co/mediocredev/open-llama-3b-v2-instruct 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_16T15_28_20.399841 path: - '**/details_harness|arc:challenge|25_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-16T15-28-20.399841.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|gsm8k|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hellaswag|10_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-16T15-28-20.399841.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-management|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-16T15-28-20.399841.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|truthfulqa:mc|0_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-16T15-28-20.399841.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_16T15_28_20.399841 path: - '**/details_harness|winogrande|5_2023-12-16T15-28-20.399841.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-16T15-28-20.399841.parquet' - config_name: results data_files: - split: 2023_12_16T15_28_20.399841 path: - results_2023-12-16T15-28-20.399841.parquet - split: latest path: - results_2023-12-16T15-28-20.399841.parquet --- # Dataset Card for Evaluation run of mediocredev/open-llama-3b-v2-instruct <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [mediocredev/open-llama-3b-v2-instruct](https://huggingface.co/mediocredev/open-llama-3b-v2-instruct) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_mediocredev__open-llama-3b-v2-instruct", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-16T15:28:20.399841](https://huggingface.co/datasets/open-llm-leaderboard/details_mediocredev__open-llama-3b-v2-instruct/blob/main/results_2023-12-16T15-28-20.399841.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": 0.3958981300034306, "acc_stderr": 0.034198998112262805, "acc_norm": 0.4018856544108267, "acc_norm_stderr": 0.035129135992579406, "mc1": 0.2252141982864137, "mc1_stderr": 0.014623240768023498, "mc2": 0.3795634078796446, "mc2_stderr": 0.014273839655133331 }, "harness|arc:challenge|25": { "acc": 0.35409556313993173, "acc_stderr": 0.01397545412275655, "acc_norm": 0.3848122866894198, "acc_norm_stderr": 0.014218371065251104 }, "harness|hellaswag|10": { "acc": 0.5142401911969727, "acc_stderr": 0.0049877573147698445, "acc_norm": 0.7024497112129058, "acc_norm_stderr": 0.004562462665505218 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.27, "acc_stderr": 0.044619604333847415, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847415 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.45185185185185184, "acc_stderr": 0.04299268905480864, "acc_norm": 0.45185185185185184, "acc_norm_stderr": 0.04299268905480864 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.3815789473684211, "acc_stderr": 0.03953173377749194, "acc_norm": 0.3815789473684211, "acc_norm_stderr": 0.03953173377749194 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.4377358490566038, "acc_stderr": 0.03053333843046751, "acc_norm": 0.4377358490566038, "acc_norm_stderr": 0.03053333843046751 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.3680555555555556, "acc_stderr": 0.04032999053960719, "acc_norm": 0.3680555555555556, "acc_norm_stderr": 0.04032999053960719 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.43352601156069365, "acc_stderr": 0.03778621079092055, "acc_norm": 0.43352601156069365, "acc_norm_stderr": 0.03778621079092055 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.19607843137254902, "acc_stderr": 0.03950581861179961, "acc_norm": 0.19607843137254902, "acc_norm_stderr": 0.03950581861179961 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3659574468085106, "acc_stderr": 0.0314895582974553, "acc_norm": 0.3659574468085106, "acc_norm_stderr": 0.0314895582974553 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2894736842105263, "acc_stderr": 0.042663394431593935, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.042663394431593935 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.3931034482758621, "acc_stderr": 0.0407032901370707, "acc_norm": 0.3931034482758621, "acc_norm_stderr": 0.0407032901370707 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2698412698412698, "acc_stderr": 0.022860838309232072, "acc_norm": 0.2698412698412698, "acc_norm_stderr": 0.022860838309232072 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.30158730158730157, "acc_stderr": 0.041049472699033945, "acc_norm": 0.30158730158730157, "acc_norm_stderr": 0.041049472699033945 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.34, "acc_stderr": 0.047609522856952365, "acc_norm": 0.34, "acc_norm_stderr": 0.047609522856952365 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.4161290322580645, "acc_stderr": 0.028040981380761547, "acc_norm": 0.4161290322580645, "acc_norm_stderr": 0.028040981380761547 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.2660098522167488, "acc_stderr": 0.03108982600293753, "acc_norm": 0.2660098522167488, "acc_norm_stderr": 0.03108982600293753 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.37, "acc_stderr": 0.04852365870939098, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939098 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.4484848484848485, "acc_stderr": 0.038835659779569286, "acc_norm": 0.4484848484848485, "acc_norm_stderr": 0.038835659779569286 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5454545454545454, "acc_stderr": 0.03547601494006937, "acc_norm": 0.5454545454545454, "acc_norm_stderr": 0.03547601494006937 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.48186528497409326, "acc_stderr": 0.03606065001832919, "acc_norm": 0.48186528497409326, "acc_norm_stderr": 0.03606065001832919 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.35128205128205126, "acc_stderr": 0.024203665177902796, "acc_norm": 0.35128205128205126, "acc_norm_stderr": 0.024203665177902796 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.25925925925925924, "acc_stderr": 0.026719240783712166, "acc_norm": 0.25925925925925924, "acc_norm_stderr": 0.026719240783712166 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.35714285714285715, "acc_stderr": 0.031124619309328177, "acc_norm": 0.35714285714285715, "acc_norm_stderr": 0.031124619309328177 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.2980132450331126, "acc_stderr": 0.037345356767871984, "acc_norm": 0.2980132450331126, "acc_norm_stderr": 0.037345356767871984 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.4972477064220184, "acc_stderr": 0.02143699835976532, "acc_norm": 0.4972477064220184, "acc_norm_stderr": 0.02143699835976532 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.3055555555555556, "acc_stderr": 0.03141554629402544, "acc_norm": 0.3055555555555556, "acc_norm_stderr": 0.03141554629402544 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.46078431372549017, "acc_stderr": 0.03498501649369527, "acc_norm": 0.46078431372549017, "acc_norm_stderr": 0.03498501649369527 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.5611814345991561, "acc_stderr": 0.032302649315470375, "acc_norm": 0.5611814345991561, "acc_norm_stderr": 0.032302649315470375 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.4977578475336323, "acc_stderr": 0.033557465352232634, "acc_norm": 0.4977578475336323, "acc_norm_stderr": 0.033557465352232634 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.46564885496183206, "acc_stderr": 0.04374928560599738, "acc_norm": 0.46564885496183206, "acc_norm_stderr": 0.04374928560599738 }, "harness|hendrycksTest-international_law|5": { "acc": 0.47107438016528924, "acc_stderr": 0.04556710331269498, "acc_norm": 0.47107438016528924, "acc_norm_stderr": 0.04556710331269498 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.4166666666666667, "acc_stderr": 0.04766075165356461, "acc_norm": 0.4166666666666667, "acc_norm_stderr": 0.04766075165356461 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.4110429447852761, "acc_stderr": 0.038656978537853624, "acc_norm": 0.4110429447852761, "acc_norm_stderr": 0.038656978537853624 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.3125, "acc_stderr": 0.043994650575715215, "acc_norm": 0.3125, "acc_norm_stderr": 0.043994650575715215 }, "harness|hendrycksTest-management|5": { "acc": 0.5533980582524272, "acc_stderr": 0.04922424153458933, "acc_norm": 0.5533980582524272, "acc_norm_stderr": 0.04922424153458933 }, "harness|hendrycksTest-marketing|5": { "acc": 0.5341880341880342, "acc_stderr": 0.03267942734081228, "acc_norm": 0.5341880341880342, "acc_norm_stderr": 0.03267942734081228 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.5261813537675607, "acc_stderr": 0.01785543455404199, "acc_norm": 0.5261813537675607, "acc_norm_stderr": 0.01785543455404199 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.4277456647398844, "acc_stderr": 0.02663653974111608, "acc_norm": 0.4277456647398844, "acc_norm_stderr": 0.02663653974111608 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.25139664804469275, "acc_stderr": 0.014508979453553984, "acc_norm": 0.25139664804469275, "acc_norm_stderr": 0.014508979453553984 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.42810457516339867, "acc_stderr": 0.028332397483664274, "acc_norm": 0.42810457516339867, "acc_norm_stderr": 0.028332397483664274 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.40192926045016075, "acc_stderr": 0.027846476005930473, "acc_norm": 0.40192926045016075, "acc_norm_stderr": 0.027846476005930473 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.41358024691358025, "acc_stderr": 0.027402042040269952, "acc_norm": 0.41358024691358025, "acc_norm_stderr": 0.027402042040269952 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.3049645390070922, "acc_stderr": 0.027464708442022128, "acc_norm": 0.3049645390070922, "acc_norm_stderr": 0.027464708442022128 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.30964797913950454, "acc_stderr": 0.01180859826250332, "acc_norm": 0.30964797913950454, "acc_norm_stderr": 0.01180859826250332 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.3786764705882353, "acc_stderr": 0.029465133639776132, "acc_norm": 0.3786764705882353, "acc_norm_stderr": 0.029465133639776132 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.36437908496732024, "acc_stderr": 0.019469518221573702, "acc_norm": 0.36437908496732024, "acc_norm_stderr": 0.019469518221573702 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.5, "acc_stderr": 0.04789131426105757, "acc_norm": 0.5, "acc_norm_stderr": 0.04789131426105757 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.32653061224489793, "acc_stderr": 0.030021056238440286, "acc_norm": 0.32653061224489793, "acc_norm_stderr": 0.030021056238440286 }, "harness|hendrycksTest-sociology|5": { "acc": 0.4527363184079602, "acc_stderr": 0.035197027175769155, "acc_norm": 0.4527363184079602, "acc_norm_stderr": 0.035197027175769155 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.6, "acc_stderr": 0.049236596391733084, "acc_norm": 0.6, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-virology|5": { "acc": 0.39156626506024095, "acc_stderr": 0.03799857454479636, "acc_norm": 0.39156626506024095, "acc_norm_stderr": 0.03799857454479636 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.49707602339181284, "acc_stderr": 0.03834759370936839, "acc_norm": 0.49707602339181284, "acc_norm_stderr": 0.03834759370936839 }, "harness|truthfulqa:mc|0": { "mc1": 0.2252141982864137, "mc1_stderr": 0.014623240768023498, "mc2": 0.3795634078796446, "mc2_stderr": 0.014273839655133331 }, "harness|winogrande|5": { "acc": 0.6574585635359116, "acc_stderr": 0.013337483579075923 }, "harness|gsm8k|5": { "acc": 0.0, "acc_stderr": 0.0 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
ohsuz/DACON_RAG
--- dataset_info: features: - name: id dtype: string - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 7091959 num_examples: 2576 download_size: 2570364 dataset_size: 7091959 configs: - config_name: default data_files: - split: train path: data/train-* ---
lewtun/top_quark_tagging_old
--- license: cc-by-4.0 ---
MeetX/mental-health-dataset-mistral7b-auto-tune
--- dataset_info: features: - name: text dtype: string - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 375246 num_examples: 172 download_size: 209156 dataset_size: 375246 configs: - config_name: default data_files: - split: train path: data/train-* ---
hotfinda/smithsonian_butterflies_subset
--- dataset_info: features: - name: image_url dtype: string - name: image_alt dtype: string - name: id dtype: string - name: name dtype: string - name: scientific_name dtype: string - name: gender dtype: string - name: taxonomy dtype: string - name: region dtype: string - name: locality dtype: string - name: date dtype: string - name: usnm_no dtype: string - name: guid dtype: string - name: edan_url dtype: string - name: source dtype: string - name: stage dtype: float64 - name: image dtype: image - name: image_hash dtype: string - name: sim_score dtype: float64 splits: - name: train num_bytes: 237753960.0 num_examples: 1000 download_size: 237446351 dataset_size: 237753960.0 --- # Dataset Card for "smithsonian_butterflies_subset" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_yunconglong__MoE_13B_DPO
--- pretty_name: Evaluation run of yunconglong/MoE_13B_DPO dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [yunconglong/MoE_13B_DPO](https://huggingface.co/yunconglong/MoE_13B_DPO) 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_yunconglong__MoE_13B_DPO\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-28T08:55:06.256687](https://huggingface.co/datasets/open-llm-leaderboard/details_yunconglong__MoE_13B_DPO/blob/main/results_2024-01-28T08-55-06.256687.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\": 0.6516933230862831,\n\ \ \"acc_stderr\": 0.03214433470973161,\n \"acc_norm\": 0.6507001593260299,\n\ \ \"acc_norm_stderr\": 0.03283113819359505,\n \"mc1\": 0.6364749082007344,\n\ \ \"mc1_stderr\": 0.016838862883965834,\n \"mc2\": 0.7846972943990677,\n\ \ \"mc2_stderr\": 0.013799810152287217\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.7201365187713311,\n \"acc_stderr\": 0.013119040897725923,\n\ \ \"acc_norm\": 0.7431740614334471,\n \"acc_norm_stderr\": 0.0127669237941168\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7226648078072098,\n\ \ \"acc_stderr\": 0.0044676841327724115,\n \"acc_norm\": 0.8939454291973711,\n\ \ \"acc_norm_stderr\": 0.0030727817579111268\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness|hendrycksTest-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\": 0.6578947368421053,\n \"acc_stderr\": 0.03860731599316092,\n\ \ \"acc_norm\": 0.6578947368421053,\n \"acc_norm_stderr\": 0.03860731599316092\n\ \ },\n \"harness|hendrycksTest-business_ethics|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-clinical_knowledge|5\"\ : {\n \"acc\": 0.7132075471698113,\n \"acc_stderr\": 0.02783491252754407,\n\ \ \"acc_norm\": 0.7132075471698113,\n \"acc_norm_stderr\": 0.02783491252754407\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7638888888888888,\n\ \ \"acc_stderr\": 0.03551446610810826,\n \"acc_norm\": 0.7638888888888888,\n\ \ \"acc_norm_stderr\": 0.03551446610810826\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956911,\n \ \ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956911\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.54,\n \"acc_stderr\": 0.05009082659620333,\n \"acc_norm\": 0.54,\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\": 0.6647398843930635,\n\ \ \"acc_stderr\": 0.03599586301247077,\n \"acc_norm\": 0.6647398843930635,\n\ \ \"acc_norm_stderr\": 0.03599586301247077\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.43137254901960786,\n \"acc_stderr\": 0.04928099597287534,\n\ \ \"acc_norm\": 0.43137254901960786,\n \"acc_norm_stderr\": 0.04928099597287534\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.74,\n \"acc_stderr\": 0.04408440022768078,\n \"acc_norm\": 0.74,\n\ \ \"acc_norm_stderr\": 0.04408440022768078\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5787234042553191,\n \"acc_stderr\": 0.03227834510146268,\n\ \ \"acc_norm\": 0.5787234042553191,\n \"acc_norm_stderr\": 0.03227834510146268\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4824561403508772,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.4824561403508772,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5724137931034483,\n \"acc_stderr\": 0.04122737111370332,\n\ \ \"acc_norm\": 0.5724137931034483,\n \"acc_norm_stderr\": 0.04122737111370332\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.42063492063492064,\n \"acc_stderr\": 0.025424835086924,\n \"acc_norm\"\ : 0.42063492063492064,\n \"acc_norm_stderr\": 0.025424835086924\n },\n\ \ \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4603174603174603,\n\ \ \"acc_stderr\": 0.04458029125470973,\n \"acc_norm\": 0.4603174603174603,\n\ \ \"acc_norm_stderr\": 0.04458029125470973\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621505,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621505\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7967741935483871,\n\ \ \"acc_stderr\": 0.022891687984554963,\n \"acc_norm\": 0.7967741935483871,\n\ \ \"acc_norm_stderr\": 0.022891687984554963\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.4876847290640394,\n \"acc_stderr\": 0.035169204442208966,\n\ \ \"acc_norm\": 0.4876847290640394,\n \"acc_norm_stderr\": 0.035169204442208966\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.74,\n \"acc_stderr\": 0.04408440022768079,\n \"acc_norm\"\ : 0.74,\n \"acc_norm_stderr\": 0.04408440022768079\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7757575757575758,\n \"acc_stderr\": 0.032568666616811015,\n\ \ \"acc_norm\": 0.7757575757575758,\n \"acc_norm_stderr\": 0.032568666616811015\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7727272727272727,\n \"acc_stderr\": 0.029857515673386414,\n \"\ acc_norm\": 0.7727272727272727,\n \"acc_norm_stderr\": 0.029857515673386414\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8860103626943006,\n \"acc_stderr\": 0.022935144053919436,\n\ \ \"acc_norm\": 0.8860103626943006,\n \"acc_norm_stderr\": 0.022935144053919436\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6743589743589744,\n \"acc_stderr\": 0.02375966576741229,\n \ \ \"acc_norm\": 0.6743589743589744,\n \"acc_norm_stderr\": 0.02375966576741229\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.34444444444444444,\n \"acc_stderr\": 0.028972648884844267,\n \ \ \"acc_norm\": 0.34444444444444444,\n \"acc_norm_stderr\": 0.028972648884844267\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6722689075630253,\n \"acc_stderr\": 0.03048991141767323,\n \ \ \"acc_norm\": 0.6722689075630253,\n \"acc_norm_stderr\": 0.03048991141767323\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.33112582781456956,\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\"\ : 0.8440366972477065,\n \"acc_stderr\": 0.01555580271359017,\n \"\ acc_norm\": 0.8440366972477065,\n \"acc_norm_stderr\": 0.01555580271359017\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5092592592592593,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.5092592592592593,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8235294117647058,\n \"acc_stderr\": 0.026756401538078962,\n \"\ acc_norm\": 0.8235294117647058,\n \"acc_norm_stderr\": 0.026756401538078962\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7932489451476793,\n \"acc_stderr\": 0.0263616516683891,\n \ \ \"acc_norm\": 0.7932489451476793,\n \"acc_norm_stderr\": 0.0263616516683891\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6860986547085202,\n\ \ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.6860986547085202,\n\ \ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7938931297709924,\n \"acc_stderr\": 0.03547771004159465,\n\ \ \"acc_norm\": 0.7938931297709924,\n \"acc_norm_stderr\": 0.03547771004159465\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.768595041322314,\n \"acc_stderr\": 0.03849856098794088,\n \"acc_norm\"\ : 0.768595041322314,\n \"acc_norm_stderr\": 0.03849856098794088\n },\n\ \ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7685185185185185,\n\ \ \"acc_stderr\": 0.04077494709252626,\n \"acc_norm\": 0.7685185185185185,\n\ \ \"acc_norm_stderr\": 0.04077494709252626\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7730061349693251,\n \"acc_stderr\": 0.03291099578615769,\n\ \ \"acc_norm\": 0.7730061349693251,\n \"acc_norm_stderr\": 0.03291099578615769\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.42857142857142855,\n\ \ \"acc_stderr\": 0.04697113923010212,\n \"acc_norm\": 0.42857142857142855,\n\ \ \"acc_norm_stderr\": 0.04697113923010212\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7669902912621359,\n \"acc_stderr\": 0.04185832598928315,\n\ \ \"acc_norm\": 0.7669902912621359,\n \"acc_norm_stderr\": 0.04185832598928315\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8846153846153846,\n\ \ \"acc_stderr\": 0.02093019318517933,\n \"acc_norm\": 0.8846153846153846,\n\ \ \"acc_norm_stderr\": 0.02093019318517933\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.74,\n \"acc_stderr\": 0.04408440022768079,\n \ \ \"acc_norm\": 0.74,\n \"acc_norm_stderr\": 0.04408440022768079\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8301404853128991,\n\ \ \"acc_stderr\": 0.013428186370608304,\n \"acc_norm\": 0.8301404853128991,\n\ \ \"acc_norm_stderr\": 0.013428186370608304\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7167630057803468,\n \"acc_stderr\": 0.02425790170532338,\n\ \ \"acc_norm\": 0.7167630057803468,\n \"acc_norm_stderr\": 0.02425790170532338\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.44581005586592176,\n\ \ \"acc_stderr\": 0.016623998513333106,\n \"acc_norm\": 0.44581005586592176,\n\ \ \"acc_norm_stderr\": 0.016623998513333106\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7287581699346405,\n \"acc_stderr\": 0.025457756696667874,\n\ \ \"acc_norm\": 0.7287581699346405,\n \"acc_norm_stderr\": 0.025457756696667874\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7009646302250804,\n\ \ \"acc_stderr\": 0.026003301117885135,\n \"acc_norm\": 0.7009646302250804,\n\ \ \"acc_norm_stderr\": 0.026003301117885135\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7438271604938271,\n \"acc_stderr\": 0.0242885336377261,\n\ \ \"acc_norm\": 0.7438271604938271,\n \"acc_norm_stderr\": 0.0242885336377261\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4929078014184397,\n \"acc_stderr\": 0.02982449855912901,\n \ \ \"acc_norm\": 0.4929078014184397,\n \"acc_norm_stderr\": 0.02982449855912901\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.46479791395045633,\n\ \ \"acc_stderr\": 0.012738547371303957,\n \"acc_norm\": 0.46479791395045633,\n\ \ \"acc_norm_stderr\": 0.012738547371303957\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6617647058823529,\n \"acc_stderr\": 0.028739328513983572,\n\ \ \"acc_norm\": 0.6617647058823529,\n \"acc_norm_stderr\": 0.028739328513983572\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.673202614379085,\n \"acc_stderr\": 0.0189754279205072,\n \ \ \"acc_norm\": 0.673202614379085,\n \"acc_norm_stderr\": 0.0189754279205072\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\": 0.7306122448979592,\n \"acc_stderr\": 0.02840125202902294,\n\ \ \"acc_norm\": 0.7306122448979592,\n \"acc_norm_stderr\": 0.02840125202902294\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8308457711442786,\n\ \ \"acc_stderr\": 0.02650859065623327,\n \"acc_norm\": 0.8308457711442786,\n\ \ \"acc_norm_stderr\": 0.02650859065623327\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.84,\n \"acc_stderr\": 0.03684529491774709,\n \ \ \"acc_norm\": 0.84,\n \"acc_norm_stderr\": 0.03684529491774709\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5421686746987951,\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\": 0.8421052631578947,\n \"acc_stderr\": 0.027966785859160893,\n\ \ \"acc_norm\": 0.8421052631578947,\n \"acc_norm_stderr\": 0.027966785859160893\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.6364749082007344,\n\ \ \"mc1_stderr\": 0.016838862883965834,\n \"mc2\": 0.7846972943990677,\n\ \ \"mc2_stderr\": 0.013799810152287217\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8800315706393055,\n \"acc_stderr\": 0.009131996995678647\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6762699014404853,\n \ \ \"acc_stderr\": 0.012888247397371141\n }\n}\n```" repo_url: https://huggingface.co/yunconglong/MoE_13B_DPO leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|arc:challenge|25_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-01-28T08-55-06.256687.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|gsm8k|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hellaswag|10_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-28T08-55-06.256687.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-management|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-virology|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-28T08-55-06.256687.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|truthfulqa:mc|0_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-01-28T08-55-06.256687.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_28T08_55_06.256687 path: - '**/details_harness|winogrande|5_2024-01-28T08-55-06.256687.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-01-28T08-55-06.256687.parquet' - config_name: results data_files: - split: 2024_01_28T08_55_06.256687 path: - results_2024-01-28T08-55-06.256687.parquet - split: latest path: - results_2024-01-28T08-55-06.256687.parquet --- # Dataset Card for Evaluation run of yunconglong/MoE_13B_DPO <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [yunconglong/MoE_13B_DPO](https://huggingface.co/yunconglong/MoE_13B_DPO) 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_yunconglong__MoE_13B_DPO", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-28T08:55:06.256687](https://huggingface.co/datasets/open-llm-leaderboard/details_yunconglong__MoE_13B_DPO/blob/main/results_2024-01-28T08-55-06.256687.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": 0.6516933230862831, "acc_stderr": 0.03214433470973161, "acc_norm": 0.6507001593260299, "acc_norm_stderr": 0.03283113819359505, "mc1": 0.6364749082007344, "mc1_stderr": 0.016838862883965834, "mc2": 0.7846972943990677, "mc2_stderr": 0.013799810152287217 }, "harness|arc:challenge|25": { "acc": 0.7201365187713311, "acc_stderr": 0.013119040897725923, "acc_norm": 0.7431740614334471, "acc_norm_stderr": 0.0127669237941168 }, "harness|hellaswag|10": { "acc": 0.7226648078072098, "acc_stderr": 0.0044676841327724115, "acc_norm": 0.8939454291973711, "acc_norm_stderr": 0.0030727817579111268 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "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": 0.6578947368421053, "acc_stderr": 0.03860731599316092, "acc_norm": 0.6578947368421053, "acc_norm_stderr": 0.03860731599316092 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.65, "acc_stderr": 0.0479372485441102, "acc_norm": 0.65, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7132075471698113, "acc_stderr": 0.02783491252754407, "acc_norm": 0.7132075471698113, "acc_norm_stderr": 0.02783491252754407 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7638888888888888, "acc_stderr": 0.03551446610810826, "acc_norm": 0.7638888888888888, "acc_norm_stderr": 0.03551446610810826 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.49, "acc_stderr": 0.05024183937956911, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956911 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.54, "acc_stderr": 0.05009082659620333, "acc_norm": 0.54, "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": 0.6647398843930635, "acc_stderr": 0.03599586301247077, "acc_norm": 0.6647398843930635, "acc_norm_stderr": 0.03599586301247077 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.43137254901960786, "acc_stderr": 0.04928099597287534, "acc_norm": 0.43137254901960786, "acc_norm_stderr": 0.04928099597287534 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.74, "acc_stderr": 0.04408440022768078, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768078 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5787234042553191, "acc_stderr": 0.03227834510146268, "acc_norm": 0.5787234042553191, "acc_norm_stderr": 0.03227834510146268 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4824561403508772, "acc_stderr": 0.04700708033551038, "acc_norm": 0.4824561403508772, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5724137931034483, "acc_stderr": 0.04122737111370332, "acc_norm": 0.5724137931034483, "acc_norm_stderr": 0.04122737111370332 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.42063492063492064, "acc_stderr": 0.025424835086924, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.025424835086924 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.32, "acc_stderr": 0.04688261722621505, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7967741935483871, "acc_stderr": 0.022891687984554963, "acc_norm": 0.7967741935483871, "acc_norm_stderr": 0.022891687984554963 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4876847290640394, "acc_stderr": 0.035169204442208966, "acc_norm": 0.4876847290640394, "acc_norm_stderr": 0.035169204442208966 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.74, "acc_stderr": 0.04408440022768079, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768079 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7757575757575758, "acc_stderr": 0.032568666616811015, "acc_norm": 0.7757575757575758, "acc_norm_stderr": 0.032568666616811015 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7727272727272727, "acc_stderr": 0.029857515673386414, "acc_norm": 0.7727272727272727, "acc_norm_stderr": 0.029857515673386414 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8860103626943006, "acc_stderr": 0.022935144053919436, "acc_norm": 0.8860103626943006, "acc_norm_stderr": 0.022935144053919436 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6743589743589744, "acc_stderr": 0.02375966576741229, "acc_norm": 0.6743589743589744, "acc_norm_stderr": 0.02375966576741229 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.34444444444444444, "acc_stderr": 0.028972648884844267, "acc_norm": 0.34444444444444444, "acc_norm_stderr": 0.028972648884844267 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6722689075630253, "acc_stderr": 0.03048991141767323, "acc_norm": 0.6722689075630253, "acc_norm_stderr": 0.03048991141767323 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.33112582781456956, "acc_stderr": 0.038425817186598696, "acc_norm": 0.33112582781456956, "acc_norm_stderr": 0.038425817186598696 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8440366972477065, "acc_stderr": 0.01555580271359017, "acc_norm": 0.8440366972477065, "acc_norm_stderr": 0.01555580271359017 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5092592592592593, "acc_stderr": 0.034093869469927006, "acc_norm": 0.5092592592592593, "acc_norm_stderr": 0.034093869469927006 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8235294117647058, "acc_stderr": 0.026756401538078962, "acc_norm": 0.8235294117647058, "acc_norm_stderr": 0.026756401538078962 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7932489451476793, "acc_stderr": 0.0263616516683891, "acc_norm": 0.7932489451476793, "acc_norm_stderr": 0.0263616516683891 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6860986547085202, "acc_stderr": 0.031146796482972465, "acc_norm": 0.6860986547085202, "acc_norm_stderr": 0.031146796482972465 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7938931297709924, "acc_stderr": 0.03547771004159465, "acc_norm": 0.7938931297709924, "acc_norm_stderr": 0.03547771004159465 }, "harness|hendrycksTest-international_law|5": { "acc": 0.768595041322314, "acc_stderr": 0.03849856098794088, "acc_norm": 0.768595041322314, "acc_norm_stderr": 0.03849856098794088 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7685185185185185, "acc_stderr": 0.04077494709252626, "acc_norm": 0.7685185185185185, "acc_norm_stderr": 0.04077494709252626 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7730061349693251, "acc_stderr": 0.03291099578615769, "acc_norm": 0.7730061349693251, "acc_norm_stderr": 0.03291099578615769 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.42857142857142855, "acc_stderr": 0.04697113923010212, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.04697113923010212 }, "harness|hendrycksTest-management|5": { "acc": 0.7669902912621359, "acc_stderr": 0.04185832598928315, "acc_norm": 0.7669902912621359, "acc_norm_stderr": 0.04185832598928315 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8846153846153846, "acc_stderr": 0.02093019318517933, "acc_norm": 0.8846153846153846, "acc_norm_stderr": 0.02093019318517933 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.74, "acc_stderr": 0.04408440022768079, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768079 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8301404853128991, "acc_stderr": 0.013428186370608304, "acc_norm": 0.8301404853128991, "acc_norm_stderr": 0.013428186370608304 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7167630057803468, "acc_stderr": 0.02425790170532338, "acc_norm": 0.7167630057803468, "acc_norm_stderr": 0.02425790170532338 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.44581005586592176, "acc_stderr": 0.016623998513333106, "acc_norm": 0.44581005586592176, "acc_norm_stderr": 0.016623998513333106 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7287581699346405, "acc_stderr": 0.025457756696667874, "acc_norm": 0.7287581699346405, "acc_norm_stderr": 0.025457756696667874 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7009646302250804, "acc_stderr": 0.026003301117885135, "acc_norm": 0.7009646302250804, "acc_norm_stderr": 0.026003301117885135 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7438271604938271, "acc_stderr": 0.0242885336377261, "acc_norm": 0.7438271604938271, "acc_norm_stderr": 0.0242885336377261 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4929078014184397, "acc_stderr": 0.02982449855912901, "acc_norm": 0.4929078014184397, "acc_norm_stderr": 0.02982449855912901 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.46479791395045633, "acc_stderr": 0.012738547371303957, "acc_norm": 0.46479791395045633, "acc_norm_stderr": 0.012738547371303957 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6617647058823529, "acc_stderr": 0.028739328513983572, "acc_norm": 0.6617647058823529, "acc_norm_stderr": 0.028739328513983572 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.673202614379085, "acc_stderr": 0.0189754279205072, "acc_norm": 0.673202614379085, "acc_norm_stderr": 0.0189754279205072 }, "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": 0.7306122448979592, "acc_stderr": 0.02840125202902294, "acc_norm": 0.7306122448979592, "acc_norm_stderr": 0.02840125202902294 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8308457711442786, "acc_stderr": 0.02650859065623327, "acc_norm": 0.8308457711442786, "acc_norm_stderr": 0.02650859065623327 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.84, "acc_stderr": 0.03684529491774709, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774709 }, "harness|hendrycksTest-virology|5": { "acc": 0.5421686746987951, "acc_stderr": 0.0387862677100236, "acc_norm": 0.5421686746987951, "acc_norm_stderr": 0.0387862677100236 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8421052631578947, "acc_stderr": 0.027966785859160893, "acc_norm": 0.8421052631578947, "acc_norm_stderr": 0.027966785859160893 }, "harness|truthfulqa:mc|0": { "mc1": 0.6364749082007344, "mc1_stderr": 0.016838862883965834, "mc2": 0.7846972943990677, "mc2_stderr": 0.013799810152287217 }, "harness|winogrande|5": { "acc": 0.8800315706393055, "acc_stderr": 0.009131996995678647 }, "harness|gsm8k|5": { "acc": 0.6762699014404853, "acc_stderr": 0.012888247397371141 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
ChoiDongHo/HuggingfaceTest
--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 5826 num_examples: 39 download_size: 2572 dataset_size: 5826 configs: - config_name: default data_files: - split: train path: data/train-* ---
nthngdy/babylm_10M
--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 55441912.303940535 num_examples: 1015494 download_size: 36288832 dataset_size: 55441912.303940535 --- # Dataset Card for "babylm_10M" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
graphs-datasets/IMDB-BINARY
--- license: unknown task_categories: - graph-ml --- # Dataset Card for IMDB-BINARY (IMDb-B) ## 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) - [External Use](#external-use) - [PyGeometric](#pygeometric) - [Dataset Structure](#dataset-structure) - [Data Properties](#data-properties) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Additional Information](#additional-information) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **[Homepage](https://dl.acm.org/doi/10.1145/2783258.2783417)** - **[Repository](https://www.chrsmrrs.com/graphkerneldatasets/IMDB-BINARY.zip):**: - **Paper:**: Deep Graph Kernels (see citation) - **Leaderboard:**: [Papers with code leaderboard](https://paperswithcode.com/sota/graph-classification-on-imdb-b) ### Dataset Summary The `IMDb-B` dataset is "a movie collaboration dataset that consists of the ego-networks of 1,000 actors/actresses who played roles in movies in IMDB. In each graph, nodes represent actors/actress, and there is an edge between them if they appear in the same movie. These graphs are derived from the Action and Romance genres". ### Supported Tasks and Leaderboards `IMDb-B` should be used for graph classification (aiming to predict whether a movie graph is an action or romance movie), a binary classification task. The score used is accuracy, using a 10-fold cross-validation. ## External Use ### PyGeometric To load in PyGeometric, do the following: ```python from datasets import load_dataset from torch_geometric.data import Data from torch_geometric.loader import DataLoader dataset_hf = load_dataset("graphs-datasets/<mydataset>") # For the train set (replace by valid or test as needed) dataset_pg_list = [Data(graph) for graph in dataset_hf["train"]] dataset_pg = DataLoader(dataset_pg_list) ``` ## Dataset Structure ### Data Properties | property | value | |---|---| | scale | medium | | #graphs | 1000 | | average #nodes | 19.79 | | average #edges | 193.25 | ### Data Fields Each row of a given file is a graph, with: - `edge_index` (list: 2 x #edges): pairs of nodes constituting edges - `y` (list: 1 x #labels): contains the number of labels available to predict (here 1, equal to zero or one) - `num_nodes` (int): number of nodes of the graph ### Data Splits This data comes from the PyGeometric version of the dataset. This information can be found back using ```python from torch_geometric.datasets import TUDataset cur_dataset = TUDataset(root="../dataset/loaded/", name="IMDB-BINARY") ``` ## Additional Information ### Licensing Information The dataset has been released under unknown license, please open an issue if you have this information. ### Citation Information ``` @inproceedings{10.1145/2783258.2783417, author = {Yanardag, Pinar and Vishwanathan, S.V.N.}, title = {Deep Graph Kernels}, year = {2015}, isbn = {9781450336642}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/2783258.2783417}, doi = {10.1145/2783258.2783417}, abstract = {In this paper, we present Deep Graph Kernels, a unified framework to learn latent representations of sub-structures for graphs, inspired by latest advancements in language modeling and deep learning. Our framework leverages the dependency information between sub-structures by learning their latent representations. We demonstrate instances of our framework on three popular graph kernels, namely Graphlet kernels, Weisfeiler-Lehman subtree kernels, and Shortest-Path graph kernels. Our experiments on several benchmark datasets show that Deep Graph Kernels achieve significant improvements in classification accuracy over state-of-the-art graph kernels.}, booktitle = {Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining}, pages = {1365–1374}, numpages = {10}, keywords = {collaboration networks, bioinformatics, r-convolution kernels, graph kernels, structured data, deep learning, social networks, string kernels}, location = {Sydney, NSW, Australia}, series = {KDD '15} } ``` ### Contributions Thanks to [@clefourrier](https://github.com/clefourrier) for adding this dataset.
TrainingDataPro/plantations_segmentation
--- license: cc-by-nd-4.0 task_categories: - image-segmentation language: - en tags: - biology - code dataset_info: features: - name: image_id dtype: int32 - name: image dtype: image - name: class_segmentation dtype: image - name: object_segmentation dtype: image - name: shapes dtype: string splits: - name: train num_bytes: 48297698 num_examples: 13 download_size: 48362120 dataset_size: 48297698 --- # Plantations Segmentation The images consist of aerial photography of agricultural plantations with crops such as cabbage and zucchini. The dataset addresses agricultural tasks such as plant detection and counting, health assessment, and irrigation planning. The dataset consists of plantations' photographs with object and class segmentation of cabbage. # Get the dataset ### This is just an example of the data Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market/agriculture-data-labeling?utm_source=huggingface&utm_medium=cpc&utm_campaign=plantations_segmentation) to discuss your requirements, learn about the price and buy the dataset. ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F5fa7e8e62e793dac70dc9e1db6f60a18%2F66666.png?generation=1685972525147537&alt=media) # Dataset structure - **Plantations_Segmentation** - contains of original plantation images (folder **img**) and file with annotations (.xml) - **Object_Segmentation** - includes object segmentation masks for the original images - **Class_Segmentation** - includes class segmentation masks for the original images # Types of segmentation The dataset includes two types of segmentation: - **Class Segmentation** - objects corresponding to one class are identified - **Object Segmentation** - all objects are identified separately # Data Format Each image from `img` folder is accompanied by an XML-annotation in the `annotations.xml` file indicating the coordinates of the polygons. For each point, the x and y coordinates are provided. # Example of XML file structure ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F0c5baa0d81e6c2fb17885456f1bd3cfd%2Fcarbon%20(1).png?generation=1685973058340642&alt=media) # Plantation segmentation might be made in accordance with your requirements. ## [**TrainingData**](https://trainingdata.pro/data-market/agriculture-data-labeling?utm_source=huggingface&utm_medium=cpc&utm_campaign=plantations_segmentation) provides high-quality data annotation tailored to your needs More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets** TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**
dim/competition_math_selected
--- license: mit dataset_info: features: - name: problem dtype: string - name: level dtype: string - name: type dtype: string - name: solution dtype: string splits: - name: train num_bytes: 2332225.2 num_examples: 3000 download_size: 1217035 dataset_size: 2332225.2 ---
bigscience-data/roots_indic-hi_wikiversity
--- language: hi license: cc-by-sa-3.0 extra_gated_prompt: 'By accessing this dataset, you agree to abide by the BigScience Ethical Charter. The charter can be found at: https://hf.co/spaces/bigscience/ethical-charter' extra_gated_fields: I have read and agree to abide by the BigScience Ethical Charter: checkbox --- ROOTS Subset: roots_indic-hi_wikiversity # wikiversity_filtered - Dataset uid: `wikiversity_filtered` ### Description ### Homepage ### Licensing ### Speaker Locations ### Sizes - 0.0367 % of total - 0.1050 % of en - 0.1178 % of fr - 0.1231 % of pt - 0.0072 % of zh - 0.0393 % of es - 0.0076 % of ar - 0.0069 % of indic-hi ### BigScience processing steps #### Filters applied to: en - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_en - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: fr - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_fr - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: pt - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_pt - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: zh - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_zhs - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: es - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_es - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_1024 #### Filters applied to: ar - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_ar - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300 #### Filters applied to: indic-hi - filter_wiki_user_titles - filter_wiki_non_text_type - dedup_document - filter_remove_empty_docs - split_sentences_indic-hi - dedup_template_soft - replace_newline_with_space - filter_small_docs_bytes_300
CyberHarem/de_lisle_girlsfrontline
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of de_lisle/デ・リーズル/德利尔 (Girls' Frontline) This is the dataset of de_lisle/デ・リーズル/德利尔 (Girls' Frontline), containing 17 images and their tags. The core tags of this character are `green_eyes, long_hair, brown_hair, heterochromia, blue_eyes, mole, mole_under_eye, bangs, multicolored_hair, twintails, hair_ornament, earrings, horns`, 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 | 17 | 30.35 MiB | [Download](https://huggingface.co/datasets/CyberHarem/de_lisle_girlsfrontline/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 17 | 14.36 MiB | [Download](https://huggingface.co/datasets/CyberHarem/de_lisle_girlsfrontline/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 44 | 32.03 MiB | [Download](https://huggingface.co/datasets/CyberHarem/de_lisle_girlsfrontline/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 17 | 25.73 MiB | [Download](https://huggingface.co/datasets/CyberHarem/de_lisle_girlsfrontline/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 44 | 51.13 MiB | [Download](https://huggingface.co/datasets/CyberHarem/de_lisle_girlsfrontline/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/de_lisle_girlsfrontline', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | 0 | 17 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | 1girl, looking_at_viewer, solo, open_mouth, black_gloves, piercing, collarbone, earbuds, simple_background, black_choker, blush, fingerless_gloves, holding, white_background | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | looking_at_viewer | solo | open_mouth | black_gloves | piercing | collarbone | earbuds | simple_background | black_choker | blush | fingerless_gloves | holding | white_background | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------------|:-------|:-------------|:---------------|:-----------|:-------------|:----------|:--------------------|:---------------|:--------|:--------------------|:----------|:-------------------| | 0 | 17 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
somewheresystems/dataclysm-wikipedia
--- license: cc-by-sa-3.0 language: - en pretty_name: dataclysm-wikipedia-titles size_categories: - 1M<n<10M --- # somewheresystems/dataclysm-wikipedia ## USE THE NOTEBOOK TO GET STARTED! https://github.com/somewheresystems/dataclysm This dataset comprises of 6,458,670 English language Wikipedia articles, with an additional column added for title-embeddings using the bge-small-en-v1.5 embeddings model. The dataset was sourced here: https://huggingface.co/datasets/wikipedia/viewer/20220301.en This dataset contains the full text of each Wikipedia article as of the date March 01, 2022. In comparison to somewheresystems/dataclysm-wikipedia-titles (68.93 GB), and the wikipedia-titles-lite dataset (49.72 GB), this entire dataset is only 16.32 GB uncompressed, which is 86.25% smaller and 63.18% smaller respectively. # Embeddings Model We used https://huggingface.co/BAAI/bge-small-en-v1.5 to embed the artcle `title` field. The purpose of using this model in particular was to leverage the ability to embed each title quickly while allowing for slightly more performant retrieval than `instruct-xl`. # Why? You can either load this entire dataset into a database and retrieve article text by similarity searches between queries and titles, link them to URLs and pull up-to-date articles, or pull the article text from March 01, 2022 from the dataset directly (included). For efficiency, we recommend dropping everything except the title, title embeddings, and URL to be able to quickly load and index information which can be used to efficiently pull the remaining information asynchronously via web. # Citation Information ``` @ONLINE{wikidump, author = "Wikimedia Foundation", title = "Wikimedia Downloads", url = "https://dumps.wikimedia.org" } ``` # Contributions Thanks to @lewtun, @mariamabarham, @thomwolf, @lhoestq, @patrickvonplaten for adding the Wikipedia dataset in the first place. ## Contact Please contact hi@dataclysm.xyz for inquiries.
joey234/mmlu-college_biology-neg-prepend-fix
--- configs: - config_name: default data_files: - split: dev path: data/dev-* - split: test path: data/test-* dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: negate_openai_prompt struct: - name: content dtype: string - name: role dtype: string - name: neg_question dtype: string - name: fewshot_context dtype: string - name: ori_prompt dtype: string splits: - name: dev num_bytes: 6719 num_examples: 5 - name: test num_bytes: 417471 num_examples: 144 download_size: 14610 dataset_size: 424190 --- # Dataset Card for "mmlu-college_biology-neg-prepend-fix" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
sheik21/rose
--- license: openrail ---
dinaaaaaa/LIMA_instructions_generate
--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 158731.98003327788 num_examples: 80 download_size: 141043 dataset_size: 158731.98003327788 configs: - config_name: default data_files: - split: train path: data/train-* ---
autoevaluate/autoeval-staging-eval-project-e4791b21-302d-4702-9dba-a4a3a73498cd-118114
--- type: predictions tags: - autotrain - evaluation datasets: - emotion eval_info: task: multi_class_classification model: autoevaluate/multi-class-classification-not-evaluated metrics: ['matthews_correlation'] dataset_name: emotion dataset_config: default dataset_split: test col_mapping: text: text 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: Multi-class Text Classification * Model: autoevaluate/multi-class-classification-not-evaluated * Dataset: emotion * Config: default * Split: test 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.
smallfish166/github-issues
--- dataset_info: features: - name: url dtype: string - name: repository_url dtype: string - name: labels_url dtype: string - name: comments_url dtype: string - name: events_url dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: number dtype: int64 - name: title dtype: string - name: user struct: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: labels list: - name: color dtype: string - name: default dtype: bool - name: description dtype: string - name: id dtype: int64 - name: name dtype: string - name: node_id dtype: string - name: url dtype: string - name: state dtype: string - name: locked dtype: bool - name: assignee struct: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: assignees list: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: milestone struct: - name: closed_at dtype: string - name: closed_issues dtype: int64 - name: created_at dtype: string - name: creator struct: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: description dtype: string - name: due_on dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: labels_url dtype: string - name: node_id dtype: string - name: number dtype: int64 - name: open_issues dtype: int64 - name: state dtype: string - name: title dtype: string - name: updated_at dtype: string - name: url dtype: string - name: comments sequence: string - name: created_at dtype: timestamp[ns, tz=UTC] - name: updated_at dtype: timestamp[ns, tz=UTC] - name: closed_at dtype: timestamp[ns, tz=UTC] - name: author_association dtype: string - name: active_lock_reason dtype: float64 - name: draft dtype: float64 - name: pull_request struct: - name: diff_url dtype: string - name: html_url dtype: string - name: merged_at dtype: string - name: patch_url dtype: string - name: url dtype: string - name: body dtype: string - name: reactions struct: - name: '+1' 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: float64 - name: state_reason dtype: string - name: is_pull_request dtype: bool splits: - name: train num_bytes: 36256485 num_examples: 6502 download_size: 10383287 dataset_size: 36256485 configs: - config_name: default data_files: - split: train path: data/train-* ---
yuan-sf63/chenyu_label_0.5_96
--- dataset_info: features: - name: text dtype: string - name: '0' dtype: int64 - name: '1' dtype: int64 - name: '2' dtype: int64 - name: '3' dtype: int64 - name: '4' dtype: int64 - name: '5' dtype: int64 - name: '6' dtype: int64 - name: '7' dtype: int64 - name: '8' dtype: int64 - name: '9' dtype: int64 - name: '10' dtype: int64 - name: '11' dtype: int64 - name: '12' dtype: int64 - name: '13' dtype: int64 - name: '14' dtype: int64 - name: '15' dtype: int64 - name: '16' dtype: int64 - name: '17' dtype: int64 - name: '18' dtype: int64 - name: '19' dtype: int64 - name: '20' dtype: int64 - name: '21' dtype: int64 - name: '22' dtype: int64 - name: '23' dtype: int64 - name: '24' dtype: int64 - name: '25' dtype: int64 - name: '26' dtype: int64 - name: '27' dtype: int64 - name: '28' dtype: int64 - name: '29' dtype: int64 - name: '30' dtype: int64 - name: '31' dtype: int64 - name: '32' dtype: int64 - name: '33' dtype: int64 - name: '34' dtype: int64 - name: '35' dtype: int64 - name: '36' dtype: int64 - name: '37' dtype: int64 - name: '38' dtype: int64 - name: '39' dtype: int64 - name: '40' dtype: int64 - name: '41' dtype: int64 - name: '42' dtype: int64 - name: '43' dtype: int64 - name: '44' dtype: int64 - name: '45' dtype: int64 - name: '46' dtype: int64 - name: '47' dtype: int64 - name: '48' dtype: int64 - name: '49' dtype: int64 - name: '50' dtype: int64 - name: '51' dtype: int64 - name: '52' dtype: int64 - name: '53' dtype: int64 - name: '54' dtype: int64 - name: '55' dtype: int64 - name: '56' dtype: int64 - name: '57' dtype: int64 - name: '58' dtype: int64 - name: '59' dtype: int64 - name: '60' dtype: int64 - name: '61' dtype: int64 - name: '62' dtype: int64 - name: '63' dtype: int64 - name: '64' dtype: int64 - name: '65' dtype: int64 - name: '66' dtype: int64 - name: '67' dtype: int64 - name: '68' dtype: int64 - name: '69' dtype: int64 - name: '70' dtype: int64 - name: '71' dtype: int64 - name: '72' dtype: int64 - name: '73' dtype: int64 - name: '74' dtype: int64 - name: '75' dtype: int64 - name: '76' dtype: int64 - name: '77' dtype: int64 - name: '78' dtype: int64 - name: '79' dtype: int64 - name: '80' dtype: int64 - name: '81' dtype: int64 - name: '82' dtype: int64 - name: '83' dtype: int64 - name: '84' dtype: int64 - name: '85' dtype: int64 - name: '86' dtype: int64 - name: '87' dtype: int64 - name: '88' dtype: int64 - name: '89' dtype: int64 - name: '90' dtype: int64 - name: '91' dtype: int64 - name: '92' dtype: int64 - name: '93' dtype: int64 - name: '94' dtype: int64 - name: '95' dtype: int64 splits: - name: train num_bytes: 33328102.677381746 num_examples: 37825 - name: validation num_bytes: 3703318.3226182545 num_examples: 4203 download_size: 0 dataset_size: 37031421.0 --- # Dataset Card for "chenyu_label_0.5_96" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
vidannn/az-text2
--- license: apache-2.0 ---
CodecSR/librispeech_asr_test_synth
--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 - name: text dtype: string - name: id dtype: string splits: - name: original num_bytes: 1238771045.0 num_examples: 5559 - name: academicodec_hifi_16k_320d_large_uni num_bytes: 1237485326.125 num_examples: 5559 - name: academicodec_hifi_24k_320d num_bytes: 1237485326.125 num_examples: 5559 - name: audiodec_24k_300d num_bytes: 1240338486.125 num_examples: 5559 - name: audiodec_48k_300d_uni num_bytes: 1240338486.125 num_examples: 5559 - name: dac_16k num_bytes: 1238775910.125 num_examples: 5559 - name: dac_24k num_bytes: 1238775910.125 num_examples: 5559 - name: dac_44k num_bytes: 1238775910.125 num_examples: 5559 - name: encodec_24k_12bps num_bytes: 1238775910.125 num_examples: 5559 - name: encodec_24k_1_5bps num_bytes: 1238775910.125 num_examples: 5559 - name: encodec_24k_24bps num_bytes: 1238775910.125 num_examples: 5559 - name: encodec_24k_3bps num_bytes: 1238775910.125 num_examples: 5559 - name: encodec_24k_6bps num_bytes: 1238775910.125 num_examples: 5559 - name: facodec_16k num_bytes: 1238339086.125 num_examples: 5559 - name: funcodec_en_libritts_16k_nq32ds320 num_bytes: 1238775910.125 num_examples: 5559 - name: funcodec_en_libritts_16k_nq32ds640 num_bytes: 1238775910.125 num_examples: 5559 - name: funcodec_zh_en_16k_nq32ds320 num_bytes: 1238775910.125 num_examples: 5559 - name: funcodec_zh_en_16k_nq32ds640 num_bytes: 1238775910.125 num_examples: 5559 - name: language_codec_chinese_24k_nq8_12kbps num_bytes: 1240065806.125 num_examples: 5559 - name: language_codec_paper_24k_nq8_12kbps num_bytes: 1240065806.125 num_examples: 5559 - name: speech_tokenizer_16k num_bytes: 1240065806.125 num_examples: 5559 download_size: 25399705699 dataset_size: 26018266095.5 configs: - config_name: default data_files: - split: original path: data/original-* - split: academicodec_hifi_16k_320d_large_uni path: data/academicodec_hifi_16k_320d_large_uni-* - split: academicodec_hifi_24k_320d path: data/academicodec_hifi_24k_320d-* - split: audiodec_24k_300d path: data/audiodec_24k_300d-* - split: audiodec_48k_300d_uni path: data/audiodec_48k_300d_uni-* - split: dac_16k path: data/dac_16k-* - split: dac_24k path: data/dac_24k-* - split: dac_44k path: data/dac_44k-* - split: encodec_24k_12bps path: data/encodec_24k_12bps-* - split: encodec_24k_1_5bps path: data/encodec_24k_1_5bps-* - split: encodec_24k_24bps path: data/encodec_24k_24bps-* - split: encodec_24k_3bps path: data/encodec_24k_3bps-* - split: encodec_24k_6bps path: data/encodec_24k_6bps-* - split: facodec_16k path: data/facodec_16k-* - split: funcodec_en_libritts_16k_nq32ds320 path: data/funcodec_en_libritts_16k_nq32ds320-* - split: funcodec_en_libritts_16k_nq32ds640 path: data/funcodec_en_libritts_16k_nq32ds640-* - split: funcodec_zh_en_16k_nq32ds320 path: data/funcodec_zh_en_16k_nq32ds320-* - split: funcodec_zh_en_16k_nq32ds640 path: data/funcodec_zh_en_16k_nq32ds640-* - split: language_codec_chinese_24k_nq8_12kbps path: data/language_codec_chinese_24k_nq8_12kbps-* - split: language_codec_paper_24k_nq8_12kbps path: data/language_codec_paper_24k_nq8_12kbps-* - split: speech_tokenizer_16k path: data/speech_tokenizer_16k-* ---
kpriyanshu256/MultiTabQA-multitable_pretraining-Salesforce-codet5-base_train-latex-63000
--- dataset_info: features: - name: input_ids sequence: sequence: int32 - name: attention_mask sequence: sequence: int8 - name: labels sequence: sequence: int64 splits: - name: train num_bytes: 13336000 num_examples: 1000 download_size: 1002435 dataset_size: 13336000 configs: - config_name: default data_files: - split: train path: data/train-* ---
edbeeching/prj_gia_dataset_atari_2B_atari_videopinball_1111
--- library_name: gia tags: - deep-reinforcement-learning - reinforcement-learning - gia - multi-task - multi-modal - imitation-learning - offline-reinforcement-learning --- An imitation learning environment for the atari_videopinball environment, sample for the policy atari_2B_atari_videopinball_1111 This environment was created as part of the Generally Intelligent Agents project gia: https://github.com/huggingface/gia
atmallen/quirky_bookrating_bob_easy
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* dataset_info: features: - name: alice_label dtype: bool - name: bob_label dtype: bool - name: difficulty dtype: float64 - name: statement dtype: string - name: choices sequence: string - name: character dtype: string - name: label dtype: bool splits: - name: train num_bytes: 96081.48302415121 num_examples: 714 - name: validation num_bytes: 65429.5725 num_examples: 486 - name: test num_bytes: 68424.7355 num_examples: 506 download_size: 78400 dataset_size: 229935.7910241512 --- # Dataset Card for "quirky_bookrating_bob_easy" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Cartinoe5930/few-shot-qwen-7b
--- dataset_info: features: - name: response dtype: string - name: predictied_answer dtype: int64 - name: actual_answer dtype: int64 splits: - name: train num_bytes: 439227 num_examples: 1319 download_size: 202218 dataset_size: 439227 configs: - config_name: default data_files: - split: train path: data/train-* ---
Chr0my/freesound.org
--- language: - en tags: - music size_categories: - 100K<n<1M --- This dataset has been scraped from https://freesound.org Containing 554849 audio clips. License: cc-by-sa-3.0, https://creativecommons.org/licenses/by-sa/3.0/
dinesht/sample_dataset
--- license: unknown ---
SuperSecureHuman/vendata-code
--- dataset_info: features: - name: repo_id dtype: string - name: file_path dtype: string - name: content dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 41265263 num_examples: 9129 download_size: 15639176 dataset_size: 41265263 configs: - config_name: default data_files: - split: train path: data/train-* ---
Brendan/nlp244_french_snli
--- dataset_info: features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: '0': entailment '1': neutral '2': contradiction - name: fr_premise dtype: string - name: fr_hypothesis dtype: string splits: - name: test num_bytes: 2298242 num_examples: 10000 - name: train num_bytes: 122710788 num_examples: 550152 - name: validation num_bytes: 2305275 num_examples: 10000 download_size: 40406975 dataset_size: 127314305 --- # Dataset Card for "nlp244_french_snli" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
BEE-spoke-data/survivorslib-law-books
--- dataset_info: features: - name: section dtype: string - name: filename dtype: string - name: text dtype: string splits: - name: train num_bytes: 73734751.97826087 num_examples: 43 - name: validation num_bytes: 1714761.6739130435 num_examples: 1 - name: test num_bytes: 3429523.347826087 num_examples: 2 download_size: 42120770 dataset_size: 78879037.00000001 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* license: odc-by task_categories: - text-generation - fill-mask language: - en size_categories: - n<1K --- # law books (nougat-small) A decent chunk of: https://www.survivorlibrary.com/index.php/8-category/173-library-law <pre>(ki) <font color="#859900"><b>➜ </b></font><font color="#2AA198"><b>primerdata-for-LLMs</b></font> python push_dataset_from_text.py /home/pszemraj/Dropbox/programming-projects/primerdata-for-LLMs/utils/output-hf-nougat-space/law -e .md -r BEE-spoke-data/survivorslib-law-books INFO:__main__:Looking for files with extensions: [&apos;md&apos;] Processing md files: 100%|███████████████████████████████| 46/46 [00:00&lt;00:00, 778.32it/s] INFO:__main__:Found 46 text files. INFO:__main__:Performing train-test split... INFO:__main__:Performing validation-test split... INFO:__main__:Train size: 43 INFO:__main__:Validation size: 1 INFO:__main__:Test size: 2 INFO:__main__:Pushing dataset</pre>
open-llm-leaderboard/details_lamhieu__ghost-7b-v0.9.1
--- pretty_name: Evaluation run of lamhieu/ghost-7b-v0.9.1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [lamhieu/ghost-7b-v0.9.1](https://huggingface.co/lamhieu/ghost-7b-v0.9.1) 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_lamhieu__ghost-7b-v0.9.1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-22T12:21:15.645809](https://huggingface.co/datasets/open-llm-leaderboard/details_lamhieu__ghost-7b-v0.9.1/blob/main/results_2024-02-22T12-21-15.645809.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\": 0.5461963762782457,\n\ \ \"acc_stderr\": 0.0341839674901544,\n \"acc_norm\": 0.5516542798358821,\n\ \ \"acc_norm_stderr\": 0.034909524738250194,\n \"mc1\": 0.29865361077111385,\n\ \ \"mc1_stderr\": 0.016021570613768542,\n \"mc2\": 0.43956086098918057,\n\ \ \"mc2_stderr\": 0.015308355019122989\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5170648464163823,\n \"acc_stderr\": 0.014602878388536595,\n\ \ \"acc_norm\": 0.5537542662116041,\n \"acc_norm_stderr\": 0.01452670554853998\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5828520215096594,\n\ \ \"acc_stderr\": 0.004920800313232742,\n \"acc_norm\": 0.770264887472615,\n\ \ \"acc_norm_stderr\": 0.004198027272982672\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.4444444444444444,\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\": 0.5,\n\ \ \"acc_stderr\": 0.050251890762960605,\n \"acc_norm\": 0.5,\n \ \ \"acc_norm_stderr\": 0.050251890762960605\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6037735849056604,\n \"acc_stderr\": 0.030102793781791197,\n\ \ \"acc_norm\": 0.6037735849056604,\n \"acc_norm_stderr\": 0.030102793781791197\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5694444444444444,\n\ \ \"acc_stderr\": 0.04140685639111502,\n \"acc_norm\": 0.5694444444444444,\n\ \ \"acc_norm_stderr\": 0.04140685639111502\n },\n \"harness|hendrycksTest-college_chemistry|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_computer_science|5\": {\n \"\ acc\": 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\"\ : 0.44,\n \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001975,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001975\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.5317919075144508,\n\ \ \"acc_stderr\": 0.03804749744364764,\n \"acc_norm\": 0.5317919075144508,\n\ \ \"acc_norm_stderr\": 0.03804749744364764\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.45098039215686275,\n \"acc_stderr\": 0.04951218252396264,\n\ \ \"acc_norm\": 0.45098039215686275,\n \"acc_norm_stderr\": 0.04951218252396264\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.72,\n \"acc_stderr\": 0.045126085985421276,\n \"acc_norm\": 0.72,\n\ \ \"acc_norm_stderr\": 0.045126085985421276\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.4723404255319149,\n \"acc_stderr\": 0.03263597118409769,\n\ \ \"acc_norm\": 0.4723404255319149,\n \"acc_norm_stderr\": 0.03263597118409769\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.37719298245614036,\n\ \ \"acc_stderr\": 0.04559522141958216,\n \"acc_norm\": 0.37719298245614036,\n\ \ \"acc_norm_stderr\": 0.04559522141958216\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\"\ : 0.3201058201058201,\n \"acc_stderr\": 0.024026846392873502,\n \"\ acc_norm\": 0.3201058201058201,\n \"acc_norm_stderr\": 0.024026846392873502\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\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.6612903225806451,\n\ \ \"acc_stderr\": 0.02692344605930284,\n \"acc_norm\": 0.6612903225806451,\n\ \ \"acc_norm_stderr\": 0.02692344605930284\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.39901477832512317,\n \"acc_stderr\": 0.034454876862647144,\n\ \ \"acc_norm\": 0.39901477832512317,\n \"acc_norm_stderr\": 0.034454876862647144\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.54,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\"\ : 0.54,\n \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.6727272727272727,\n \"acc_stderr\": 0.036639749943912434,\n\ \ \"acc_norm\": 0.6727272727272727,\n \"acc_norm_stderr\": 0.036639749943912434\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.6767676767676768,\n \"acc_stderr\": 0.033322999210706444,\n \"\ acc_norm\": 0.6767676767676768,\n \"acc_norm_stderr\": 0.033322999210706444\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.7357512953367875,\n \"acc_stderr\": 0.03182155050916647,\n\ \ \"acc_norm\": 0.7357512953367875,\n \"acc_norm_stderr\": 0.03182155050916647\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.517948717948718,\n \"acc_stderr\": 0.025334667080954904,\n \ \ \"acc_norm\": 0.517948717948718,\n \"acc_norm_stderr\": 0.025334667080954904\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\": 0.5378151260504201,\n \"acc_stderr\": 0.0323854694875898,\n \ \ \"acc_norm\": 0.5378151260504201,\n \"acc_norm_stderr\": 0.0323854694875898\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\"\ : 0.726605504587156,\n \"acc_stderr\": 0.019109299846098292,\n \"\ acc_norm\": 0.726605504587156,\n \"acc_norm_stderr\": 0.019109299846098292\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5092592592592593,\n \"acc_stderr\": 0.034093869469927006,\n \"\ acc_norm\": 0.5092592592592593,\n \"acc_norm_stderr\": 0.034093869469927006\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.7205882352941176,\n \"acc_stderr\": 0.03149328104507955,\n \"\ acc_norm\": 0.7205882352941176,\n \"acc_norm_stderr\": 0.03149328104507955\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7088607594936709,\n \"acc_stderr\": 0.029571601065753374,\n \ \ \"acc_norm\": 0.7088607594936709,\n \"acc_norm_stderr\": 0.029571601065753374\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6278026905829597,\n\ \ \"acc_stderr\": 0.03244305283008731,\n \"acc_norm\": 0.6278026905829597,\n\ \ \"acc_norm_stderr\": 0.03244305283008731\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.6030534351145038,\n \"acc_stderr\": 0.04291135671009224,\n\ \ \"acc_norm\": 0.6030534351145038,\n \"acc_norm_stderr\": 0.04291135671009224\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.71900826446281,\n \"acc_stderr\": 0.041032038305145124,\n \"acc_norm\"\ : 0.71900826446281,\n \"acc_norm_stderr\": 0.041032038305145124\n },\n\ \ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.6481481481481481,\n\ \ \"acc_stderr\": 0.04616631111801713,\n \"acc_norm\": 0.6481481481481481,\n\ \ \"acc_norm_stderr\": 0.04616631111801713\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.5766871165644172,\n \"acc_stderr\": 0.03881891213334383,\n\ \ \"acc_norm\": 0.5766871165644172,\n \"acc_norm_stderr\": 0.03881891213334383\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.42857142857142855,\n\ \ \"acc_stderr\": 0.04697113923010212,\n \"acc_norm\": 0.42857142857142855,\n\ \ \"acc_norm_stderr\": 0.04697113923010212\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.6990291262135923,\n \"acc_stderr\": 0.04541609446503948,\n\ \ \"acc_norm\": 0.6990291262135923,\n \"acc_norm_stderr\": 0.04541609446503948\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8504273504273504,\n\ \ \"acc_stderr\": 0.02336505149175372,\n \"acc_norm\": 0.8504273504273504,\n\ \ \"acc_norm_stderr\": 0.02336505149175372\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.62,\n \"acc_stderr\": 0.048783173121456316,\n \ \ \"acc_norm\": 0.62,\n \"acc_norm_stderr\": 0.048783173121456316\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7177522349936143,\n\ \ \"acc_stderr\": 0.01609530296987855,\n \"acc_norm\": 0.7177522349936143,\n\ \ \"acc_norm_stderr\": 0.01609530296987855\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.5664739884393064,\n \"acc_stderr\": 0.02668013476167922,\n\ \ \"acc_norm\": 0.5664739884393064,\n \"acc_norm_stderr\": 0.02668013476167922\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2569832402234637,\n\ \ \"acc_stderr\": 0.014614465821966332,\n \"acc_norm\": 0.2569832402234637,\n\ \ \"acc_norm_stderr\": 0.014614465821966332\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.6274509803921569,\n \"acc_stderr\": 0.027684181883302895,\n\ \ \"acc_norm\": 0.6274509803921569,\n \"acc_norm_stderr\": 0.027684181883302895\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.617363344051447,\n\ \ \"acc_stderr\": 0.027604689028581986,\n \"acc_norm\": 0.617363344051447,\n\ \ \"acc_norm_stderr\": 0.027604689028581986\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.5555555555555556,\n \"acc_stderr\": 0.027648477877413324,\n\ \ \"acc_norm\": 0.5555555555555556,\n \"acc_norm_stderr\": 0.027648477877413324\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.41843971631205673,\n \"acc_stderr\": 0.02942799403941999,\n \ \ \"acc_norm\": 0.41843971631205673,\n \"acc_norm_stderr\": 0.02942799403941999\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3859191655801825,\n\ \ \"acc_stderr\": 0.012433398911476148,\n \"acc_norm\": 0.3859191655801825,\n\ \ \"acc_norm_stderr\": 0.012433398911476148\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.5183823529411765,\n \"acc_stderr\": 0.030352303395351964,\n\ \ \"acc_norm\": 0.5183823529411765,\n \"acc_norm_stderr\": 0.030352303395351964\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.5408496732026143,\n \"acc_stderr\": 0.020160213617222516,\n \ \ \"acc_norm\": 0.5408496732026143,\n \"acc_norm_stderr\": 0.020160213617222516\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.5818181818181818,\n\ \ \"acc_stderr\": 0.04724577405731572,\n \"acc_norm\": 0.5818181818181818,\n\ \ \"acc_norm_stderr\": 0.04724577405731572\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.6204081632653061,\n \"acc_stderr\": 0.031067211262872478,\n\ \ \"acc_norm\": 0.6204081632653061,\n \"acc_norm_stderr\": 0.031067211262872478\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7761194029850746,\n\ \ \"acc_stderr\": 0.029475250236017193,\n \"acc_norm\": 0.7761194029850746,\n\ \ \"acc_norm_stderr\": 0.029475250236017193\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.73,\n \"acc_stderr\": 0.0446196043338474,\n \ \ \"acc_norm\": 0.73,\n \"acc_norm_stderr\": 0.0446196043338474\n },\n\ \ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.45180722891566266,\n\ \ \"acc_stderr\": 0.03874371556587953,\n \"acc_norm\": 0.45180722891566266,\n\ \ \"acc_norm_stderr\": 0.03874371556587953\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.7602339181286549,\n \"acc_stderr\": 0.03274485211946956,\n\ \ \"acc_norm\": 0.7602339181286549,\n \"acc_norm_stderr\": 0.03274485211946956\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.29865361077111385,\n\ \ \"mc1_stderr\": 0.016021570613768542,\n \"mc2\": 0.43956086098918057,\n\ \ \"mc2_stderr\": 0.015308355019122989\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7253354380426204,\n \"acc_stderr\": 0.012544516005117192\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.26914329037149354,\n \ \ \"acc_stderr\": 0.012216595457292733\n }\n}\n```" repo_url: https://huggingface.co/lamhieu/ghost-7b-v0.9.1 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_22T12_21_15.645809 path: - '**/details_harness|arc:challenge|25_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-22T12-21-15.645809.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|gsm8k|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hellaswag|10_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-22T12-21-15.645809.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-management|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-22T12-21-15.645809.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|truthfulqa:mc|0_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-22T12-21-15.645809.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_22T12_21_15.645809 path: - '**/details_harness|winogrande|5_2024-02-22T12-21-15.645809.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-22T12-21-15.645809.parquet' - config_name: results data_files: - split: 2024_02_22T12_21_15.645809 path: - results_2024-02-22T12-21-15.645809.parquet - split: latest path: - results_2024-02-22T12-21-15.645809.parquet --- # Dataset Card for Evaluation run of lamhieu/ghost-7b-v0.9.1 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [lamhieu/ghost-7b-v0.9.1](https://huggingface.co/lamhieu/ghost-7b-v0.9.1) 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_lamhieu__ghost-7b-v0.9.1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-22T12:21:15.645809](https://huggingface.co/datasets/open-llm-leaderboard/details_lamhieu__ghost-7b-v0.9.1/blob/main/results_2024-02-22T12-21-15.645809.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": 0.5461963762782457, "acc_stderr": 0.0341839674901544, "acc_norm": 0.5516542798358821, "acc_norm_stderr": 0.034909524738250194, "mc1": 0.29865361077111385, "mc1_stderr": 0.016021570613768542, "mc2": 0.43956086098918057, "mc2_stderr": 0.015308355019122989 }, "harness|arc:challenge|25": { "acc": 0.5170648464163823, "acc_stderr": 0.014602878388536595, "acc_norm": 0.5537542662116041, "acc_norm_stderr": 0.01452670554853998 }, "harness|hellaswag|10": { "acc": 0.5828520215096594, "acc_stderr": 0.004920800313232742, "acc_norm": 0.770264887472615, "acc_norm_stderr": 0.004198027272982672 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "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": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6037735849056604, "acc_stderr": 0.030102793781791197, "acc_norm": 0.6037735849056604, "acc_norm_stderr": 0.030102793781791197 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5694444444444444, "acc_stderr": 0.04140685639111502, "acc_norm": 0.5694444444444444, "acc_norm_stderr": 0.04140685639111502 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5317919075144508, "acc_stderr": 0.03804749744364764, "acc_norm": 0.5317919075144508, "acc_norm_stderr": 0.03804749744364764 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.45098039215686275, "acc_stderr": 0.04951218252396264, "acc_norm": 0.45098039215686275, "acc_norm_stderr": 0.04951218252396264 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.72, "acc_stderr": 0.045126085985421276, "acc_norm": 0.72, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4723404255319149, "acc_stderr": 0.03263597118409769, "acc_norm": 0.4723404255319149, "acc_norm_stderr": 0.03263597118409769 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.37719298245614036, "acc_stderr": 0.04559522141958216, "acc_norm": 0.37719298245614036, "acc_norm_stderr": 0.04559522141958216 }, "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": 0.3201058201058201, "acc_stderr": 0.024026846392873502, "acc_norm": 0.3201058201058201, "acc_norm_stderr": 0.024026846392873502 }, "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": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6612903225806451, "acc_stderr": 0.02692344605930284, "acc_norm": 0.6612903225806451, "acc_norm_stderr": 0.02692344605930284 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.39901477832512317, "acc_stderr": 0.034454876862647144, "acc_norm": 0.39901477832512317, "acc_norm_stderr": 0.034454876862647144 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6727272727272727, "acc_stderr": 0.036639749943912434, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.036639749943912434 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6767676767676768, "acc_stderr": 0.033322999210706444, "acc_norm": 0.6767676767676768, "acc_norm_stderr": 0.033322999210706444 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7357512953367875, "acc_stderr": 0.03182155050916647, "acc_norm": 0.7357512953367875, "acc_norm_stderr": 0.03182155050916647 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.517948717948718, "acc_stderr": 0.025334667080954904, "acc_norm": 0.517948717948718, "acc_norm_stderr": 0.025334667080954904 }, "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": 0.5378151260504201, "acc_stderr": 0.0323854694875898, "acc_norm": 0.5378151260504201, "acc_norm_stderr": 0.0323854694875898 }, "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": 0.726605504587156, "acc_stderr": 0.019109299846098292, "acc_norm": 0.726605504587156, "acc_norm_stderr": 0.019109299846098292 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5092592592592593, "acc_stderr": 0.034093869469927006, "acc_norm": 0.5092592592592593, "acc_norm_stderr": 0.034093869469927006 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.7205882352941176, "acc_stderr": 0.03149328104507955, "acc_norm": 0.7205882352941176, "acc_norm_stderr": 0.03149328104507955 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7088607594936709, "acc_stderr": 0.029571601065753374, "acc_norm": 0.7088607594936709, "acc_norm_stderr": 0.029571601065753374 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6278026905829597, "acc_stderr": 0.03244305283008731, "acc_norm": 0.6278026905829597, "acc_norm_stderr": 0.03244305283008731 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.6030534351145038, "acc_stderr": 0.04291135671009224, "acc_norm": 0.6030534351145038, "acc_norm_stderr": 0.04291135671009224 }, "harness|hendrycksTest-international_law|5": { "acc": 0.71900826446281, "acc_stderr": 0.041032038305145124, "acc_norm": 0.71900826446281, "acc_norm_stderr": 0.041032038305145124 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.6481481481481481, "acc_stderr": 0.04616631111801713, "acc_norm": 0.6481481481481481, "acc_norm_stderr": 0.04616631111801713 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.5766871165644172, "acc_stderr": 0.03881891213334383, "acc_norm": 0.5766871165644172, "acc_norm_stderr": 0.03881891213334383 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.42857142857142855, "acc_stderr": 0.04697113923010212, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.04697113923010212 }, "harness|hendrycksTest-management|5": { "acc": 0.6990291262135923, "acc_stderr": 0.04541609446503948, "acc_norm": 0.6990291262135923, "acc_norm_stderr": 0.04541609446503948 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8504273504273504, "acc_stderr": 0.02336505149175372, "acc_norm": 0.8504273504273504, "acc_norm_stderr": 0.02336505149175372 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.62, "acc_stderr": 0.048783173121456316, "acc_norm": 0.62, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.7177522349936143, "acc_stderr": 0.01609530296987855, "acc_norm": 0.7177522349936143, "acc_norm_stderr": 0.01609530296987855 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.5664739884393064, "acc_stderr": 0.02668013476167922, "acc_norm": 0.5664739884393064, "acc_norm_stderr": 0.02668013476167922 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.2569832402234637, "acc_stderr": 0.014614465821966332, "acc_norm": 0.2569832402234637, "acc_norm_stderr": 0.014614465821966332 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.6274509803921569, "acc_stderr": 0.027684181883302895, "acc_norm": 0.6274509803921569, "acc_norm_stderr": 0.027684181883302895 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.617363344051447, "acc_stderr": 0.027604689028581986, "acc_norm": 0.617363344051447, "acc_norm_stderr": 0.027604689028581986 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.5555555555555556, "acc_stderr": 0.027648477877413324, "acc_norm": 0.5555555555555556, "acc_norm_stderr": 0.027648477877413324 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.41843971631205673, "acc_stderr": 0.02942799403941999, "acc_norm": 0.41843971631205673, "acc_norm_stderr": 0.02942799403941999 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.3859191655801825, "acc_stderr": 0.012433398911476148, "acc_norm": 0.3859191655801825, "acc_norm_stderr": 0.012433398911476148 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.5183823529411765, "acc_stderr": 0.030352303395351964, "acc_norm": 0.5183823529411765, "acc_norm_stderr": 0.030352303395351964 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.5408496732026143, "acc_stderr": 0.020160213617222516, "acc_norm": 0.5408496732026143, "acc_norm_stderr": 0.020160213617222516 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.5818181818181818, "acc_stderr": 0.04724577405731572, "acc_norm": 0.5818181818181818, "acc_norm_stderr": 0.04724577405731572 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6204081632653061, "acc_stderr": 0.031067211262872478, "acc_norm": 0.6204081632653061, "acc_norm_stderr": 0.031067211262872478 }, "harness|hendrycksTest-sociology|5": { "acc": 0.7761194029850746, "acc_stderr": 0.029475250236017193, "acc_norm": 0.7761194029850746, "acc_norm_stderr": 0.029475250236017193 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.73, "acc_stderr": 0.0446196043338474, "acc_norm": 0.73, "acc_norm_stderr": 0.0446196043338474 }, "harness|hendrycksTest-virology|5": { "acc": 0.45180722891566266, "acc_stderr": 0.03874371556587953, "acc_norm": 0.45180722891566266, "acc_norm_stderr": 0.03874371556587953 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.7602339181286549, "acc_stderr": 0.03274485211946956, "acc_norm": 0.7602339181286549, "acc_norm_stderr": 0.03274485211946956 }, "harness|truthfulqa:mc|0": { "mc1": 0.29865361077111385, "mc1_stderr": 0.016021570613768542, "mc2": 0.43956086098918057, "mc2_stderr": 0.015308355019122989 }, "harness|winogrande|5": { "acc": 0.7253354380426204, "acc_stderr": 0.012544516005117192 }, "harness|gsm8k|5": { "acc": 0.26914329037149354, "acc_stderr": 0.012216595457292733 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). 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More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
mHossain/merge_new_para_detection_data_v2.csv
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: input_text dtype: string - name: target_text dtype: int64 - name: prefix dtype: string splits: - name: train num_bytes: 53374443.81070641 num_examples: 250453 - name: test num_bytes: 5930683.189293594 num_examples: 27829 download_size: 24871187 dataset_size: 59305127.0 --- # Dataset Card for "merge_new_para_detection_data_v2.csv" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
babs/nigerian-accented-english
--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 - name: text dtype: string splits: - name: train num_bytes: 3182575083.5629635 num_examples: 3453 - name: test num_bytes: 643515185.1730368 num_examples: 864 download_size: 3313267272 dataset_size: 3826090268.736 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
open-llm-leaderboard/details_mwitiderrick__SwahiliInstruct-v0.2
--- pretty_name: Evaluation run of mwitiderrick/SwahiliInstruct-v0.2 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mwitiderrick/SwahiliInstruct-v0.2](https://huggingface.co/mwitiderrick/SwahiliInstruct-v0.2)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_mwitiderrick__SwahiliInstruct-v0.2\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-10T17:14:24.591374](https://huggingface.co/datasets/open-llm-leaderboard/details_mwitiderrick__SwahiliInstruct-v0.2/blob/main/results_2024-01-10T17-14-24.591374.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\": 0.5020612158374184,\n\ \ \"acc_stderr\": 0.03431570224894014,\n \"acc_norm\": 0.5085604196260874,\n\ \ \"acc_norm_stderr\": 0.03510491450294754,\n \"mc1\": 0.39657282741738065,\n\ \ \"mc1_stderr\": 0.017124930942023518,\n \"mc2\": 0.5708474256962726,\n\ \ \"mc2_stderr\": 0.015744185818785193\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.514505119453925,\n \"acc_stderr\": 0.014605241081370056,\n\ \ \"acc_norm\": 0.5520477815699659,\n \"acc_norm_stderr\": 0.014532011498211678\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5935072694682334,\n\ \ \"acc_stderr\": 0.004901747426331732,\n \"acc_norm\": 0.7822146982672774,\n\ \ \"acc_norm_stderr\": 0.004118971487050471\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.45185185185185184,\n\ \ \"acc_stderr\": 0.04299268905480864,\n \"acc_norm\": 0.45185185185185184,\n\ \ \"acc_norm_stderr\": 0.04299268905480864\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.46710526315789475,\n \"acc_stderr\": 0.040601270352363966,\n\ \ \"acc_norm\": 0.46710526315789475,\n \"acc_norm_stderr\": 0.040601270352363966\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.49,\n\ \ \"acc_stderr\": 0.05024183937956911,\n \"acc_norm\": 0.49,\n \ \ \"acc_norm_stderr\": 0.05024183937956911\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.5132075471698113,\n \"acc_stderr\": 0.030762134874500476,\n\ \ \"acc_norm\": 0.5132075471698113,\n \"acc_norm_stderr\": 0.030762134874500476\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5416666666666666,\n\ \ \"acc_stderr\": 0.04166666666666666,\n \"acc_norm\": 0.5416666666666666,\n\ \ \"acc_norm_stderr\": 0.04166666666666666\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.048783173121456344,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.048783173121456344\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\ acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \"acc_norm\"\ : 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768078,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768078\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.4913294797687861,\n\ \ \"acc_stderr\": 0.038118909889404126,\n \"acc_norm\": 0.4913294797687861,\n\ \ \"acc_norm_stderr\": 0.038118909889404126\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.28431372549019607,\n \"acc_stderr\": 0.04488482852329017,\n\ \ \"acc_norm\": 0.28431372549019607,\n \"acc_norm_stderr\": 0.04488482852329017\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.62,\n \"acc_stderr\": 0.048783173121456316,\n \"acc_norm\": 0.62,\n\ \ \"acc_norm_stderr\": 0.048783173121456316\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.4553191489361702,\n \"acc_stderr\": 0.03255525359340354,\n\ \ \"acc_norm\": 0.4553191489361702,\n \"acc_norm_stderr\": 0.03255525359340354\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.35964912280701755,\n\ \ \"acc_stderr\": 0.045144961328736334,\n \"acc_norm\": 0.35964912280701755,\n\ \ \"acc_norm_stderr\": 0.045144961328736334\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.46206896551724136,\n \"acc_stderr\": 0.04154659671707548,\n\ \ \"acc_norm\": 0.46206896551724136,\n \"acc_norm_stderr\": 0.04154659671707548\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.37037037037037035,\n \"acc_stderr\": 0.0248708152510571,\n \"\ acc_norm\": 0.37037037037037035,\n \"acc_norm_stderr\": 0.0248708152510571\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.30952380952380953,\n\ \ \"acc_stderr\": 0.04134913018303316,\n \"acc_norm\": 0.30952380952380953,\n\ \ \"acc_norm_stderr\": 0.04134913018303316\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.42258064516129035,\n\ \ \"acc_stderr\": 0.02810096472427264,\n \"acc_norm\": 0.42258064516129035,\n\ \ \"acc_norm_stderr\": 0.02810096472427264\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.35960591133004927,\n \"acc_stderr\": 0.033764582465095665,\n\ \ \"acc_norm\": 0.35960591133004927,\n \"acc_norm_stderr\": 0.033764582465095665\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.51,\n \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\"\ : 0.51,\n \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.6424242424242425,\n \"acc_stderr\": 0.03742597043806587,\n\ \ \"acc_norm\": 0.6424242424242425,\n \"acc_norm_stderr\": 0.03742597043806587\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.6616161616161617,\n \"acc_stderr\": 0.03371124142626301,\n \"\ acc_norm\": 0.6616161616161617,\n \"acc_norm_stderr\": 0.03371124142626301\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.6994818652849741,\n \"acc_stderr\": 0.033088185944157494,\n\ \ \"acc_norm\": 0.6994818652849741,\n \"acc_norm_stderr\": 0.033088185944157494\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.41794871794871796,\n \"acc_stderr\": 0.02500732988246122,\n\ \ \"acc_norm\": 0.41794871794871796,\n \"acc_norm_stderr\": 0.02500732988246122\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.32222222222222224,\n \"acc_stderr\": 0.028493465091028597,\n \ \ \"acc_norm\": 0.32222222222222224,\n \"acc_norm_stderr\": 0.028493465091028597\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.453781512605042,\n \"acc_stderr\": 0.03233943468182088,\n \ \ \"acc_norm\": 0.453781512605042,\n \"acc_norm_stderr\": 0.03233943468182088\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.304635761589404,\n \"acc_stderr\": 0.03757949922943343,\n \"acc_norm\"\ : 0.304635761589404,\n \"acc_norm_stderr\": 0.03757949922943343\n },\n\ \ \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.655045871559633,\n\ \ \"acc_stderr\": 0.020380605405066952,\n \"acc_norm\": 0.655045871559633,\n\ \ \"acc_norm_stderr\": 0.020380605405066952\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\ : {\n \"acc\": 0.375,\n \"acc_stderr\": 0.033016908987210894,\n \ \ \"acc_norm\": 0.375,\n \"acc_norm_stderr\": 0.033016908987210894\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.6862745098039216,\n \"acc_stderr\": 0.03256685484460389,\n \"\ acc_norm\": 0.6862745098039216,\n \"acc_norm_stderr\": 0.03256685484460389\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7215189873417721,\n \"acc_stderr\": 0.029178682304842548,\n \ \ \"acc_norm\": 0.7215189873417721,\n \"acc_norm_stderr\": 0.029178682304842548\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6188340807174888,\n\ \ \"acc_stderr\": 0.03259625118416827,\n \"acc_norm\": 0.6188340807174888,\n\ \ \"acc_norm_stderr\": 0.03259625118416827\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.5725190839694656,\n \"acc_stderr\": 0.04338920305792401,\n\ \ \"acc_norm\": 0.5725190839694656,\n \"acc_norm_stderr\": 0.04338920305792401\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.6942148760330579,\n \"acc_stderr\": 0.04205953933884123,\n \"\ acc_norm\": 0.6942148760330579,\n \"acc_norm_stderr\": 0.04205953933884123\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.6018518518518519,\n\ \ \"acc_stderr\": 0.04732332615978813,\n \"acc_norm\": 0.6018518518518519,\n\ \ \"acc_norm_stderr\": 0.04732332615978813\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.6196319018404908,\n \"acc_stderr\": 0.038142698932618374,\n\ \ \"acc_norm\": 0.6196319018404908,\n \"acc_norm_stderr\": 0.038142698932618374\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.41964285714285715,\n\ \ \"acc_stderr\": 0.04684099321077106,\n \"acc_norm\": 0.41964285714285715,\n\ \ \"acc_norm_stderr\": 0.04684099321077106\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.6407766990291263,\n \"acc_stderr\": 0.047504583990416946,\n\ \ \"acc_norm\": 0.6407766990291263,\n \"acc_norm_stderr\": 0.047504583990416946\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7863247863247863,\n\ \ \"acc_stderr\": 0.02685345037700916,\n \"acc_norm\": 0.7863247863247863,\n\ \ \"acc_norm_stderr\": 0.02685345037700916\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.6,\n \"acc_stderr\": 0.049236596391733084,\n \ \ \"acc_norm\": 0.6,\n \"acc_norm_stderr\": 0.049236596391733084\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.6730523627075351,\n\ \ \"acc_stderr\": 0.016774908180131474,\n \"acc_norm\": 0.6730523627075351,\n\ \ \"acc_norm_stderr\": 0.016774908180131474\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.5635838150289018,\n \"acc_stderr\": 0.026700545424943677,\n\ \ \"acc_norm\": 0.5635838150289018,\n \"acc_norm_stderr\": 0.026700545424943677\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.23910614525139665,\n\ \ \"acc_stderr\": 0.014265554192331144,\n \"acc_norm\": 0.23910614525139665,\n\ \ \"acc_norm_stderr\": 0.014265554192331144\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.5490196078431373,\n \"acc_stderr\": 0.02849199358617156,\n\ \ \"acc_norm\": 0.5490196078431373,\n \"acc_norm_stderr\": 0.02849199358617156\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.5530546623794212,\n\ \ \"acc_stderr\": 0.028237769422085335,\n \"acc_norm\": 0.5530546623794212,\n\ \ \"acc_norm_stderr\": 0.028237769422085335\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.5462962962962963,\n \"acc_stderr\": 0.0277012284685426,\n\ \ \"acc_norm\": 0.5462962962962963,\n \"acc_norm_stderr\": 0.0277012284685426\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.3971631205673759,\n \"acc_stderr\": 0.0291898056735871,\n \ \ \"acc_norm\": 0.3971631205673759,\n \"acc_norm_stderr\": 0.0291898056735871\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3878748370273794,\n\ \ \"acc_stderr\": 0.012444998309675617,\n \"acc_norm\": 0.3878748370273794,\n\ \ \"acc_norm_stderr\": 0.012444998309675617\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.41544117647058826,\n \"acc_stderr\": 0.029935342707877743,\n\ \ \"acc_norm\": 0.41544117647058826,\n \"acc_norm_stderr\": 0.029935342707877743\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.4852941176470588,\n \"acc_stderr\": 0.020219083895133924,\n \ \ \"acc_norm\": 0.4852941176470588,\n \"acc_norm_stderr\": 0.020219083895133924\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.5818181818181818,\n\ \ \"acc_stderr\": 0.04724577405731572,\n \"acc_norm\": 0.5818181818181818,\n\ \ \"acc_norm_stderr\": 0.04724577405731572\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.6326530612244898,\n \"acc_stderr\": 0.030862144921087558,\n\ \ \"acc_norm\": 0.6326530612244898,\n \"acc_norm_stderr\": 0.030862144921087558\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.4925373134328358,\n\ \ \"acc_stderr\": 0.03535140084276719,\n \"acc_norm\": 0.4925373134328358,\n\ \ \"acc_norm_stderr\": 0.03535140084276719\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.41566265060240964,\n\ \ \"acc_stderr\": 0.038367221765980515,\n \"acc_norm\": 0.41566265060240964,\n\ \ \"acc_norm_stderr\": 0.038367221765980515\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.695906432748538,\n \"acc_stderr\": 0.03528211258245232,\n\ \ \"acc_norm\": 0.695906432748538,\n \"acc_norm_stderr\": 0.03528211258245232\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.39657282741738065,\n\ \ \"mc1_stderr\": 0.017124930942023518,\n \"mc2\": 0.5708474256962726,\n\ \ \"mc2_stderr\": 0.015744185818785193\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7324388318863457,\n \"acc_stderr\": 0.01244171845689301\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.11448066717210008,\n \ \ \"acc_stderr\": 0.008770157532110507\n }\n}\n```" repo_url: https://huggingface.co/mwitiderrick/SwahiliInstruct-v0.2 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|arc:challenge|25_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-01-10T17-14-24.591374.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|gsm8k|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hellaswag|10_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-10T17-14-24.591374.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-management|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-virology|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-10T17-14-24.591374.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|truthfulqa:mc|0_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-01-10T17-14-24.591374.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_10T17_14_24.591374 path: - '**/details_harness|winogrande|5_2024-01-10T17-14-24.591374.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-01-10T17-14-24.591374.parquet' - config_name: results data_files: - split: 2024_01_10T17_14_24.591374 path: - results_2024-01-10T17-14-24.591374.parquet - split: latest path: - results_2024-01-10T17-14-24.591374.parquet --- # Dataset Card for Evaluation run of mwitiderrick/SwahiliInstruct-v0.2 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [mwitiderrick/SwahiliInstruct-v0.2](https://huggingface.co/mwitiderrick/SwahiliInstruct-v0.2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_mwitiderrick__SwahiliInstruct-v0.2", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-10T17:14:24.591374](https://huggingface.co/datasets/open-llm-leaderboard/details_mwitiderrick__SwahiliInstruct-v0.2/blob/main/results_2024-01-10T17-14-24.591374.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": 0.5020612158374184, "acc_stderr": 0.03431570224894014, "acc_norm": 0.5085604196260874, "acc_norm_stderr": 0.03510491450294754, "mc1": 0.39657282741738065, "mc1_stderr": 0.017124930942023518, "mc2": 0.5708474256962726, "mc2_stderr": 0.015744185818785193 }, "harness|arc:challenge|25": { "acc": 0.514505119453925, "acc_stderr": 0.014605241081370056, "acc_norm": 0.5520477815699659, "acc_norm_stderr": 0.014532011498211678 }, "harness|hellaswag|10": { "acc": 0.5935072694682334, "acc_stderr": 0.004901747426331732, "acc_norm": 0.7822146982672774, "acc_norm_stderr": 0.004118971487050471 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.45185185185185184, "acc_stderr": 0.04299268905480864, "acc_norm": 0.45185185185185184, "acc_norm_stderr": 0.04299268905480864 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.46710526315789475, "acc_stderr": 0.040601270352363966, "acc_norm": 0.46710526315789475, "acc_norm_stderr": 0.040601270352363966 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.49, "acc_stderr": 0.05024183937956911, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956911 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5132075471698113, "acc_stderr": 0.030762134874500476, "acc_norm": 0.5132075471698113, "acc_norm_stderr": 0.030762134874500476 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5416666666666666, "acc_stderr": 0.04166666666666666, "acc_norm": 0.5416666666666666, "acc_norm_stderr": 0.04166666666666666 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.38, "acc_stderr": 0.048783173121456344, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456344 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.26, "acc_stderr": 0.04408440022768078, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768078 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4913294797687861, "acc_stderr": 0.038118909889404126, "acc_norm": 0.4913294797687861, "acc_norm_stderr": 0.038118909889404126 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.28431372549019607, "acc_stderr": 0.04488482852329017, "acc_norm": 0.28431372549019607, "acc_norm_stderr": 0.04488482852329017 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.62, "acc_stderr": 0.048783173121456316, "acc_norm": 0.62, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4553191489361702, "acc_stderr": 0.03255525359340354, "acc_norm": 0.4553191489361702, "acc_norm_stderr": 0.03255525359340354 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.35964912280701755, "acc_stderr": 0.045144961328736334, "acc_norm": 0.35964912280701755, "acc_norm_stderr": 0.045144961328736334 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.46206896551724136, "acc_stderr": 0.04154659671707548, "acc_norm": 0.46206896551724136, "acc_norm_stderr": 0.04154659671707548 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.37037037037037035, "acc_stderr": 0.0248708152510571, "acc_norm": 0.37037037037037035, "acc_norm_stderr": 0.0248708152510571 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.30952380952380953, "acc_stderr": 0.04134913018303316, "acc_norm": 0.30952380952380953, "acc_norm_stderr": 0.04134913018303316 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.42258064516129035, "acc_stderr": 0.02810096472427264, "acc_norm": 0.42258064516129035, "acc_norm_stderr": 0.02810096472427264 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.35960591133004927, "acc_stderr": 0.033764582465095665, "acc_norm": 0.35960591133004927, "acc_norm_stderr": 0.033764582465095665 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6424242424242425, "acc_stderr": 0.03742597043806587, "acc_norm": 0.6424242424242425, "acc_norm_stderr": 0.03742597043806587 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6616161616161617, "acc_stderr": 0.03371124142626301, "acc_norm": 0.6616161616161617, "acc_norm_stderr": 0.03371124142626301 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6994818652849741, "acc_stderr": 0.033088185944157494, "acc_norm": 0.6994818652849741, "acc_norm_stderr": 0.033088185944157494 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.41794871794871796, "acc_stderr": 0.02500732988246122, "acc_norm": 0.41794871794871796, "acc_norm_stderr": 0.02500732988246122 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.32222222222222224, "acc_stderr": 0.028493465091028597, "acc_norm": 0.32222222222222224, "acc_norm_stderr": 0.028493465091028597 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.453781512605042, "acc_stderr": 0.03233943468182088, "acc_norm": 0.453781512605042, "acc_norm_stderr": 0.03233943468182088 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.304635761589404, "acc_stderr": 0.03757949922943343, "acc_norm": 0.304635761589404, "acc_norm_stderr": 0.03757949922943343 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.655045871559633, "acc_stderr": 0.020380605405066952, "acc_norm": 0.655045871559633, "acc_norm_stderr": 0.020380605405066952 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.375, "acc_stderr": 0.033016908987210894, "acc_norm": 0.375, "acc_norm_stderr": 0.033016908987210894 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.6862745098039216, "acc_stderr": 0.03256685484460389, "acc_norm": 0.6862745098039216, "acc_norm_stderr": 0.03256685484460389 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7215189873417721, "acc_stderr": 0.029178682304842548, "acc_norm": 0.7215189873417721, "acc_norm_stderr": 0.029178682304842548 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6188340807174888, "acc_stderr": 0.03259625118416827, "acc_norm": 0.6188340807174888, "acc_norm_stderr": 0.03259625118416827 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.5725190839694656, "acc_stderr": 0.04338920305792401, "acc_norm": 0.5725190839694656, "acc_norm_stderr": 0.04338920305792401 }, "harness|hendrycksTest-international_law|5": { "acc": 0.6942148760330579, "acc_stderr": 0.04205953933884123, "acc_norm": 0.6942148760330579, "acc_norm_stderr": 0.04205953933884123 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.6018518518518519, "acc_stderr": 0.04732332615978813, "acc_norm": 0.6018518518518519, "acc_norm_stderr": 0.04732332615978813 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.6196319018404908, "acc_stderr": 0.038142698932618374, "acc_norm": 0.6196319018404908, "acc_norm_stderr": 0.038142698932618374 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.41964285714285715, "acc_stderr": 0.04684099321077106, "acc_norm": 0.41964285714285715, "acc_norm_stderr": 0.04684099321077106 }, "harness|hendrycksTest-management|5": { "acc": 0.6407766990291263, "acc_stderr": 0.047504583990416946, "acc_norm": 0.6407766990291263, "acc_norm_stderr": 0.047504583990416946 }, "harness|hendrycksTest-marketing|5": { "acc": 0.7863247863247863, "acc_stderr": 0.02685345037700916, "acc_norm": 0.7863247863247863, "acc_norm_stderr": 0.02685345037700916 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.6, "acc_stderr": 0.049236596391733084, "acc_norm": 0.6, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.6730523627075351, "acc_stderr": 0.016774908180131474, "acc_norm": 0.6730523627075351, "acc_norm_stderr": 0.016774908180131474 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.5635838150289018, "acc_stderr": 0.026700545424943677, "acc_norm": 0.5635838150289018, "acc_norm_stderr": 0.026700545424943677 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.23910614525139665, "acc_stderr": 0.014265554192331144, "acc_norm": 0.23910614525139665, "acc_norm_stderr": 0.014265554192331144 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.5490196078431373, "acc_stderr": 0.02849199358617156, "acc_norm": 0.5490196078431373, "acc_norm_stderr": 0.02849199358617156 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.5530546623794212, "acc_stderr": 0.028237769422085335, "acc_norm": 0.5530546623794212, "acc_norm_stderr": 0.028237769422085335 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.5462962962962963, "acc_stderr": 0.0277012284685426, "acc_norm": 0.5462962962962963, "acc_norm_stderr": 0.0277012284685426 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.3971631205673759, "acc_stderr": 0.0291898056735871, "acc_norm": 0.3971631205673759, "acc_norm_stderr": 0.0291898056735871 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.3878748370273794, "acc_stderr": 0.012444998309675617, "acc_norm": 0.3878748370273794, "acc_norm_stderr": 0.012444998309675617 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.41544117647058826, "acc_stderr": 0.029935342707877743, "acc_norm": 0.41544117647058826, "acc_norm_stderr": 0.029935342707877743 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.4852941176470588, "acc_stderr": 0.020219083895133924, "acc_norm": 0.4852941176470588, "acc_norm_stderr": 0.020219083895133924 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.5818181818181818, "acc_stderr": 0.04724577405731572, "acc_norm": 0.5818181818181818, "acc_norm_stderr": 0.04724577405731572 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6326530612244898, "acc_stderr": 0.030862144921087558, "acc_norm": 0.6326530612244898, "acc_norm_stderr": 0.030862144921087558 }, "harness|hendrycksTest-sociology|5": { "acc": 0.4925373134328358, "acc_stderr": 0.03535140084276719, "acc_norm": 0.4925373134328358, "acc_norm_stderr": 0.03535140084276719 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-virology|5": { "acc": 0.41566265060240964, "acc_stderr": 0.038367221765980515, "acc_norm": 0.41566265060240964, "acc_norm_stderr": 0.038367221765980515 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.695906432748538, "acc_stderr": 0.03528211258245232, "acc_norm": 0.695906432748538, "acc_norm_stderr": 0.03528211258245232 }, "harness|truthfulqa:mc|0": { "mc1": 0.39657282741738065, "mc1_stderr": 0.017124930942023518, "mc2": 0.5708474256962726, "mc2_stderr": 0.015744185818785193 }, "harness|winogrande|5": { "acc": 0.7324388318863457, "acc_stderr": 0.01244171845689301 }, "harness|gsm8k|5": { "acc": 0.11448066717210008, "acc_stderr": 0.008770157532110507 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
Multimodal-Fatima/TinyImagenet_validation
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': goldfish '1': fire salamander '2': american bullfrog '3': tailed frog '4': american alligator '5': boa constrictor '6': trilobite '7': scorpion '8': southern black widow '9': tarantula '10': centipede '11': koala '12': jellyfish '13': brain coral '14': snail '15': sea slug '16': american lobster '17': spiny lobster '18': black stork '19': king penguin '20': albatross '21': dugong '22': yorkshire terrier '23': golden retriever '24': labrador retriever '25': german shepherd dog '26': standard poodle '27': tabby cat '28': persian cat '29': egyptian mau '30': cougar '31': lion '32': brown bear '33': ladybug '34': grasshopper '35': stick insect '36': cockroach '37': praying mantis '38': dragonfly '39': monarch butterfly '40': sulphur butterfly '41': sea cucumber '42': guinea pig '43': pig '44': ox '45': bison '46': bighorn sheep '47': gazelle '48': arabian camel '49': orangutan '50': chimpanzee '51': baboon '52': african bush elephant '53': red panda '54': abacus '55': academic gown '56': altar '57': backpack '58': baluster / handrail '59': barbershop '60': barn '61': barrel '62': basketball '63': bathtub '64': station wagon '65': lighthouse '66': beaker '67': beer bottle '68': bikini '69': binoculars '70': birdhouse '71': bow tie '72': brass memorial plaque '73': bucket '74': high speed train '75': butcher shop '76': candle '77': cannon '78': cardigan '79': automated teller machine '80': cd player '81': storage chest '82': christmas stocking '83': cliff dwelling '84': computer keyboard '85': candy store '86': convertible '87': crane bird '88': dam '89': desk '90': dining table '91': dumbbell '92': flagpole '93': fly '94': fountain '95': freight car '96': frying pan '97': fur coat '98': gas mask or respirator '99': go kart '100': gondola '101': hourglass '102': ipod '103': rickshaw '104': kimono '105': lampshade '106': lawn mower '107': lifeboat '108': limousine '109': magnetic compass '110': maypole '111': military uniform '112': miniskirt '113': moving van '114': neck brace '115': obelisk '116': oboe '117': pipe organ '118': parking meter '119': payphone '120': picket fence '121': pill bottle '122': plunger '123': police van '124': poncho '125': soda bottle '126': potter's wheel '127': missile '128': punching bag '129': refrigerator '130': remote control '131': rocking chair '132': rugby ball '133': sandal '134': school bus '135': scoreboard '136': sewing machine '137': snorkel '138': sock '139': sombrero '140': space heater '141': spider web '142': sports car '143': through arch bridge '144': stopwatch '145': sunglasses '146': suspension bridge '147': swim trunks / shorts '148': syringe '149': teapot '150': teddy bear '151': thatched roof '152': torch '153': tractor '154': triumphal arch '155': trolleybus '156': turnstile '157': umbrella '158': vestment '159': viaduct '160': volleyball '161': water jug '162': water tower '163': wok '164': wooden spoon '165': comic book '166': fishing casting reel '167': guacamole '168': ice cream '169': popsicle '170': goose '171': drumstick '172': plate '173': pretzel '174': mashed potatoes '175': cauliflower '176': bell pepper '177': lemon '178': banana '179': pomegranate '180': meatloaf '181': pizza '182': pot pie '183': espresso '184': bee '185': apron '186': pole '187': chihuahua '188': mountain '189': cliff '190': coral reef '191': lakeshore '192': beach '193': acorn '194': broom '195': mushroom '196': metal nail '197': chain '198': slug '199': orange - name: id dtype: int64 - name: Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full sequence: string - name: Attributes_ViT_L_14_descriptors_text_davinci_003_full sequence: string - name: clip_tags_ViT_L_14_simple_specific dtype: string - name: clip_tags_ViT_L_14_ensemble_specific dtype: string - name: clip_tags_LAION_ViT_H_14_2B_simple_specific dtype: string - name: clip_tags_LAION_ViT_H_14_2B_ensemble_specific dtype: string splits: - name: validation num_bytes: 25528461.0 num_examples: 10000 download_size: 15791743 dataset_size: 25528461.0 --- # Dataset Card for "TinyImagenet_validation" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
haseong8012/child-10k
--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: text dtype: string - name: audio sequence: float32 splits: - name: train num_bytes: 2077216016 num_examples: 10000 download_size: 1810220972 dataset_size: 2077216016 --- # Dataset Card for "korean-child-command-voice_train-0-10000_smaplingRate-16000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
alpayariyak/IAM_Sentences_LLaVA
--- dataset_info: features: - name: image dtype: image - name: id dtype: string - name: conversations dtype: string splits: - name: train num_bytes: 1053875995.077 num_examples: 5663 download_size: 1128902513 dataset_size: 1053875995.077 --- # Dataset Card for "IAM_Sentences_LLaVA" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)