Datasets:
davanstrien
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summary-test

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Anssi/europarl_dbca_splits
--- configs: - config_name: comdiv0.0_en_fr data_files: - split: train path: "comdiv0.0_en_fr/train.jsonl" - split: test path: "comdiv0.0_en_fr/test.jsonl" - config_name: comdiv0.0_en_de data_files: - split: train path: "comdiv0.0_en_de/train.jsonl" - split: test path: "comdiv0.0_en_de/test.jsonl" - config_name: comdiv0.0_en_fi data_files: - split: train path: "comdiv0.0_en_fi/train.jsonl" - split: test path: "comdiv0.0_en_fi/test.jsonl" - config_name: comdiv0.0_en_el data_files: - split: train path: "comdiv0.0_en_el/train.jsonl" - split: test path: "comdiv0.0_en_el/test.jsonl" - config_name: comdiv1.0_en_fr data_files: - split: train path: "comdiv1.0_en_fr/train.jsonl" - split: test path: "comdiv1.0_en_fr/test.jsonl" - config_name: comdiv1.0_en_de data_files: - split: train path: "comdiv1.0_en_de/train.jsonl" - split: test path: "comdiv1.0_en_de/test.jsonl" - config_name: comdiv1.0_en_fi data_files: - split: train path: "comdiv1.0_en_fi/train.jsonl" - split: test path: "comdiv1.0_en_fi/test.jsonl" - config_name: comdiv1.0_en_el data_files: - split: train path: "comdiv1.0_en_el/train.jsonl" - split: test path: "comdiv1.0_en_el/test.jsonl" ---
lsimon/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: login dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: avatar_url dtype: string - name: gravatar_id dtype: string - name: url dtype: string - name: html_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: organizations_url dtype: string - name: repos_url dtype: string - name: events_url dtype: string - name: received_events_url dtype: string - name: type dtype: string - name: site_admin dtype: bool - name: labels list: - name: id dtype: int64 - name: node_id dtype: string - name: url dtype: string - name: name dtype: string - name: color dtype: string - name: default dtype: bool - name: description dtype: string - name: state dtype: string - name: locked dtype: bool - name: assignee struct: - name: login dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: avatar_url dtype: string - name: gravatar_id dtype: string - name: url dtype: string - name: html_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: organizations_url dtype: string - name: repos_url dtype: string - name: events_url dtype: string - name: received_events_url dtype: string - name: type dtype: string - name: site_admin dtype: bool - name: assignees list: - name: login dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: avatar_url dtype: string - name: gravatar_id dtype: string - name: url dtype: string - name: html_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: organizations_url dtype: string - name: repos_url dtype: string - name: events_url dtype: string - name: received_events_url dtype: string - name: type dtype: string - name: site_admin dtype: bool - name: milestone struct: - name: url dtype: string - name: html_url dtype: string - name: labels_url dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: number dtype: int64 - name: title dtype: string - name: description dtype: string - name: creator struct: - name: login dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: avatar_url dtype: string - name: gravatar_id dtype: string - name: url dtype: string - name: html_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: organizations_url dtype: string - name: repos_url dtype: string - name: events_url dtype: string - name: received_events_url dtype: string - name: type dtype: string - name: site_admin dtype: bool - name: open_issues dtype: int64 - name: closed_issues dtype: int64 - name: state dtype: string - name: created_at dtype: timestamp[s] - name: updated_at dtype: timestamp[s] - name: due_on dtype: 'null' - name: closed_at dtype: 'null' - name: comments sequence: string - name: created_at dtype: timestamp[s] - name: updated_at dtype: timestamp[s] - name: closed_at dtype: timestamp[s] - name: author_association dtype: string - name: active_lock_reason dtype: 'null' - name: draft dtype: bool - name: pull_request struct: - name: url dtype: string - name: html_url dtype: string - name: diff_url dtype: string - name: patch_url dtype: string - name: merged_at dtype: timestamp[s] - name: body dtype: string - name: reactions struct: - name: url dtype: string - name: total_count dtype: int64 - name: '+1' dtype: int64 - name: '-1' dtype: int64 - name: laugh dtype: int64 - name: hooray dtype: int64 - name: confused dtype: int64 - name: heart dtype: int64 - name: rocket dtype: int64 - name: eyes dtype: int64 - name: timeline_url dtype: string - name: performed_via_github_app dtype: 'null' - name: state_reason dtype: string - name: is_pull_request dtype: bool splits: - name: train num_bytes: 5004849 num_examples: 500 download_size: 1349309 dataset_size: 5004849 --- # Dataset Card for "github-issues" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
nlplabtdtu/OpenOrca-processes-QA-vi
--- dataset_info: features: - name: id dtype: string - name: system_prompt dtype: string - name: question dtype: string - name: response dtype: string splits: - name: train num_bytes: 36733040 num_examples: 32860 download_size: 12971853 dataset_size: 36733040 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "OpenOrca-processes-QA-vi" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
kartikagg98/HINMIX_hi-en
--- license: apache-2.0 dataset_info: - config_name: lcsalign-en features: - name: text dtype: string splits: - name: test num_bytes: 305023 num_examples: 2507 - name: train num_bytes: 455104487 num_examples: 4200000 - name: valid num_bytes: 21217 num_examples: 280 download_size: 318440274 dataset_size: 455430727 - config_name: lcsalign-hi features: - name: text dtype: string splits: - name: test num_bytes: 770118 num_examples: 2507 - name: train num_bytes: 1084853757 num_examples: 4200000 - name: valid num_bytes: 45670 num_examples: 280 download_size: 470820787 dataset_size: 1085669545 - config_name: lcsalign-hicm features: - name: text dtype: string splits: - name: test num_bytes: 561442 num_examples: 2507 - name: train num_bytes: 872213032 num_examples: 4200000 - name: valid num_bytes: 34530 num_examples: 280 download_size: 455501891 dataset_size: 872809004 - config_name: lcsalign-hicmdvg features: - name: text dtype: string splits: - name: test num_bytes: 798126 num_examples: 2507 - name: train num_bytes: 1104443176 num_examples: 4200000 - name: valid num_bytes: 47513 num_examples: 280 download_size: 491775164 dataset_size: 1105288815 - config_name: lcsalign-hicmrom features: - name: text dtype: string splits: - name: test num_bytes: 338176 num_examples: 2507 - name: train num_bytes: 467370942 num_examples: 4200000 - name: valid num_bytes: 20431 num_examples: 280 download_size: 337385029 dataset_size: 467729549 - config_name: lcsalign-noisyhicmrom features: - name: text dtype: string splits: - name: train num_bytes: 462418855 num_examples: 4200000 - name: test num_bytes: 334401 num_examples: 2507 - name: valid num_bytes: 20246 num_examples: 280 download_size: 379419827 dataset_size: 462773502 configs: - config_name: lcsalign-en data_files: - split: test path: lcsalign-en/test-* - split: train path: lcsalign-en/train-* - split: valid path: lcsalign-en/valid-* - config_name: lcsalign-hi data_files: - split: test path: lcsalign-hi/test-* - split: train path: lcsalign-hi/train-* - split: valid path: lcsalign-hi/valid-* - config_name: lcsalign-hicm data_files: - split: test path: lcsalign-hicm/test-* - split: train path: lcsalign-hicm/train-* - split: valid path: lcsalign-hicm/valid-* - config_name: lcsalign-hicmdvg data_files: - split: test path: lcsalign-hicmdvg/test-* - split: train path: lcsalign-hicmdvg/train-* - split: valid path: lcsalign-hicmdvg/valid-* - config_name: lcsalign-hicmrom data_files: - split: test path: lcsalign-hicmrom/test-* - split: train path: lcsalign-hicmrom/train-* - split: valid path: lcsalign-hicmrom/valid-* - config_name: lcsalign-noisyhicmrom data_files: - split: train path: lcsalign-noisyhicmrom/train-* - split: test path: lcsalign-noisyhicmrom/test-* - split: valid path: lcsalign-noisyhicmrom/valid-* task_categories: - translation language: - hi - en tags: - codemix - indicnlp - hindi - english - multilingual pretty_name: Hindi-English Codemix Datasets size_categories: - 1M<n<10M ---
anderloh/5ClassMotorizedLarge
--- dataset_info: - config_name: finetune features: - name: audio dtype: audio - name: label dtype: class_label: names: '0': Helicopter '1': Jet '2': Racecar '3': Train_ '4': Truck splits: - name: train num_bytes: 448111066.0 num_examples: 2000 - name: validation num_bytes: 224056125.0 num_examples: 1000 download_size: 672179128 dataset_size: 672167191.0 - config_name: pretraining features: - name: audio dtype: audio - name: label dtype: class_label: names: '0': Helicopter '1': Jet '2': Racecar '3': Train_ '4': Truck splits: - name: train num_bytes: 2381396801.811 num_examples: 10629 - name: test num_bytes: 905396784.689 num_examples: 4041 download_size: 3286168021 dataset_size: 3286793586.5 configs: - config_name: finetune data_files: - split: train path: finetune/train-* - split: validation path: finetune/validation-* - config_name: pretraining data_files: - split: train path: pretraining/train-* - split: test path: pretraining/test-* --- # Dataset Card for "5ClassMotorizedLarge" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
liuyanchen1015/MULTI_VALUE_rte_more_much
--- 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: 80145 num_examples: 187 - name: train num_bytes: 84239 num_examples: 189 download_size: 117525 dataset_size: 164384 --- # Dataset Card for "MULTI_VALUE_rte_more_much" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
parambharat/tamil_asr_corpus
--- annotations_creators: - found language: - ta language_creators: - found license: - cc-by-4.0 multilinguality: - monolingual pretty_name: Tamil ASR Corpus size_categories: - 100K<n<1M source_datasets: - extended|common_voice - extended|openslr tags: [] task_categories: - automatic-speech-recognition task_ids: [] --- # Dataset Card for [Dataset Name] ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary [More Information Needed] ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions Thanks to [@parambharat](https://github.com/parambharat) for adding this dataset.
datahrvoje/twitter_dataset_1713194546
--- 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: 9457 num_examples: 23 download_size: 9806 dataset_size: 9457 configs: - config_name: default data_files: - split: train path: data/train-* ---
communityai/Telugu-LLM-Labs___telugu_alpaca_yahma_cleaned_filtered_romanized
--- dataset_info: features: - name: source dtype: string - name: conversations list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 85288011.0 num_examples: 28910 download_size: 29059985 dataset_size: 85288011.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
odepraz/rvl_cdip_5percentofdata
--- license: unknown ---
EleutherAI/pile
--- annotations_creators: - no-annotation language_creators: - found language: - en license: other multilinguality: - monolingual pretty_name: the Pile size_categories: - 100B<n<1T source_datasets: - original task_categories: - text-generation - fill-mask task_ids: - language-modeling - masked-language-modeling paperswithcode_id: the-pile --- # Dataset Card for The Pile ## 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) This model card is a work in progress. Please also see [our datasheet](https://arxiv.org/abs/2201.07311) for more detailed info. ## Dataset Description - **Homepage:** https://pile.eleuther.ai/ - **Repository:** https://github.com/EleutherAI/the-pile - **Paper:** [The Pile: An 800GB Dataset of Diverse Text for Language Modeling](https://arxiv.org/abs/2101.00027) - **Leaderboard:** - **Point of Contact:** [EleutherAI](mailto:contact@eleuther.ai) - **Datasheet:** [Datasheet for the Pile](https://arxiv.org/abs/2201.07311) ### Dataset Summary The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality datasets combined together. ### Supported Tasks and Leaderboards [More Information Needed] ### Languages This dataset is in English (`EN`). ## Dataset Structure ### Data Instances #### all ``` { 'meta': {'pile_set_name': 'Pile-CC'}, 'text': 'It is done, and submitted. You can play “Survival of the Tastiest” on Android, and on the web. Playing on...' } ``` <details> <summary>Expand to see individual components</summary> #### enron_emails ``` { 'text': 'Name\t\t\tNew Title\t\t\t\tEffective Date\t\t\tMid Year promotion Yes/No\n\nFloyd, Jodie\t\tSr Cust Svc Rep (no change)\t\t7/16/01\t\t\t\tNo\n\nBuehler, Craig\t\tSr Mkt/Sup Analyst (no change)\t\t7/16/01\t\t\t\tNo\n\nWagoner, Mike\t\tTeam Advisor - Gas Control\t\t7/1/01\t\t\t\tNo\n\nClapper, Karen\t\tSr Cust Svc Rep\t\t\t8/1/01\t\t\t\tYes\n\nGreaney, Chris\t\tSr Cust Svc Rep\t\t\t8/1/01\t\t\t\tYes\n\nWilkens, Jerry\t\tSr Cust Svc Rep\t\t\t8/1/01\t\t\t\tYes\n\nMinton, Kevin\t\tPipeline Controller\t\t\t8/1/01\t\t\t\tYes\n\nCox, Don\t\tPipeline Controller\t\t\t8/1/01\t\t\t\tYes\n\nHanagriff, Richard\tSr Accounting Control Spec\t\t8/1/01\t\t\t\tYes\n\n\nThanks,\nMS' 'meta': "{}", } ``` #### europarl ``` { 'text': 'Uvádění biocidních přípravků na trh - Nový návrh revize týkající se biocidních přípravků (rozprava) \nPředsedající\nDalším bodem je společná rozprava o následujících tématech:\nzpráva paní Sârbuové za Výbor pro životní prostředí, veřejné zdraví a bezpečnost potravin o návrhu...' 'meta': "{'language': 'cs'}", } ``` #### free_law ``` { 'meta': "{'case_jurisdiction': 'scotus.tar.gz', 'case_ID': '110921.json','date_created': '2010-04-28T17:12:49Z'}", 'text': '\n461 U.S. 238 (1983)\nOLIM ET AL.\nv.\nWAKINEKONA\nNo. 81-1581.\nSupreme Court of United States.\nArgued...' } ``` #### hacker_news ``` { 'text': "\nChina Deserves Donald Trump - rm2889\nhttps://www.nytimes.com/2019/05/21/opinion/china-trump-trade.html\n======\nNotPaidToPost\n> so he’d be wise to curb his nationalistic “no-one-tells-China-what-to-do”\n> bluster\n\nThis comment highlights both ignorance of Chinese history and continuing\nAmerican arrogance.\n\nChina has been painfully dictated what to do during the last 200 years. This\nhas had a profound effect on the country and has led to the collapse of\nimperial rule and the drive to 'rejuvenate'...", 'meta': "{'id': '19979654'}", } ``` #### nih_exporter ``` { 'text': "The National Domestic Violence Hotline (NDVH) and the National Dating Abuse Helpline (NDAH), which are supported by the Division of Family Violence Prevention and Services within the Family and Youth Services Bureau, serve as critical partners in the intervention, prevention, and resource assistance efforts of the network of family violence, domestic violence, and dating violence service providers. They provide crisis intervention and support services; information about resources on domestic...", 'meta': " {'APPLICATION_ID': 100065}", } ``` #### pubmed ``` { 'meta': {'pmid': 11409574, 'language': 'eng'}, 'text': 'Epidemiology of hypoxaemia in children with acute lower respiratory infection.\nTo determine the prevalence of hypoxaemia in children aged under 5 years suffering acute lower respiratory infections (ALRI), the risk factors for hypoxaemia in children under 5 years of age with ALRI, and the association of hypoxaemia with an increased risk of dying in children of the same age. Systematic review of the published literature. Out-patient clinics, emergency departments and hospitalisation wards in 23 health centres from 10 countries. Cohort studies reporting the frequency of hypoxaemia in children under 5 years of age with ALRI, and the association between hypoxaemia and the risk of dying. Prevalence of hypoxaemia measured in children with ARI and relative risks for the association between the severity of illness and the frequency of hypoxaemia, and between hypoxaemia and the risk of dying. Seventeen published studies were found that included 4,021 children under 5 with acute respiratory infections (ARI) and reported the prevalence of hypoxaemia. Out-patient children and those with a clinical diagnosis of upper ARI had a low risk of hypoxaemia (pooled estimate of 6% to 9%). The prevalence increased to 31% and to 43% in patients in emergency departments and in cases with clinical pneumonia, respectively, and it was even higher among hospitalised children (47%) and in those with radiographically confirmed pneumonia (72%). The cumulated data also suggest that hypoxaemia is more frequent in children living at high altitude. Three papers reported an association between hypoxaemia and death, with relative risks varying between 1.4 and 4.6. Papers describing predictors of hypoxaemia have focused on clinical signs for detecting hypoxaemia rather than on identifying risk factors for developing this complication. Hypoxaemia is a common and potentially lethal complication of ALRI in children under 5, particularly among those with severe disease and those living at high altitude. Given the observed high prevalence of hypoxaemia and its likely association with increased mortality, efforts should be made to improve the detection of hypoxaemia and to provide oxygen earlier to more children with severe ALRI.' } ``` #### pubmed_central ``` { 'meta': "{id': 'PMC5595690'}", 'text': 'Introduction {#acel12642-sec-0001}\n============\n\nAlzheimer\\\'s disease (AD), the most common cause of...' } ``` #### ubuntu_irc ``` { 'text': "#ubuntu 2004-07-05\n* Window 3\n* \tServer: [0] <None>\n* \tScreen: 0x817e90c\n* \tGeometry Info: [0 11 0 11 11 11] \n* \tCO, LI are [94 49] \n* \tCurrent channel: #ubuntu\n* \tQuery User: <None> \n*\tPrompt: <None>\n* \tSecond status line is OFF\n* \tSplit line is ON triple is OFF\n* \tLogging is ON\n* \tLogfile is irclogs/ubuntu.log\n* \tNotification is OFF\n* \tHold mode is OFF\n* \tWindow level is NONE\n* \tLastlog level is ALL\n* \tNotify level is ALL\n<mdz> lifeless: using tla effectively for all packages in Warty requ...", 'meta': "{'channel': 'ubuntu', 'month': 7}" } ``` #### uspto ``` { 'text': "1. Field of the Invention\nIn an extensive plant breeding program, Grant Merrill, originator and now deceased, originated a large number of new and distinct varieties of fruit trees, and which included the herein-claimed variety of peach tree. Such plant breeding program was undertaken in originator's experimental orchard located near Exeter, Tulare County, Calif.\n2. Prior Varieties\nAmong the existent varieties of peach trees which were known to originator, particular reference is made to Gemfree (U.S. Plant Pat. No. 1,409) and June Lady (U.S. Plant Pat. No. 3,022) hereinafter mentioned for the purpose of comparison.", 'meta': "{'bibliographic_information': {'Patent Number': 'PP0049700', 'Series Code': '6', 'Application Number': '2845415', 'Application Type': '6', 'Art unit': '337', 'Application Filing Date': '19810720', 'Title of Invention': 'Peach tree (A3-10)', 'Issue Date': '19830104', 'Number of Claims': '1', 'Exemplary Claim Number(s)': '1', 'Primary Examiner': 'Bagwill; Robert E.', 'Number of Drawing Sheets': '1', 'Number of figures': '1'}, 'source_file': 'https://bulkdata.uspto.gov/data/patent/grant/redbook/fulltext/1983/pftaps19830104_wk01.zip', 'abstract': 'A peach tree which is large, vigorous, and spreading; foliated with large, lanceolate leaves having a finely serrate margin, a petiole of medium length and thickness, and medium size, reniform glands; blooms from medium size, conic, plump, pubescent buds; the flowers, medium in blooming period compared with other varieties, being of medium size, and pink; and is a regular and very productive bearer of medium but variable size, round truncate, clingstone fruit having yellow skin substantially overspread with red, yellow flesh mottled with red adjacent the skin, and an amber stone.', 'classifications': [{'OCL': ['Plt', '43'], 'EDF': ['3'], 'ICL': ['A01H', '503'], 'FSC': ['Plt'], 'FSS': ['43']}], 'inventors': [{'inventor name': 'Merrill, deceased; Grant', 'Street': '325 Breese Ave.', 'City': 'late of Red Bluff', 'State': 'CA'}, {'inventor name': 'Merrill, executrix; by Lucile B.', 'Street': '325 Breese Ave.', 'City': 'Red Bluff', 'State': 'CA', 'Zip code': '96080'}]}" } ``` #### github ``` { 'text': "/* filesystem.c\n * Filesystem utility routines\n *\n * Wireshark - Network traffic analyzer\n * By Gerald Combs <gerald@wireshark.org>\n * Copyright 1998 Gerald Combs\n *\n * SPDX-License-Identifier: GPL-2.0-or-later\n */\n\n#include <config.h>\n\n#include <stdio.h>\n#include <stdlib.h>\n#include <string.h>\n#include <errno.h>\n\n#include <glib.h>...", 'meta': "{'repo_name': 'wireshark/wireshark', 'stars': '2789', 'repo_language': 'C', 'file_name': 'packet-mpeg-audio-template.c', 'mime_type': 'text/x-c'}" } ``` </details> ### Data Fields #### all - `text` (str): Text. - `meta` (dict): Metadata of the data instance with keys: - pile_set_name: Name of the subset. <details> <summary>Expand to see individual components</summary> #### enron_emails - `text` (str): Text. - `meta` (str): Metadata of the data instance. #### europarl - `text` (str): Text. - `meta` (str): Metadata of the data instance with: language. #### free_law - `text` (str): Text. - `meta` (str): Metadata of the data instance with: case_ID, case_jurisdiction, date_created. #### hacker_news - `text` (str): Text. - `meta` (str): Metadata of the data instance with: id. #### nih_exporter - `text` (str): Text. - `meta` (str): Metadata of the data instance with: APPLICATION_ID. #### pubmed - `text` (str): Text. - `meta` (str): Metadata of the data instance with: pmid, language. #### pubmed_central - `text` (str): Text. - `meta` (str): Metadata of the data instance with: ID of the data instance. #### ubuntu_irc - `text` (str): Text. - `meta` (str): Metadata of the data instance with: channel, month. #### uspto - `text` (str): Text. - `meta` (str): Metadata of the data instance with: bibliographic_information, source_file, abstract, classifications, inventors. #### github - `text` (str): Text. - `meta` (str): Metadata of the data instance with: repo_name, stars, repo_language, file_name, mime_type. ### Data Splits The "all" configuration is composed of 3 splits: train, validation and test. </details> ## 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 This dataset was primarily curated by Leo Gao and Stella Biderman, with assistance from other authors of the Pile paper. ### Licensing Information Please refer to the specific license depending on the subset you use: - PubMed Central: [MIT License](https://github.com/EleutherAI/pile-pubmedcentral/blob/master/LICENSE) ### Citation Information ``` @article{gao2020pile, title={The {P}ile: An 800{GB} dataset of diverse text for language modeling}, author={Gao, Leo and Biderman, Stella and Black, Sid and Golding, Laurence and Hoppe, Travis and Foster, Charles and Phang, Jason and He, Horace and Thite, Anish and Nabeshima, Noa and others}, journal={arXiv preprint arXiv:2101.00027}, year={2020} } @article{biderman2022datasheet, title={Datasheet for the pile}, author={Biderman, Stella and Bicheno, Kieran and Gao, Leo}, journal={arXiv preprint arXiv:2201.07311}, year={2022} } ``` ### Contributions Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
LULab/myPOS
--- license: cc-by-4.0 ---
open-llm-leaderboard/details_FuseAI__FuseChat-7B-Slerp
--- pretty_name: Evaluation run of FuseAI/FuseChat-7B-Slerp dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [FuseAI/FuseChat-7B-Slerp](https://huggingface.co/FuseAI/FuseChat-7B-Slerp) on\ \ the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_FuseAI__FuseChat-7B-Slerp\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-29T19:25:05.731431](https://huggingface.co/datasets/open-llm-leaderboard/details_FuseAI__FuseChat-7B-Slerp/blob/main/results_2024-02-29T19-25-05.731431.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\": 0.6405573713281516,\n\ \ \"acc_stderr\": 0.032222929251837,\n \"acc_norm\": 0.6422501101500138,\n\ \ \"acc_norm_stderr\": 0.032873048974703764,\n \"mc1\": 0.3072215422276622,\n\ \ \"mc1_stderr\": 0.016150201321323016,\n \"mc2\": 0.45618408792342546,\n\ \ \"mc2_stderr\": 0.015076169944832135\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5793515358361775,\n \"acc_stderr\": 0.014426211252508397,\n\ \ \"acc_norm\": 0.6262798634812287,\n \"acc_norm_stderr\": 0.014137708601759093\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6495717984465246,\n\ \ \"acc_stderr\": 0.004761289867046068,\n \"acc_norm\": 0.841665006970723,\n\ \ \"acc_norm_stderr\": 0.003643087529213717\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.5777777777777777,\n\ \ \"acc_stderr\": 0.04266763404099582,\n \"acc_norm\": 0.5777777777777777,\n\ \ \"acc_norm_stderr\": 0.04266763404099582\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6842105263157895,\n \"acc_stderr\": 0.0378272898086547,\n\ \ \"acc_norm\": 0.6842105263157895,\n \"acc_norm_stderr\": 0.0378272898086547\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.63,\n\ \ \"acc_stderr\": 0.048523658709391,\n \"acc_norm\": 0.63,\n \ \ \"acc_norm_stderr\": 0.048523658709391\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6830188679245283,\n \"acc_stderr\": 0.02863723563980089,\n\ \ \"acc_norm\": 0.6830188679245283,\n \"acc_norm_stderr\": 0.02863723563980089\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.03621034121889507,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.03621034121889507\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\ acc\": 0.46,\n \"acc_stderr\": 0.05009082659620333,\n \"acc_norm\"\ : 0.46,\n \"acc_norm_stderr\": 0.05009082659620333\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.31,\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\": 0.6473988439306358,\n\ \ \"acc_stderr\": 0.036430371689585475,\n \"acc_norm\": 0.6473988439306358,\n\ \ \"acc_norm_stderr\": 0.036430371689585475\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.4019607843137255,\n \"acc_stderr\": 0.04878608714466996,\n\ \ \"acc_norm\": 0.4019607843137255,\n \"acc_norm_stderr\": 0.04878608714466996\n\ \ },\n \"harness|hendrycksTest-computer_security|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-conceptual_physics|5\"\ : {\n \"acc\": 0.5702127659574469,\n \"acc_stderr\": 0.03236214467715564,\n\ \ \"acc_norm\": 0.5702127659574469,\n \"acc_norm_stderr\": 0.03236214467715564\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5526315789473685,\n\ \ \"acc_stderr\": 0.04677473004491199,\n \"acc_norm\": 0.5526315789473685,\n\ \ \"acc_norm_stderr\": 0.04677473004491199\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5448275862068965,\n \"acc_stderr\": 0.04149886942192117,\n\ \ \"acc_norm\": 0.5448275862068965,\n \"acc_norm_stderr\": 0.04149886942192117\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.42857142857142855,\n \"acc_stderr\": 0.025487187147859375,\n \"\ acc_norm\": 0.42857142857142855,\n \"acc_norm_stderr\": 0.025487187147859375\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.5396825396825397,\n\ \ \"acc_stderr\": 0.04458029125470973,\n \"acc_norm\": 0.5396825396825397,\n\ \ \"acc_norm_stderr\": 0.04458029125470973\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.27,\n \"acc_stderr\": 0.0446196043338474,\n \ \ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.0446196043338474\n },\n\ \ \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7870967741935484,\n\ \ \"acc_stderr\": 0.02328766512726854,\n \"acc_norm\": 0.7870967741935484,\n\ \ \"acc_norm_stderr\": 0.02328766512726854\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.49261083743842365,\n \"acc_stderr\": 0.03517603540361008,\n\ \ \"acc_norm\": 0.49261083743842365,\n \"acc_norm_stderr\": 0.03517603540361008\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\"\ : 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7636363636363637,\n \"acc_stderr\": 0.03317505930009182,\n\ \ \"acc_norm\": 0.7636363636363637,\n \"acc_norm_stderr\": 0.03317505930009182\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7777777777777778,\n \"acc_stderr\": 0.02962022787479048,\n \"\ acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.02962022787479048\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.9222797927461139,\n \"acc_stderr\": 0.019321805557223137,\n\ \ \"acc_norm\": 0.9222797927461139,\n \"acc_norm_stderr\": 0.019321805557223137\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6641025641025641,\n \"acc_stderr\": 0.02394672474156397,\n \ \ \"acc_norm\": 0.6641025641025641,\n \"acc_norm_stderr\": 0.02394672474156397\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.34074074074074073,\n \"acc_stderr\": 0.028897748741131143,\n \ \ \"acc_norm\": 0.34074074074074073,\n \"acc_norm_stderr\": 0.028897748741131143\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6554621848739496,\n \"acc_stderr\": 0.030868682604121622,\n\ \ \"acc_norm\": 0.6554621848739496,\n \"acc_norm_stderr\": 0.030868682604121622\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\": 0.8477064220183487,\n\ \ \"acc_stderr\": 0.015405084393157074,\n \"acc_norm\": 0.8477064220183487,\n\ \ \"acc_norm_stderr\": 0.015405084393157074\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\ : {\n \"acc\": 0.5231481481481481,\n \"acc_stderr\": 0.03406315360711507,\n\ \ \"acc_norm\": 0.5231481481481481,\n \"acc_norm_stderr\": 0.03406315360711507\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.7892156862745098,\n \"acc_stderr\": 0.02862654791243742,\n \"\ acc_norm\": 0.7892156862745098,\n \"acc_norm_stderr\": 0.02862654791243742\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8059071729957806,\n \"acc_stderr\": 0.025744902532290916,\n \ \ \"acc_norm\": 0.8059071729957806,\n \"acc_norm_stderr\": 0.025744902532290916\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7085201793721974,\n\ \ \"acc_stderr\": 0.030500283176545847,\n \"acc_norm\": 0.7085201793721974,\n\ \ \"acc_norm_stderr\": 0.030500283176545847\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7480916030534351,\n \"acc_stderr\": 0.03807387116306086,\n\ \ \"acc_norm\": 0.7480916030534351,\n \"acc_norm_stderr\": 0.03807387116306086\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7520661157024794,\n \"acc_stderr\": 0.03941897526516303,\n \"\ acc_norm\": 0.7520661157024794,\n \"acc_norm_stderr\": 0.03941897526516303\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7685185185185185,\n\ \ \"acc_stderr\": 0.04077494709252627,\n \"acc_norm\": 0.7685185185185185,\n\ \ \"acc_norm_stderr\": 0.04077494709252627\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.754601226993865,\n \"acc_stderr\": 0.03380939813943354,\n\ \ \"acc_norm\": 0.754601226993865,\n \"acc_norm_stderr\": 0.03380939813943354\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.44642857142857145,\n\ \ \"acc_stderr\": 0.04718471485219588,\n \"acc_norm\": 0.44642857142857145,\n\ \ \"acc_norm_stderr\": 0.04718471485219588\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.8058252427184466,\n \"acc_stderr\": 0.03916667762822583,\n\ \ \"acc_norm\": 0.8058252427184466,\n \"acc_norm_stderr\": 0.03916667762822583\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8717948717948718,\n\ \ \"acc_stderr\": 0.021901905115073325,\n \"acc_norm\": 0.8717948717948718,\n\ \ \"acc_norm_stderr\": 0.021901905115073325\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8135376756066411,\n\ \ \"acc_stderr\": 0.013927751372001512,\n \"acc_norm\": 0.8135376756066411,\n\ \ \"acc_norm_stderr\": 0.013927751372001512\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7225433526011561,\n \"acc_stderr\": 0.024105712607754307,\n\ \ \"acc_norm\": 0.7225433526011561,\n \"acc_norm_stderr\": 0.024105712607754307\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.39888268156424583,\n\ \ \"acc_stderr\": 0.01637696614261008,\n \"acc_norm\": 0.39888268156424583,\n\ \ \"acc_norm_stderr\": 0.01637696614261008\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7320261437908496,\n \"acc_stderr\": 0.025360603796242557,\n\ \ \"acc_norm\": 0.7320261437908496,\n \"acc_norm_stderr\": 0.025360603796242557\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7170418006430869,\n\ \ \"acc_stderr\": 0.02558306248998481,\n \"acc_norm\": 0.7170418006430869,\n\ \ \"acc_norm_stderr\": 0.02558306248998481\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7222222222222222,\n \"acc_stderr\": 0.02492200116888633,\n\ \ \"acc_norm\": 0.7222222222222222,\n \"acc_norm_stderr\": 0.02492200116888633\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4645390070921986,\n \"acc_stderr\": 0.029752389657427047,\n \ \ \"acc_norm\": 0.4645390070921986,\n \"acc_norm_stderr\": 0.029752389657427047\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4804432855280313,\n\ \ \"acc_stderr\": 0.012760464028289299,\n \"acc_norm\": 0.4804432855280313,\n\ \ \"acc_norm_stderr\": 0.012760464028289299\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.7022058823529411,\n \"acc_stderr\": 0.027778298701545443,\n\ \ \"acc_norm\": 0.7022058823529411,\n \"acc_norm_stderr\": 0.027778298701545443\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6650326797385621,\n \"acc_stderr\": 0.019094228167000318,\n \ \ \"acc_norm\": 0.6650326797385621,\n \"acc_norm_stderr\": 0.019094228167000318\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6636363636363637,\n\ \ \"acc_stderr\": 0.04525393596302506,\n \"acc_norm\": 0.6636363636363637,\n\ \ \"acc_norm_stderr\": 0.04525393596302506\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7224489795918367,\n \"acc_stderr\": 0.028666857790274645,\n\ \ \"acc_norm\": 0.7224489795918367,\n \"acc_norm_stderr\": 0.028666857790274645\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8258706467661692,\n\ \ \"acc_stderr\": 0.026814951200421603,\n \"acc_norm\": 0.8258706467661692,\n\ \ \"acc_norm_stderr\": 0.026814951200421603\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.88,\n \"acc_stderr\": 0.03265986323710906,\n \ \ \"acc_norm\": 0.88,\n \"acc_norm_stderr\": 0.03265986323710906\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5301204819277109,\n\ \ \"acc_stderr\": 0.03885425420866767,\n \"acc_norm\": 0.5301204819277109,\n\ \ \"acc_norm_stderr\": 0.03885425420866767\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8538011695906432,\n \"acc_stderr\": 0.027097290118070806,\n\ \ \"acc_norm\": 0.8538011695906432,\n \"acc_norm_stderr\": 0.027097290118070806\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3072215422276622,\n\ \ \"mc1_stderr\": 0.016150201321323016,\n \"mc2\": 0.45618408792342546,\n\ \ \"mc2_stderr\": 0.015076169944832135\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7947908445146015,\n \"acc_stderr\": 0.01135031570746207\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6254738438210766,\n \ \ \"acc_stderr\": 0.013331774158491391\n }\n}\n```" repo_url: https://huggingface.co/FuseAI/FuseChat-7B-Slerp 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_29T19_25_05.731431 path: - '**/details_harness|arc:challenge|25_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-29T19-25-05.731431.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|gsm8k|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hellaswag|10_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-29T19-25-05.731431.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-management|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-29T19-25-05.731431.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|truthfulqa:mc|0_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-29T19-25-05.731431.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_29T19_25_05.731431 path: - '**/details_harness|winogrande|5_2024-02-29T19-25-05.731431.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-29T19-25-05.731431.parquet' - config_name: results data_files: - split: 2024_02_29T19_25_05.731431 path: - results_2024-02-29T19-25-05.731431.parquet - split: latest path: - results_2024-02-29T19-25-05.731431.parquet --- # Dataset Card for Evaluation run of FuseAI/FuseChat-7B-Slerp <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [FuseAI/FuseChat-7B-Slerp](https://huggingface.co/FuseAI/FuseChat-7B-Slerp) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_FuseAI__FuseChat-7B-Slerp", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-29T19:25:05.731431](https://huggingface.co/datasets/open-llm-leaderboard/details_FuseAI__FuseChat-7B-Slerp/blob/main/results_2024-02-29T19-25-05.731431.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": 0.6405573713281516, "acc_stderr": 0.032222929251837, "acc_norm": 0.6422501101500138, "acc_norm_stderr": 0.032873048974703764, "mc1": 0.3072215422276622, "mc1_stderr": 0.016150201321323016, "mc2": 0.45618408792342546, "mc2_stderr": 0.015076169944832135 }, "harness|arc:challenge|25": { "acc": 0.5793515358361775, "acc_stderr": 0.014426211252508397, "acc_norm": 0.6262798634812287, "acc_norm_stderr": 0.014137708601759093 }, "harness|hellaswag|10": { "acc": 0.6495717984465246, "acc_stderr": 0.004761289867046068, "acc_norm": 0.841665006970723, "acc_norm_stderr": 0.003643087529213717 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5777777777777777, "acc_stderr": 0.04266763404099582, "acc_norm": 0.5777777777777777, "acc_norm_stderr": 0.04266763404099582 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6842105263157895, "acc_stderr": 0.0378272898086547, "acc_norm": 0.6842105263157895, "acc_norm_stderr": 0.0378272898086547 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.63, "acc_stderr": 0.048523658709391, "acc_norm": 0.63, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6830188679245283, "acc_stderr": 0.02863723563980089, "acc_norm": 0.6830188679245283, "acc_norm_stderr": 0.02863723563980089 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.75, "acc_stderr": 0.03621034121889507, "acc_norm": 0.75, "acc_norm_stderr": 0.03621034121889507 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6473988439306358, "acc_stderr": 0.036430371689585475, "acc_norm": 0.6473988439306358, "acc_norm_stderr": 0.036430371689585475 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4019607843137255, "acc_stderr": 0.04878608714466996, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.04878608714466996 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.74, "acc_stderr": 0.04408440022768079, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768079 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5702127659574469, "acc_stderr": 0.03236214467715564, "acc_norm": 0.5702127659574469, "acc_norm_stderr": 0.03236214467715564 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5526315789473685, "acc_stderr": 0.04677473004491199, "acc_norm": 0.5526315789473685, "acc_norm_stderr": 0.04677473004491199 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5448275862068965, "acc_stderr": 0.04149886942192117, "acc_norm": 0.5448275862068965, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.42857142857142855, "acc_stderr": 0.025487187147859375, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.025487187147859375 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5396825396825397, "acc_stderr": 0.04458029125470973, "acc_norm": 0.5396825396825397, "acc_norm_stderr": 0.04458029125470973 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.27, "acc_stderr": 0.0446196043338474, "acc_norm": 0.27, "acc_norm_stderr": 0.0446196043338474 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7870967741935484, "acc_stderr": 0.02328766512726854, "acc_norm": 0.7870967741935484, "acc_norm_stderr": 0.02328766512726854 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.49261083743842365, "acc_stderr": 0.03517603540361008, "acc_norm": 0.49261083743842365, "acc_norm_stderr": 0.03517603540361008 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7636363636363637, "acc_stderr": 0.03317505930009182, "acc_norm": 0.7636363636363637, "acc_norm_stderr": 0.03317505930009182 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7777777777777778, "acc_stderr": 0.02962022787479048, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.02962022787479048 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9222797927461139, "acc_stderr": 0.019321805557223137, "acc_norm": 0.9222797927461139, "acc_norm_stderr": 0.019321805557223137 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6641025641025641, "acc_stderr": 0.02394672474156397, "acc_norm": 0.6641025641025641, "acc_norm_stderr": 0.02394672474156397 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.34074074074074073, "acc_stderr": 0.028897748741131143, "acc_norm": 0.34074074074074073, "acc_norm_stderr": 0.028897748741131143 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6554621848739496, "acc_stderr": 0.030868682604121622, "acc_norm": 0.6554621848739496, "acc_norm_stderr": 0.030868682604121622 }, "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": 0.8477064220183487, "acc_stderr": 0.015405084393157074, "acc_norm": 0.8477064220183487, "acc_norm_stderr": 0.015405084393157074 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5231481481481481, "acc_stderr": 0.03406315360711507, "acc_norm": 0.5231481481481481, "acc_norm_stderr": 0.03406315360711507 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.7892156862745098, "acc_stderr": 0.02862654791243742, "acc_norm": 0.7892156862745098, "acc_norm_stderr": 0.02862654791243742 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8059071729957806, "acc_stderr": 0.025744902532290916, "acc_norm": 0.8059071729957806, "acc_norm_stderr": 0.025744902532290916 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.7085201793721974, "acc_stderr": 0.030500283176545847, "acc_norm": 0.7085201793721974, "acc_norm_stderr": 0.030500283176545847 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7480916030534351, "acc_stderr": 0.03807387116306086, "acc_norm": 0.7480916030534351, "acc_norm_stderr": 0.03807387116306086 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7520661157024794, "acc_stderr": 0.03941897526516303, "acc_norm": 0.7520661157024794, "acc_norm_stderr": 0.03941897526516303 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7685185185185185, "acc_stderr": 0.04077494709252627, "acc_norm": 0.7685185185185185, "acc_norm_stderr": 0.04077494709252627 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.754601226993865, "acc_stderr": 0.03380939813943354, "acc_norm": 0.754601226993865, "acc_norm_stderr": 0.03380939813943354 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.44642857142857145, "acc_stderr": 0.04718471485219588, "acc_norm": 0.44642857142857145, "acc_norm_stderr": 0.04718471485219588 }, "harness|hendrycksTest-management|5": { "acc": 0.8058252427184466, "acc_stderr": 0.03916667762822583, "acc_norm": 0.8058252427184466, "acc_norm_stderr": 0.03916667762822583 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8717948717948718, "acc_stderr": 0.021901905115073325, "acc_norm": 0.8717948717948718, "acc_norm_stderr": 0.021901905115073325 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8135376756066411, "acc_stderr": 0.013927751372001512, "acc_norm": 0.8135376756066411, "acc_norm_stderr": 0.013927751372001512 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7225433526011561, "acc_stderr": 0.024105712607754307, "acc_norm": 0.7225433526011561, "acc_norm_stderr": 0.024105712607754307 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.39888268156424583, "acc_stderr": 0.01637696614261008, "acc_norm": 0.39888268156424583, "acc_norm_stderr": 0.01637696614261008 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7320261437908496, "acc_stderr": 0.025360603796242557, "acc_norm": 0.7320261437908496, "acc_norm_stderr": 0.025360603796242557 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7170418006430869, "acc_stderr": 0.02558306248998481, "acc_norm": 0.7170418006430869, "acc_norm_stderr": 0.02558306248998481 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7222222222222222, "acc_stderr": 0.02492200116888633, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.02492200116888633 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4645390070921986, "acc_stderr": 0.029752389657427047, "acc_norm": 0.4645390070921986, "acc_norm_stderr": 0.029752389657427047 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4804432855280313, "acc_stderr": 0.012760464028289299, "acc_norm": 0.4804432855280313, "acc_norm_stderr": 0.012760464028289299 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.7022058823529411, "acc_stderr": 0.027778298701545443, "acc_norm": 0.7022058823529411, "acc_norm_stderr": 0.027778298701545443 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6650326797385621, "acc_stderr": 0.019094228167000318, "acc_norm": 0.6650326797385621, "acc_norm_stderr": 0.019094228167000318 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6636363636363637, "acc_stderr": 0.04525393596302506, "acc_norm": 0.6636363636363637, "acc_norm_stderr": 0.04525393596302506 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7224489795918367, "acc_stderr": 0.028666857790274645, "acc_norm": 0.7224489795918367, "acc_norm_stderr": 0.028666857790274645 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8258706467661692, "acc_stderr": 0.026814951200421603, "acc_norm": 0.8258706467661692, "acc_norm_stderr": 0.026814951200421603 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.88, "acc_stderr": 0.03265986323710906, "acc_norm": 0.88, "acc_norm_stderr": 0.03265986323710906 }, "harness|hendrycksTest-virology|5": { "acc": 0.5301204819277109, "acc_stderr": 0.03885425420866767, "acc_norm": 0.5301204819277109, "acc_norm_stderr": 0.03885425420866767 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8538011695906432, "acc_stderr": 0.027097290118070806, "acc_norm": 0.8538011695906432, "acc_norm_stderr": 0.027097290118070806 }, "harness|truthfulqa:mc|0": { "mc1": 0.3072215422276622, "mc1_stderr": 0.016150201321323016, "mc2": 0.45618408792342546, "mc2_stderr": 0.015076169944832135 }, "harness|winogrande|5": { "acc": 0.7947908445146015, "acc_stderr": 0.01135031570746207 }, "harness|gsm8k|5": { "acc": 0.6254738438210766, "acc_stderr": 0.013331774158491391 } } ``` ## 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] 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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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timpal0l/OpenHermes-2.5-sv
--- language: - sv dataset_info: features: - name: category dtype: string - name: model_name dtype: 'null' - name: idx dtype: 'null' - name: custom_instruction dtype: 'null' - name: topic dtype: 'null' - name: system_prompt dtype: 'null' - name: conversations list: - name: from dtype: string - name: value dtype: string - name: weight dtype: 'null' - name: source dtype: string - name: hash dtype: 'null' - name: avatarUrl dtype: 'null' - name: model dtype: 'null' - name: language dtype: 'null' - name: id dtype: string - name: views dtype: 'null' - name: title dtype: 'null' - name: skip_prompt_formatting dtype: bool - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 76599171 num_examples: 84765 download_size: 46192507 dataset_size: 76599171 configs: - config_name: default data_files: - split: train path: data/train-* license: mit task_categories: - text-generation tags: - instruct datasets: - timpal0l/OpenHermes-2.5-sv - teknium/OpenHermes-2.5 --- # OpenHermes-2.5-sv This is a machine translated instruct dataset from [OpenHermes-2.5](https://huggingface.co/datasets/teknium/OpenHermes-2.5). The [facebook/seamless-m4t-v2-large](https://huggingface.co/facebook/seamless-m4t-v2-large) was used, and some post filtering is done to remove repetitive texts that occurred due to translation errors. # Example data: ```json [ { "from":"human", "value":"Vilket naturfenomen, som orsakas av att ljus reflekteras och bryts genom vattendroppar, resulterar i en färgglad båge på himlen?", "weight":null }, { "from":"gpt", "value":"En regnbåge är ett naturligt fenomen som uppstår när ljus reflekteras och bryts genom vattendroppar i jordens atmosfär. Denna spridning av ljus resulterar i en färgglad båge på himlen, vanligtvis med färgerna rött, orange, gult, grönt, blått, indigo och violett. Regnbågar dyker oftast upp efter regnfall och under soliga intervaller.", "weight":null } ] ```
davanstrien/illustrated_ads_images_labels_only
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': text-only '1': illustrations splits: - name: train num_bytes: 47581375 num_examples: 549 download_size: 47599430 dataset_size: 47581375 size_categories: - n<1K --- # Dataset Card for "illustrated_ads_images_labels_only" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
yejeekang/legal_sum_instruction
--- license: afl-3.0 ---
CyberHarem/sakurai_yumeko_theidolmster
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of sakurai_yumeko (THE iDOLM@STER) This is the dataset of sakurai_yumeko (THE iDOLM@STER), containing 69 images and their tags. The core tags of this character are `long_hair, green_eyes, brown_hair, side_ponytail, breasts`, 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 | 69 | 35.23 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakurai_yumeko_theidolmster/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 69 | 30.48 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakurai_yumeko_theidolmster/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 114 | 50.37 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakurai_yumeko_theidolmster/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 69 | 34.78 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakurai_yumeko_theidolmster/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 114 | 55.82 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakurai_yumeko_theidolmster/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/sakurai_yumeko_theidolmster', 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 | 24 | ![](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, detached_sleeves, bare_shoulders, blush, solo, midriff, star_(symbol), necklace, navel, smile, skirt, striped, clothes_around_waist, open_mouth | | 1 | 8 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | boots, midriff, thighhighs, navel, skirt, 3girls, clothes_around_waist, crop_top, smile, 1girl, 2girls, detached_sleeves, open_mouth, star_(symbol), striped | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | detached_sleeves | bare_shoulders | blush | solo | midriff | star_(symbol) | necklace | navel | smile | skirt | striped | clothes_around_waist | open_mouth | boots | thighhighs | 3girls | crop_top | 2girls | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------------------|:-----------------|:--------|:-------|:----------|:----------------|:-----------|:--------|:--------|:--------|:----------|:-----------------------|:-------------|:--------|:-------------|:---------|:-----------|:---------| | 0 | 24 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | 1 | 8 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | X | X | | | | X | X | | X | X | X | X | X | X | X | X | X | X | X |
wsyar/llmbG11
--- license: apache-2.0 ---
atharvapawar/part5_dataSorted_Diversevul_llama2_dataset
--- license: mit ---
babs/vox-populi-subset
--- dataset_info: features: - name: source_id dtype: string - name: target_id dtype: string - name: source_audio dtype: audio - name: target_audio dtype: audio - name: target_units sequence: int32 splits: - name: train num_bytes: 459597811.0 num_examples: 1000 download_size: 457570458 dataset_size: 459597811.0 configs: - config_name: default data_files: - split: train path: data/train-* --- THis repo contains about 100 rows of random speech to speech vox populi data. can be use for quick testing of code and pipelines
KatoHF/ultrafeedback_binarized
--- dataset_info: features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 493667577 num_examples: 225328 download_size: 184177111 dataset_size: 493667577 configs: - config_name: default data_files: - split: train path: data/train-* ---
Locutusque/hercules-v2.5
--- language: - en license: apache-2.0 size_categories: - 1M<n<10M task_categories: - text-generation - question-answering - conversational dataset_info: features: - name: conversations list: - name: from dtype: string - name: value dtype: string - name: source dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 3257199688.0 num_examples: 1810725 download_size: 1488468818 dataset_size: 3257199688.0 configs: - config_name: default data_files: - split: train path: data/train-* --- ### Dataset Card for Hercules-v2.5 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6437292ecd93f4c9a34b0d47/SGKE0YqD-e2r-ceJGksUX.png) #### Overview **Dataset Name:** Hercules-v2.5 **Version:** 2.5 **Date of Release:** February 9, 2024 **Size:** 1,810,725 **Data Sources:** Hercules-v2.5 is an enriched instruction dataset derived from Hercules-v2.0, aimed at fixing a critical oversight that was not caught and improving reasoning, math, and truth capabilities. The oversight was that the functions were not provided in the function calling examples of the previous dataset, leading to severe hallucinations. The dataset amalgamates contributions from various data sources, with a strong emphasis on Biology, Physics, Medicine, Math, Computer Science, Instruction Following, Function Calling, and Roleplay. The data sources used to construct Hercules-v2.0 include: - cognitivecomputations/dolphin (first 300k examples) - Evol Instruct 70K && 140K - teknium/GPT4-LLM-Cleaned - jondurbin/airoboros-3.2 - AlekseyKorshuk/camel-chatml - CollectiveCognition/chats-data-2023-09-22 - Nebulous/lmsys-chat-1m-smortmodelsonly - glaiveai/glaive-code-assistant-v2 - glaiveai/glaive-code-assistant - glaiveai/glaive-function-calling-v2 - garage-bAInd/Open-Platypus - meta-math/MetaMathQA - teknium/GPTeacher-General-Instruct - GPTeacher roleplay datasets - BI55/MedText - pubmed_qa labeled subset - Unnatural Instructions - M4-ai/LDJnr_combined_inout_format - CollectiveCognition/chats-data-2023-09-27 - CollectiveCognition/chats-data-2023-10-16 This dataset is written with mostly GPT-4, but other models such as Claude-1, Claude-1-instant, Claude-2, Claude-2.1, and GPT-3.5-Turbo can be found in the data. Curation of this dataset was based on findings from hercules-v2.0. Warning: This dataset contains toxic examples. Use at your own risk. #### Description Hercules-v2.5 is designed to serve as a comprehensive and multifaceted dataset tailored for the development and evaluation of advanced machine learning models, particularly those focused on natural language understanding and processing in specialized domains. It includes a variety of formats, such as question-answering pairs, dialogues, function calls, and roleplay scenarios, providing robust training material for models to handle complex instructions and execute function calls. #### Data Format The dataset includes JSON-formatted entries, with a unique structure to incorporate function calling examples. Each entry is composed of a sequence of interactions, each tagged with "from" to indicate the speaker (human, function-call, function-response, or gpt) and "value" to present the content or payload of the interaction. For example: ```json [ { "from": "human", "value": "Hi, I need to convert a temperature from Celsius to Fahrenheit. The temperature is 30 degrees Celsius." }, { "from": "function-call", "value": "{\"name\": \"convert_temperature\", \"arguments\": '{\"temperature\": 30, \"from_unit\": \"Celsius\", \"to_unit\": \"Fahrenheit\"}'}" }, { "from": "function-response", "value": "{\"converted_temperature\": 86}" }, { "from": "gpt", "value": "The converted temperature from 30 degrees Celsius to Fahrenheit is 86 degrees Fahrenheit." } ] ``` #### Usage The Hercules-v2.5 dataset is designed for training and evaluating AI systems in their ability to follow instructions, execute function calls, and interact in roleplay scenarios across various scientific and technical disciplines. Researchers and developers can leverage this dataset for: - Enhancing language models' understanding of complex topics. - Improving the accuracy of function-call executions within conversational agents. - Developing models capable of engaging in educational and informative dialogue. - Benchmarking systems on their ability to follow intricate instructions and provide accurate responses. #### Licensing This dataset is released under the apache-2.0 license. #### Citation Researchers using Hercules-v2.5 in their work should cite the dataset as follows: ``` @misc{sebastian_gabarain_2024, title = {Hercules-v2.0: An Instruction Dataset for Specialized Domains}, author = {Sebastian Gabarain}, publisher = {HuggingFace}, year = {2024}, doi = {10.57967/hf/1744} url = {https://huggingface.co/datasets/Locutusque/hercules-v2.0} } ``` #### Acknowledgements Hercules-v2.5 was made possible thanks to the contributions from various datasets and the community's efforts in compiling and refining data to create a rich and diverse instruction set. Special thanks go to the creator of OpenHermes-2.5 and all the data sources listed above. #### Version History v2.5: Current version with fixed function-calling oversight. v2.0: Enhanced diversity and scope. v1.0: Initial release.
doushabao4766/resume_zh_ner
--- dataset_info: features: - name: id dtype: int64 - name: tokens sequence: string - name: ner_tags sequence: int64 splits: - name: train num_bytes: 1893971 num_examples: 3821 - name: test num_bytes: 231104 num_examples: 477 - name: validation num_bytes: 212262 num_examples: 463 download_size: 0 dataset_size: 2337337 --- # Dataset Card for "resume_zh_ner" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
distilled-from-one-sec-cv12/chunk_186
--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 646724376 num_examples: 126018 download_size: 653514673 dataset_size: 646724376 --- # Dataset Card for "chunk_186" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
drmworld/uird_t5-small_v.0.1
--- dataset_info: features: - name: character struct: - name: age dtype: int64 - name: bio dtype: string - name: code dtype: string - name: country_flag dtype: string - name: created_at dtype: string - name: deleted_at dtype: 'null' - name: description dtype: string - name: display_name dtype: string - name: eleven_voice_id dtype: string - name: eleven_voice_settings struct: - name: similarity_boost dtype: float64 - name: stability dtype: float64 - name: style dtype: int64 - name: use_speaker_boost dtype: bool - name: height dtype: string - name: hobbies sequence: string - name: id dtype: string - name: image_cost dtype: int64 - name: is_ready_chat_content dtype: bool - name: is_ready_llm dtype: bool - name: is_ready_profile_content dtype: bool - name: is_ready_profile_data dtype: bool - name: level1_name dtype: string - name: level1_value dtype: int64 - name: level2_name dtype: string - name: level2_value dtype: int64 - name: level3_name dtype: string - name: level3_value dtype: int64 - name: llm_mw_url dtype: 'null' - name: location dtype: string - name: metadata struct: - name: age dtype: string - name: birthday dtype: string - name: body type dtype: string - name: description dtype: string - name: education dtype: string - name: example 2 / notes dtype: string - name: eye color dtype: string - name: family dtype: string - name: favorite destinations dtype: string - name: favorite food dtype: string - name: favorite movies / tv dtype: string - name: favorite music / artist dtype: string - name: favorite sports / team dtype: string - name: first_name dtype: string - name: gender dtype: string - name: hair color dtype: string - name: height dtype: string - name: hobbies dtype: string - name: ig / twitter bio dtype: string - name: location dtype: string - name: name dtype: string - name: nationality dtype: string - name: occupation dtype: string - name: personality dtype: string - name: pets dtype: string - name: pronoun dtype: string - name: pronoun_heshe dtype: string - name: turn ons dtype: string - name: website bio dtype: string - name: website headline dtype: string - name: zodiac sign dtype: string - name: nature dtype: string - name: ordering dtype: int64 - name: preferences sequence: string - name: updated_at dtype: string - name: welcome_message dtype: string - name: welcome_message_reply_suggestion dtype: string - name: user struct: - name: gender dtype: string - name: hobbies sequence: string - name: turn_ons sequence: string - name: history list: - name: id dtype: int64 - name: llm_id dtype: int64 - name: normal_request sequence: string - name: normal_tag dtype: string - name: picture_camera dtype: 'null' - name: picture_category dtype: string - name: picture_clothes dtype: string - name: picture_location dtype: string - name: picture_request sequence: string - name: role dtype: string splits: - name: train num_bytes: 26654 num_examples: 1 download_size: 68244 dataset_size: 26654 configs: - config_name: default data_files: - split: train path: data/train-* ---
mtkinit/mtkinit_TCB_sentiment_dataset
--- pretty_name: mtkinit/TCB-sentiment-dataset --- # mtkinit/TCB-sentiment-dataset Created from AIOD platform
DK9/UV-ControlNet
--- license: apache-2.0 ---
khalidalt/SANAD
--- license: cc-by-4.0 --- # Dataset Card for SANAD ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:https://data.mendeley.com/datasets/57zpx667y9/2** ### Dataset Summary SANAD Dataset is a large collection of Arabic news articles that can be used in different Arabic NLP tasks such as Text Classification and Word Embedding. The articles were collected using Python scripts written specifically for three popular news websites: AlKhaleej, AlArabiya and Akhbarona. All datasets have seven categories [Culture, Finance, Medical, Politics, Religion, Sports and Tech], except AlArabiya which doesn’t have [Religion]. SANAD contains a total number of 190k+ articles. ### 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 license: cc-by-4.0 ### Citation Information ``` @article{einea2019sanad, title={Sanad: Single-label arabic news articles dataset for automatic text categorization}, author={Einea, Omar and Elnagar, Ashraf and Al Debsi, Ridhwan}, journal={Data in brief}, volume={25}, pages={104076}, year={2019}, publisher={Elsevier} } ``` ### Contributions
Omerturktt/omerturkai
--- license: openrail ---
open-llm-leaderboard/details_teilomillet__MiniMerlin-3b-v0.1
--- pretty_name: Evaluation run of teilomillet/MiniMerlin-3b-v0.1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [teilomillet/MiniMerlin-3b-v0.1](https://huggingface.co/teilomillet/MiniMerlin-3b-v0.1)\ \ 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_teilomillet__MiniMerlin-3b-v0.1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-13T12:30:09.463717](https://huggingface.co/datasets/open-llm-leaderboard/details_teilomillet__MiniMerlin-3b-v0.1/blob/main/results_2023-12-13T12-30-09.463717.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\": 0.42829802423091123,\n\ \ \"acc_stderr\": 0.034419009383078604,\n \"acc_norm\": 0.4345596062931712,\n\ \ \"acc_norm_stderr\": 0.035301959046270974,\n \"mc1\": 0.3023255813953488,\n\ \ \"mc1_stderr\": 0.016077509266133022,\n \"mc2\": 0.49647374974901654,\n\ \ \"mc2_stderr\": 0.015915065186614973\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.38139931740614336,\n \"acc_stderr\": 0.014194389086685261,\n\ \ \"acc_norm\": 0.4069965870307167,\n \"acc_norm_stderr\": 0.014356399418009131\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.4343756223859789,\n\ \ \"acc_stderr\": 0.004946617138983514,\n \"acc_norm\": 0.5406293567018522,\n\ \ \"acc_norm_stderr\": 0.004973280417705513\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.43703703703703706,\n\ \ \"acc_stderr\": 0.042849586397533994,\n \"acc_norm\": 0.43703703703703706,\n\ \ \"acc_norm_stderr\": 0.042849586397533994\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.4473684210526316,\n \"acc_stderr\": 0.040463368839782486,\n\ \ \"acc_norm\": 0.4473684210526316,\n \"acc_norm_stderr\": 0.040463368839782486\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.38,\n\ \ \"acc_stderr\": 0.048783173121456316,\n \"acc_norm\": 0.38,\n \ \ \"acc_norm_stderr\": 0.048783173121456316\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.47924528301886793,\n \"acc_stderr\": 0.030746349975723463,\n\ \ \"acc_norm\": 0.47924528301886793,\n \"acc_norm_stderr\": 0.030746349975723463\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.4722222222222222,\n\ \ \"acc_stderr\": 0.04174752578923185,\n \"acc_norm\": 0.4722222222222222,\n\ \ \"acc_norm_stderr\": 0.04174752578923185\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.047258156262526045\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\ acc\": 0.45,\n \"acc_stderr\": 0.049999999999999996,\n \"acc_norm\"\ : 0.45,\n \"acc_norm_stderr\": 0.049999999999999996\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542126,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542126\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.3872832369942196,\n\ \ \"acc_stderr\": 0.037143259063020656,\n \"acc_norm\": 0.3872832369942196,\n\ \ \"acc_norm_stderr\": 0.037143259063020656\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.2549019607843137,\n \"acc_stderr\": 0.04336432707993177,\n\ \ \"acc_norm\": 0.2549019607843137,\n \"acc_norm_stderr\": 0.04336432707993177\n\ \ },\n \"harness|hendrycksTest-computer_security|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-conceptual_physics|5\"\ : {\n \"acc\": 0.3276595744680851,\n \"acc_stderr\": 0.030683020843231,\n\ \ \"acc_norm\": 0.3276595744680851,\n \"acc_norm_stderr\": 0.030683020843231\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2719298245614035,\n\ \ \"acc_stderr\": 0.04185774424022056,\n \"acc_norm\": 0.2719298245614035,\n\ \ \"acc_norm_stderr\": 0.04185774424022056\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.43448275862068964,\n \"acc_stderr\": 0.04130740879555497,\n\ \ \"acc_norm\": 0.43448275862068964,\n \"acc_norm_stderr\": 0.04130740879555497\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.2566137566137566,\n \"acc_stderr\": 0.022494510767503154,\n \"\ acc_norm\": 0.2566137566137566,\n \"acc_norm_stderr\": 0.022494510767503154\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.25396825396825395,\n\ \ \"acc_stderr\": 0.03893259610604673,\n \"acc_norm\": 0.25396825396825395,\n\ \ \"acc_norm_stderr\": 0.03893259610604673\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.5161290322580645,\n\ \ \"acc_stderr\": 0.028429203176724555,\n \"acc_norm\": 0.5161290322580645,\n\ \ \"acc_norm_stderr\": 0.028429203176724555\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.35467980295566504,\n \"acc_stderr\": 0.0336612448905145,\n\ \ \"acc_norm\": 0.35467980295566504,\n \"acc_norm_stderr\": 0.0336612448905145\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|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_european_history|5\"\ : {\n \"acc\": 0.5212121212121212,\n \"acc_stderr\": 0.03900828913737302,\n\ \ \"acc_norm\": 0.5212121212121212,\n \"acc_norm_stderr\": 0.03900828913737302\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.5252525252525253,\n \"acc_stderr\": 0.03557806245087314,\n \"\ acc_norm\": 0.5252525252525253,\n \"acc_norm_stderr\": 0.03557806245087314\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.5647668393782384,\n \"acc_stderr\": 0.035780381650085846,\n\ \ \"acc_norm\": 0.5647668393782384,\n \"acc_norm_stderr\": 0.035780381650085846\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.382051282051282,\n \"acc_stderr\": 0.024635549163908227,\n \ \ \"acc_norm\": 0.382051282051282,\n \"acc_norm_stderr\": 0.024635549163908227\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.22962962962962963,\n \"acc_stderr\": 0.025644108639267613,\n \ \ \"acc_norm\": 0.22962962962962963,\n \"acc_norm_stderr\": 0.025644108639267613\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.35294117647058826,\n \"acc_stderr\": 0.031041941304059274,\n\ \ \"acc_norm\": 0.35294117647058826,\n \"acc_norm_stderr\": 0.031041941304059274\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\"\ : 0.5614678899082569,\n \"acc_stderr\": 0.021274713073954572,\n \"\ acc_norm\": 0.5614678899082569,\n \"acc_norm_stderr\": 0.021274713073954572\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.25,\n \"acc_stderr\": 0.029531221160930918,\n \"acc_norm\": 0.25,\n\ \ \"acc_norm_stderr\": 0.029531221160930918\n },\n \"harness|hendrycksTest-high_school_us_history|5\"\ : {\n \"acc\": 0.5441176470588235,\n \"acc_stderr\": 0.03495624522015475,\n\ \ \"acc_norm\": 0.5441176470588235,\n \"acc_norm_stderr\": 0.03495624522015475\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.5907172995780591,\n \"acc_stderr\": 0.032007041833595914,\n \ \ \"acc_norm\": 0.5907172995780591,\n \"acc_norm_stderr\": 0.032007041833595914\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.4663677130044843,\n\ \ \"acc_stderr\": 0.033481800170603065,\n \"acc_norm\": 0.4663677130044843,\n\ \ \"acc_norm_stderr\": 0.033481800170603065\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.5267175572519084,\n \"acc_stderr\": 0.04379024936553894,\n\ \ \"acc_norm\": 0.5267175572519084,\n \"acc_norm_stderr\": 0.04379024936553894\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.5867768595041323,\n \"acc_stderr\": 0.04495087843548408,\n \"\ acc_norm\": 0.5867768595041323,\n \"acc_norm_stderr\": 0.04495087843548408\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.5,\n\ \ \"acc_stderr\": 0.04833682445228318,\n \"acc_norm\": 0.5,\n \ \ \"acc_norm_stderr\": 0.04833682445228318\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.5030674846625767,\n \"acc_stderr\": 0.03928297078179663,\n\ \ \"acc_norm\": 0.5030674846625767,\n \"acc_norm_stderr\": 0.03928297078179663\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.3482142857142857,\n\ \ \"acc_stderr\": 0.04521829902833586,\n \"acc_norm\": 0.3482142857142857,\n\ \ \"acc_norm_stderr\": 0.04521829902833586\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.5825242718446602,\n \"acc_stderr\": 0.048828405482122375,\n\ \ \"acc_norm\": 0.5825242718446602,\n \"acc_norm_stderr\": 0.048828405482122375\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.6709401709401709,\n\ \ \"acc_stderr\": 0.03078232157768817,\n \"acc_norm\": 0.6709401709401709,\n\ \ \"acc_norm_stderr\": 0.03078232157768817\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.49936143039591313,\n\ \ \"acc_stderr\": 0.01787994891443168,\n \"acc_norm\": 0.49936143039591313,\n\ \ \"acc_norm_stderr\": 0.01787994891443168\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.4653179190751445,\n \"acc_stderr\": 0.026854257928258893,\n\ \ \"acc_norm\": 0.4653179190751445,\n \"acc_norm_stderr\": 0.026854257928258893\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.24692737430167597,\n\ \ \"acc_stderr\": 0.014422292204808862,\n \"acc_norm\": 0.24692737430167597,\n\ \ \"acc_norm_stderr\": 0.014422292204808862\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.5163398692810458,\n \"acc_stderr\": 0.028614624752805434,\n\ \ \"acc_norm\": 0.5163398692810458,\n \"acc_norm_stderr\": 0.028614624752805434\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.4855305466237942,\n\ \ \"acc_stderr\": 0.02838619808417768,\n \"acc_norm\": 0.4855305466237942,\n\ \ \"acc_norm_stderr\": 0.02838619808417768\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.45987654320987653,\n \"acc_stderr\": 0.027731022753539274,\n\ \ \"acc_norm\": 0.45987654320987653,\n \"acc_norm_stderr\": 0.027731022753539274\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.3475177304964539,\n \"acc_stderr\": 0.028406627809590947,\n \ \ \"acc_norm\": 0.3475177304964539,\n \"acc_norm_stderr\": 0.028406627809590947\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3533246414602347,\n\ \ \"acc_stderr\": 0.012208408211082428,\n \"acc_norm\": 0.3533246414602347,\n\ \ \"acc_norm_stderr\": 0.012208408211082428\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.2757352941176471,\n \"acc_stderr\": 0.02714627193662517,\n\ \ \"acc_norm\": 0.2757352941176471,\n \"acc_norm_stderr\": 0.02714627193662517\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.4133986928104575,\n \"acc_stderr\": 0.01992211568278667,\n \ \ \"acc_norm\": 0.4133986928104575,\n \"acc_norm_stderr\": 0.01992211568278667\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.5181818181818182,\n\ \ \"acc_stderr\": 0.04785964010794916,\n \"acc_norm\": 0.5181818181818182,\n\ \ \"acc_norm_stderr\": 0.04785964010794916\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.5346938775510204,\n \"acc_stderr\": 0.03193207024425314,\n\ \ \"acc_norm\": 0.5346938775510204,\n \"acc_norm_stderr\": 0.03193207024425314\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.5771144278606966,\n\ \ \"acc_stderr\": 0.034932317774212816,\n \"acc_norm\": 0.5771144278606966,\n\ \ \"acc_norm_stderr\": 0.034932317774212816\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.61,\n \"acc_stderr\": 0.04902071300001974,\n \ \ \"acc_norm\": 0.61,\n \"acc_norm_stderr\": 0.04902071300001974\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.43373493975903615,\n\ \ \"acc_stderr\": 0.03858158940685516,\n \"acc_norm\": 0.43373493975903615,\n\ \ \"acc_norm_stderr\": 0.03858158940685516\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.5029239766081871,\n \"acc_stderr\": 0.03834759370936839,\n\ \ \"acc_norm\": 0.5029239766081871,\n \"acc_norm_stderr\": 0.03834759370936839\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.3023255813953488,\n\ \ \"mc1_stderr\": 0.016077509266133022,\n \"mc2\": 0.49647374974901654,\n\ \ \"mc2_stderr\": 0.015915065186614973\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.6053670086819258,\n \"acc_stderr\": 0.013736915172371888\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.013646702047005308,\n \ \ \"acc_stderr\": 0.003195747075480817\n }\n}\n```" repo_url: https://huggingface.co/teilomillet/MiniMerlin-3b-v0.1 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: 2023_12_13T12_30_09.463717 path: - '**/details_harness|arc:challenge|25_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-13T12-30-09.463717.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|gsm8k|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hellaswag|10_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-13T12-30-09.463717.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-management|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-13T12-30-09.463717.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|truthfulqa:mc|0_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-13T12-30-09.463717.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_13T12_30_09.463717 path: - '**/details_harness|winogrande|5_2023-12-13T12-30-09.463717.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-13T12-30-09.463717.parquet' - config_name: results data_files: - split: 2023_12_13T12_30_09.463717 path: - results_2023-12-13T12-30-09.463717.parquet - split: latest path: - results_2023-12-13T12-30-09.463717.parquet --- # Dataset Card for Evaluation run of teilomillet/MiniMerlin-3b-v0.1 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [teilomillet/MiniMerlin-3b-v0.1](https://huggingface.co/teilomillet/MiniMerlin-3b-v0.1) 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_teilomillet__MiniMerlin-3b-v0.1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-13T12:30:09.463717](https://huggingface.co/datasets/open-llm-leaderboard/details_teilomillet__MiniMerlin-3b-v0.1/blob/main/results_2023-12-13T12-30-09.463717.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": 0.42829802423091123, "acc_stderr": 0.034419009383078604, "acc_norm": 0.4345596062931712, "acc_norm_stderr": 0.035301959046270974, "mc1": 0.3023255813953488, "mc1_stderr": 0.016077509266133022, "mc2": 0.49647374974901654, "mc2_stderr": 0.015915065186614973 }, "harness|arc:challenge|25": { "acc": 0.38139931740614336, "acc_stderr": 0.014194389086685261, "acc_norm": 0.4069965870307167, "acc_norm_stderr": 0.014356399418009131 }, "harness|hellaswag|10": { "acc": 0.4343756223859789, "acc_stderr": 0.004946617138983514, "acc_norm": 0.5406293567018522, "acc_norm_stderr": 0.004973280417705513 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.43703703703703706, "acc_stderr": 0.042849586397533994, "acc_norm": 0.43703703703703706, "acc_norm_stderr": 0.042849586397533994 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.4473684210526316, "acc_stderr": 0.040463368839782486, "acc_norm": 0.4473684210526316, "acc_norm_stderr": 0.040463368839782486 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.47924528301886793, "acc_stderr": 0.030746349975723463, "acc_norm": 0.47924528301886793, "acc_norm_stderr": 0.030746349975723463 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4722222222222222, "acc_stderr": 0.04174752578923185, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.04174752578923185 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.45, "acc_stderr": 0.049999999999999996, "acc_norm": 0.45, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.28, "acc_stderr": 0.04512608598542126, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542126 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3872832369942196, "acc_stderr": 0.037143259063020656, "acc_norm": 0.3872832369942196, "acc_norm_stderr": 0.037143259063020656 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.2549019607843137, "acc_stderr": 0.04336432707993177, "acc_norm": 0.2549019607843137, "acc_norm_stderr": 0.04336432707993177 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3276595744680851, "acc_stderr": 0.030683020843231, "acc_norm": 0.3276595744680851, "acc_norm_stderr": 0.030683020843231 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2719298245614035, "acc_stderr": 0.04185774424022056, "acc_norm": 0.2719298245614035, "acc_norm_stderr": 0.04185774424022056 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.43448275862068964, "acc_stderr": 0.04130740879555497, "acc_norm": 0.43448275862068964, "acc_norm_stderr": 0.04130740879555497 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2566137566137566, "acc_stderr": 0.022494510767503154, "acc_norm": 0.2566137566137566, "acc_norm_stderr": 0.022494510767503154 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.25396825396825395, "acc_stderr": 0.03893259610604673, "acc_norm": 0.25396825396825395, "acc_norm_stderr": 0.03893259610604673 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5161290322580645, "acc_stderr": 0.028429203176724555, "acc_norm": 0.5161290322580645, "acc_norm_stderr": 0.028429203176724555 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.35467980295566504, "acc_stderr": 0.0336612448905145, "acc_norm": 0.35467980295566504, "acc_norm_stderr": 0.0336612448905145 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.5212121212121212, "acc_stderr": 0.03900828913737302, "acc_norm": 0.5212121212121212, "acc_norm_stderr": 0.03900828913737302 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5252525252525253, "acc_stderr": 0.03557806245087314, "acc_norm": 0.5252525252525253, "acc_norm_stderr": 0.03557806245087314 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.5647668393782384, "acc_stderr": 0.035780381650085846, "acc_norm": 0.5647668393782384, "acc_norm_stderr": 0.035780381650085846 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.382051282051282, "acc_stderr": 0.024635549163908227, "acc_norm": 0.382051282051282, "acc_norm_stderr": 0.024635549163908227 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.22962962962962963, "acc_stderr": 0.025644108639267613, "acc_norm": 0.22962962962962963, "acc_norm_stderr": 0.025644108639267613 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.35294117647058826, "acc_stderr": 0.031041941304059274, "acc_norm": 0.35294117647058826, "acc_norm_stderr": 0.031041941304059274 }, "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": 0.5614678899082569, "acc_stderr": 0.021274713073954572, "acc_norm": 0.5614678899082569, "acc_norm_stderr": 0.021274713073954572 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.25, "acc_stderr": 0.029531221160930918, "acc_norm": 0.25, "acc_norm_stderr": 0.029531221160930918 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.5441176470588235, "acc_stderr": 0.03495624522015475, "acc_norm": 0.5441176470588235, "acc_norm_stderr": 0.03495624522015475 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.5907172995780591, "acc_stderr": 0.032007041833595914, "acc_norm": 0.5907172995780591, "acc_norm_stderr": 0.032007041833595914 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.4663677130044843, "acc_stderr": 0.033481800170603065, "acc_norm": 0.4663677130044843, "acc_norm_stderr": 0.033481800170603065 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.5267175572519084, "acc_stderr": 0.04379024936553894, "acc_norm": 0.5267175572519084, "acc_norm_stderr": 0.04379024936553894 }, "harness|hendrycksTest-international_law|5": { "acc": 0.5867768595041323, "acc_stderr": 0.04495087843548408, "acc_norm": 0.5867768595041323, "acc_norm_stderr": 0.04495087843548408 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.5, "acc_stderr": 0.04833682445228318, "acc_norm": 0.5, "acc_norm_stderr": 0.04833682445228318 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.5030674846625767, "acc_stderr": 0.03928297078179663, "acc_norm": 0.5030674846625767, "acc_norm_stderr": 0.03928297078179663 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.3482142857142857, "acc_stderr": 0.04521829902833586, "acc_norm": 0.3482142857142857, "acc_norm_stderr": 0.04521829902833586 }, "harness|hendrycksTest-management|5": { "acc": 0.5825242718446602, "acc_stderr": 0.048828405482122375, "acc_norm": 0.5825242718446602, "acc_norm_stderr": 0.048828405482122375 }, "harness|hendrycksTest-marketing|5": { "acc": 0.6709401709401709, "acc_stderr": 0.03078232157768817, "acc_norm": 0.6709401709401709, "acc_norm_stderr": 0.03078232157768817 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.49936143039591313, "acc_stderr": 0.01787994891443168, "acc_norm": 0.49936143039591313, "acc_norm_stderr": 0.01787994891443168 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.4653179190751445, "acc_stderr": 0.026854257928258893, "acc_norm": 0.4653179190751445, "acc_norm_stderr": 0.026854257928258893 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.24692737430167597, "acc_stderr": 0.014422292204808862, "acc_norm": 0.24692737430167597, "acc_norm_stderr": 0.014422292204808862 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.5163398692810458, "acc_stderr": 0.028614624752805434, "acc_norm": 0.5163398692810458, "acc_norm_stderr": 0.028614624752805434 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.4855305466237942, "acc_stderr": 0.02838619808417768, "acc_norm": 0.4855305466237942, "acc_norm_stderr": 0.02838619808417768 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.45987654320987653, "acc_stderr": 0.027731022753539274, "acc_norm": 0.45987654320987653, "acc_norm_stderr": 0.027731022753539274 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.3475177304964539, "acc_stderr": 0.028406627809590947, "acc_norm": 0.3475177304964539, "acc_norm_stderr": 0.028406627809590947 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.3533246414602347, "acc_stderr": 0.012208408211082428, "acc_norm": 0.3533246414602347, "acc_norm_stderr": 0.012208408211082428 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.2757352941176471, "acc_stderr": 0.02714627193662517, "acc_norm": 0.2757352941176471, "acc_norm_stderr": 0.02714627193662517 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.4133986928104575, "acc_stderr": 0.01992211568278667, "acc_norm": 0.4133986928104575, "acc_norm_stderr": 0.01992211568278667 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.5181818181818182, "acc_stderr": 0.04785964010794916, "acc_norm": 0.5181818181818182, "acc_norm_stderr": 0.04785964010794916 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.5346938775510204, "acc_stderr": 0.03193207024425314, "acc_norm": 0.5346938775510204, "acc_norm_stderr": 0.03193207024425314 }, "harness|hendrycksTest-sociology|5": { "acc": 0.5771144278606966, "acc_stderr": 0.034932317774212816, "acc_norm": 0.5771144278606966, "acc_norm_stderr": 0.034932317774212816 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.61, "acc_stderr": 0.04902071300001974, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001974 }, "harness|hendrycksTest-virology|5": { "acc": 0.43373493975903615, "acc_stderr": 0.03858158940685516, "acc_norm": 0.43373493975903615, "acc_norm_stderr": 0.03858158940685516 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.5029239766081871, "acc_stderr": 0.03834759370936839, "acc_norm": 0.5029239766081871, "acc_norm_stderr": 0.03834759370936839 }, "harness|truthfulqa:mc|0": { "mc1": 0.3023255813953488, "mc1_stderr": 0.016077509266133022, "mc2": 0.49647374974901654, "mc2_stderr": 0.015915065186614973 }, "harness|winogrande|5": { "acc": 0.6053670086819258, "acc_stderr": 0.013736915172371888 }, "harness|gsm8k|5": { "acc": 0.013646702047005308, "acc_stderr": 0.003195747075480817 } } ``` ## 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]
elliotthwangmsa/Evol-Instruct-Chinese-GPT4-3k
--- dataset_info: features: - name: output dtype: string - name: instruction dtype: string splits: - name: train num_bytes: 4936507.757142857 num_examples: 3000 download_size: 3074697 dataset_size: 4936507.757142857 configs: - config_name: default data_files: - split: train path: data/train-* ---
jxu124/llava_instruct_150k
--- dataset_info: features: - name: global_image_id dtype: string - name: image_path dtype: string - name: dialog sequence: sequence: string - name: anns_id dtype: string splits: - name: train num_bytes: 187730970 num_examples: 157712 download_size: 95089013 dataset_size: 187730970 --- # Dataset Card for "llava_instruct_150k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
loubnabnl/gpt4-1k-annotations
--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: completion dtype: string - name: eval_prompt_header dtype: string - name: generation_config struct: - name: do_sample dtype: bool - name: temperature dtype: float64 - name: top_p dtype: float64 - name: metadata struct: - name: timestamp dtype: string - name: prompt dtype: string - name: review_model dtype: string - name: score dtype: float64 - name: code_file dtype: string - name: size dtype: int64 splits: - name: train num_bytes: 7384714 num_examples: 1000 download_size: 2350749 dataset_size: 7384714 --- # Dataset Card for "gpt4-1k-annotations" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
DZN222/lucas
--- license: openrail ---
TristanPermentier/some_chives_ones
--- dataset_info: features: - name: pixel_values dtype: image - name: label dtype: image splits: - name: train num_bytes: 21662024.0 num_examples: 29 download_size: 21484795 dataset_size: 21662024.0 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "some_chives_ones" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
heliosprime/twitter_dataset_1712986344
--- 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: 8285 num_examples: 18 download_size: 8029 dataset_size: 8285 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "twitter_dataset_1712986344" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
AI-C/rvc-models
--- title: Genshin Impact RVC Models (combined) emoji: 🎤 colorFrom: purple colorTo: red sdk: gradio sdk_version: 3.36.1 app_file: app.py pinned: false license: mit --- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
sazirarrwth99/repo_A
--- dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: lex dtype: string - name: category dtype: string - name: size dtype: int64 - name: eid dtype: int64 - name: original_triple_sets dtype: string - name: modified_triple_sets dtype: string - name: shape dtype: string - name: shape_type dtype: string - name: metadata dtype: string - name: test_category dtype: string - name: dbpedia_links dtype: string - name: links dtype: string splits: - name: train num_bytes: 2978451 num_examples: 3293 download_size: 1057306 dataset_size: 2978451 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "repo_A" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
OUTEIRAL2/VOZIA3
--- license: openrail ---
ayeshgk/java_bug_ctx_fix_small_4
--- dataset_info: features: - name: id dtype: int64 - name: bug_ctx dtype: string - name: fixed dtype: string splits: - name: train num_bytes: 59106 num_examples: 120 - name: validation num_bytes: 16505 num_examples: 36 - name: test num_bytes: 2022 num_examples: 4 download_size: 25058 dataset_size: 77633 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
open-llm-leaderboard/details_LeoLM__leo-hessianai-7b
--- pretty_name: Evaluation run of LeoLM/leo-hessianai-7b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [LeoLM/leo-hessianai-7b](https://huggingface.co/LeoLM/leo-hessianai-7b) on the\ \ [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 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 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_LeoLM__leo-hessianai-7b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-25T10:03:23.884304](https://huggingface.co/datasets/open-llm-leaderboard/details_LeoLM__leo-hessianai-7b/blob/main/results_2023-10-25T10-03-23.884304.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\": 0.0009437919463087249,\n\ \ \"em_stderr\": 0.0003144653119413205,\n \"f1\": 0.056075922818791854,\n\ \ \"f1_stderr\": 0.0013232326016856207,\n \"acc\": 0.38874610827245293,\n\ \ \"acc_stderr\": 0.009469282540407879\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.0009437919463087249,\n \"em_stderr\": 0.0003144653119413205,\n\ \ \"f1\": 0.056075922818791854,\n \"f1_stderr\": 0.0013232326016856207\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.056103108415466264,\n \ \ \"acc_stderr\": 0.006338668431321877\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7213891081294396,\n \"acc_stderr\": 0.01259989664949388\n\ \ }\n}\n```" repo_url: https://huggingface.co/LeoLM/leo-hessianai-7b leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|arc:challenge|25_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-10-08T17-16-14.181420.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_25T10_03_23.884304 path: - '**/details_harness|drop|3_2023-10-25T10-03-23.884304.parquet' - split: latest path: - '**/details_harness|drop|3_2023-10-25T10-03-23.884304.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_25T10_03_23.884304 path: - '**/details_harness|gsm8k|5_2023-10-25T10-03-23.884304.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-10-25T10-03-23.884304.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hellaswag|10_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-management|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-management|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-10-08T17-16-14.181420.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-international_law|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-management|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-marketing|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-sociology|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-virology|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-10-08T17-16-14.181420.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_08T17_16_14.181420 path: - '**/details_harness|truthfulqa:mc|0_2023-10-08T17-16-14.181420.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-10-08T17-16-14.181420.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_25T10_03_23.884304 path: - '**/details_harness|winogrande|5_2023-10-25T10-03-23.884304.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-10-25T10-03-23.884304.parquet' - config_name: results data_files: - split: 2023_10_08T17_16_14.181420 path: - results_2023-10-08T17-16-14.181420.parquet - split: 2023_10_25T10_03_23.884304 path: - results_2023-10-25T10-03-23.884304.parquet - split: latest path: - results_2023-10-25T10-03-23.884304.parquet --- # Dataset Card for Evaluation run of LeoLM/leo-hessianai-7b ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/LeoLM/leo-hessianai-7b - **Paper:** - **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - **Point of Contact:** clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [LeoLM/leo-hessianai-7b](https://huggingface.co/LeoLM/leo-hessianai-7b) 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 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 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_LeoLM__leo-hessianai-7b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-25T10:03:23.884304](https://huggingface.co/datasets/open-llm-leaderboard/details_LeoLM__leo-hessianai-7b/blob/main/results_2023-10-25T10-03-23.884304.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": 0.0009437919463087249, "em_stderr": 0.0003144653119413205, "f1": 0.056075922818791854, "f1_stderr": 0.0013232326016856207, "acc": 0.38874610827245293, "acc_stderr": 0.009469282540407879 }, "harness|drop|3": { "em": 0.0009437919463087249, "em_stderr": 0.0003144653119413205, "f1": 0.056075922818791854, "f1_stderr": 0.0013232326016856207 }, "harness|gsm8k|5": { "acc": 0.056103108415466264, "acc_stderr": 0.006338668431321877 }, "harness|winogrande|5": { "acc": 0.7213891081294396, "acc_stderr": 0.01259989664949388 } } ``` ### 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]
liuyanchen1015/MULTI_VALUE_wnli_who_at
--- 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: dev num_bytes: 1153 num_examples: 5 - name: test num_bytes: 4996 num_examples: 14 - name: train num_bytes: 6964 num_examples: 24 download_size: 14664 dataset_size: 13113 --- # Dataset Card for "MULTI_VALUE_wnli_who_at" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_PulsarAI__Chat-AYB-Nova-13B
--- pretty_name: Evaluation run of PulsarAI/Chat-AYB-Nova-13B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [PulsarAI/Chat-AYB-Nova-13B](https://huggingface.co/PulsarAI/Chat-AYB-Nova-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 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 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_PulsarAI__Chat-AYB-Nova-13B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-27T20:18:17.450635](https://huggingface.co/datasets/open-llm-leaderboard/details_PulsarAI__Chat-AYB-Nova-13B/blob/main/results_2023-10-27T20-18-17.450635.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\": 0.0041946308724832215,\n\ \ \"em_stderr\": 0.0006618716168266419,\n \"f1\": 0.0802946728187919,\n\ \ \"f1_stderr\": 0.0016873252068220475,\n \"acc\": 0.44971346473405205,\n\ \ \"acc_stderr\": 0.010392725523775513\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.0041946308724832215,\n \"em_stderr\": 0.0006618716168266419,\n\ \ \"f1\": 0.0802946728187919,\n \"f1_stderr\": 0.0016873252068220475\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.12357846853677028,\n \ \ \"acc_stderr\": 0.009065050306776921\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7758484609313339,\n \"acc_stderr\": 0.011720400740774104\n\ \ }\n}\n```" repo_url: https://huggingface.co/PulsarAI/Chat-AYB-Nova-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_10_08T14_44_32.660445 path: - '**/details_harness|arc:challenge|25_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-10-08T14-44-32.660445.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_27T20_18_17.450635 path: - '**/details_harness|drop|3_2023-10-27T20-18-17.450635.parquet' - split: latest path: - '**/details_harness|drop|3_2023-10-27T20-18-17.450635.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_27T20_18_17.450635 path: - '**/details_harness|gsm8k|5_2023-10-27T20-18-17.450635.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-10-27T20-18-17.450635.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hellaswag|10_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-management|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-management|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-10-08T14-44-32.660445.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-international_law|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-management|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-marketing|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-sociology|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-virology|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-10-08T14-44-32.660445.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_08T14_44_32.660445 path: - '**/details_harness|truthfulqa:mc|0_2023-10-08T14-44-32.660445.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-10-08T14-44-32.660445.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_27T20_18_17.450635 path: - '**/details_harness|winogrande|5_2023-10-27T20-18-17.450635.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-10-27T20-18-17.450635.parquet' - config_name: results data_files: - split: 2023_10_08T14_44_32.660445 path: - results_2023-10-08T14-44-32.660445.parquet - split: 2023_10_27T20_18_17.450635 path: - results_2023-10-27T20-18-17.450635.parquet - split: latest path: - results_2023-10-27T20-18-17.450635.parquet --- # Dataset Card for Evaluation run of PulsarAI/Chat-AYB-Nova-13B ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/PulsarAI/Chat-AYB-Nova-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 [PulsarAI/Chat-AYB-Nova-13B](https://huggingface.co/PulsarAI/Chat-AYB-Nova-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 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 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_PulsarAI__Chat-AYB-Nova-13B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-27T20:18:17.450635](https://huggingface.co/datasets/open-llm-leaderboard/details_PulsarAI__Chat-AYB-Nova-13B/blob/main/results_2023-10-27T20-18-17.450635.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": 0.0041946308724832215, "em_stderr": 0.0006618716168266419, "f1": 0.0802946728187919, "f1_stderr": 0.0016873252068220475, "acc": 0.44971346473405205, "acc_stderr": 0.010392725523775513 }, "harness|drop|3": { "em": 0.0041946308724832215, "em_stderr": 0.0006618716168266419, "f1": 0.0802946728187919, "f1_stderr": 0.0016873252068220475 }, "harness|gsm8k|5": { "acc": 0.12357846853677028, "acc_stderr": 0.009065050306776921 }, "harness|winogrande|5": { "acc": 0.7758484609313339, "acc_stderr": 0.011720400740774104 } } ``` ### 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_xzuyn__LLaMa-2-PeanutButter_v14-7B
--- pretty_name: Evaluation run of xzuyn/LLaMa-2-PeanutButter_v14-7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [xzuyn/LLaMa-2-PeanutButter_v14-7B](https://huggingface.co/xzuyn/LLaMa-2-PeanutButter_v14-7B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_xzuyn__LLaMa-2-PeanutButter_v14-7B\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-08-31T13:28:42.641649](https://huggingface.co/datasets/open-llm-leaderboard/details_xzuyn__LLaMa-2-PeanutButter_v14-7B/blob/main/results_2023-08-31T13%3A28%3A42.641649.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\": 0.46314650559918413,\n\ \ \"acc_stderr\": 0.0353597619312551,\n \"acc_norm\": 0.4669718546477287,\n\ \ \"acc_norm_stderr\": 0.03534376319528717,\n \"mc1\": 0.27906976744186046,\n\ \ \"mc1_stderr\": 0.0157021070906279,\n \"mc2\": 0.44677492914800465,\n\ \ \"mc2_stderr\": 0.015984529713376692\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5051194539249146,\n \"acc_stderr\": 0.014610624890309157,\n\ \ \"acc_norm\": 0.5418088737201365,\n \"acc_norm_stderr\": 0.014560220308714697\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6148177653853814,\n\ \ \"acc_stderr\": 0.004856437955719853,\n \"acc_norm\": 0.803823939454292,\n\ \ \"acc_norm_stderr\": 0.003962917115206181\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621502,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621502\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.4962962962962963,\n\ \ \"acc_stderr\": 0.04319223625811331,\n \"acc_norm\": 0.4962962962962963,\n\ \ \"acc_norm_stderr\": 0.04319223625811331\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.4407894736842105,\n \"acc_stderr\": 0.040403110624904356,\n\ \ \"acc_norm\": 0.4407894736842105,\n \"acc_norm_stderr\": 0.040403110624904356\n\ \ },\n \"harness|hendrycksTest-business_ethics|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-clinical_knowledge|5\"\ : {\n \"acc\": 0.4867924528301887,\n \"acc_stderr\": 0.030762134874500476,\n\ \ \"acc_norm\": 0.4867924528301887,\n \"acc_norm_stderr\": 0.030762134874500476\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.4861111111111111,\n\ \ \"acc_stderr\": 0.04179596617581002,\n \"acc_norm\": 0.4861111111111111,\n\ \ \"acc_norm_stderr\": 0.04179596617581002\n },\n \"harness|hendrycksTest-college_chemistry|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_computer_science|5\": {\n \"acc\"\ : 0.39,\n \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.39,\n\ \ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.31,\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\": 0.41040462427745666,\n\ \ \"acc_stderr\": 0.03750757044895537,\n \"acc_norm\": 0.41040462427745666,\n\ \ \"acc_norm_stderr\": 0.03750757044895537\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.19607843137254902,\n \"acc_stderr\": 0.03950581861179963,\n\ \ \"acc_norm\": 0.19607843137254902,\n \"acc_norm_stderr\": 0.03950581861179963\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.51,\n \"acc_stderr\": 0.05024183937956913,\n \"acc_norm\": 0.51,\n\ \ \"acc_norm_stderr\": 0.05024183937956913\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.425531914893617,\n \"acc_stderr\": 0.03232146916224468,\n\ \ \"acc_norm\": 0.425531914893617,\n \"acc_norm_stderr\": 0.03232146916224468\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.32456140350877194,\n\ \ \"acc_stderr\": 0.04404556157374767,\n \"acc_norm\": 0.32456140350877194,\n\ \ \"acc_norm_stderr\": 0.04404556157374767\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.4413793103448276,\n \"acc_stderr\": 0.04137931034482758,\n\ \ \"acc_norm\": 0.4413793103448276,\n \"acc_norm_stderr\": 0.04137931034482758\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.3148148148148148,\n \"acc_stderr\": 0.02391998416404773,\n \"\ acc_norm\": 0.3148148148148148,\n \"acc_norm_stderr\": 0.02391998416404773\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.23809523809523808,\n\ \ \"acc_stderr\": 0.03809523809523811,\n \"acc_norm\": 0.23809523809523808,\n\ \ \"acc_norm_stderr\": 0.03809523809523811\n },\n \"harness|hendrycksTest-global_facts|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-high_school_biology|5\": {\n \"acc\": 0.4935483870967742,\n\ \ \"acc_stderr\": 0.02844163823354051,\n \"acc_norm\": 0.4935483870967742,\n\ \ \"acc_norm_stderr\": 0.02844163823354051\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.3891625615763547,\n \"acc_stderr\": 0.03430462416103872,\n\ \ \"acc_norm\": 0.3891625615763547,\n \"acc_norm_stderr\": 0.03430462416103872\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.45,\n \"acc_stderr\": 0.049999999999999996,\n \"acc_norm\"\ : 0.45,\n \"acc_norm_stderr\": 0.049999999999999996\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.5393939393939394,\n \"acc_stderr\": 0.03892207016552013,\n\ \ \"acc_norm\": 0.5393939393939394,\n \"acc_norm_stderr\": 0.03892207016552013\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.5303030303030303,\n \"acc_stderr\": 0.03555804051763929,\n \"\ acc_norm\": 0.5303030303030303,\n \"acc_norm_stderr\": 0.03555804051763929\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.6528497409326425,\n \"acc_stderr\": 0.03435696168361355,\n\ \ \"acc_norm\": 0.6528497409326425,\n \"acc_norm_stderr\": 0.03435696168361355\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.43333333333333335,\n \"acc_stderr\": 0.025124653525885124,\n\ \ \"acc_norm\": 0.43333333333333335,\n \"acc_norm_stderr\": 0.025124653525885124\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.29259259259259257,\n \"acc_stderr\": 0.027738969632176088,\n \ \ \"acc_norm\": 0.29259259259259257,\n \"acc_norm_stderr\": 0.027738969632176088\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.4327731092436975,\n \"acc_stderr\": 0.03218358107742613,\n \ \ \"acc_norm\": 0.4327731092436975,\n \"acc_norm_stderr\": 0.03218358107742613\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.304635761589404,\n \"acc_stderr\": 0.03757949922943342,\n \"acc_norm\"\ : 0.304635761589404,\n \"acc_norm_stderr\": 0.03757949922943342\n },\n\ \ \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.6238532110091743,\n\ \ \"acc_stderr\": 0.020769231968205085,\n \"acc_norm\": 0.6238532110091743,\n\ \ \"acc_norm_stderr\": 0.020769231968205085\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\ : {\n \"acc\": 0.27314814814814814,\n \"acc_stderr\": 0.030388051301678116,\n\ \ \"acc_norm\": 0.27314814814814814,\n \"acc_norm_stderr\": 0.030388051301678116\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.5686274509803921,\n \"acc_stderr\": 0.03476099060501636,\n \"\ acc_norm\": 0.5686274509803921,\n \"acc_norm_stderr\": 0.03476099060501636\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.5907172995780591,\n \"acc_stderr\": 0.032007041833595914,\n \ \ \"acc_norm\": 0.5907172995780591,\n \"acc_norm_stderr\": 0.032007041833595914\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.48878923766816146,\n\ \ \"acc_stderr\": 0.033549366530984746,\n \"acc_norm\": 0.48878923766816146,\n\ \ \"acc_norm_stderr\": 0.033549366530984746\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.5114503816793893,\n \"acc_stderr\": 0.043841400240780176,\n\ \ \"acc_norm\": 0.5114503816793893,\n \"acc_norm_stderr\": 0.043841400240780176\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.5950413223140496,\n \"acc_stderr\": 0.04481137755942469,\n \"\ acc_norm\": 0.5950413223140496,\n \"acc_norm_stderr\": 0.04481137755942469\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.4722222222222222,\n\ \ \"acc_stderr\": 0.04826217294139894,\n \"acc_norm\": 0.4722222222222222,\n\ \ \"acc_norm_stderr\": 0.04826217294139894\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.5030674846625767,\n \"acc_stderr\": 0.03928297078179663,\n\ \ \"acc_norm\": 0.5030674846625767,\n \"acc_norm_stderr\": 0.03928297078179663\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.375,\n\ \ \"acc_stderr\": 0.04595091388086298,\n \"acc_norm\": 0.375,\n \ \ \"acc_norm_stderr\": 0.04595091388086298\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.5145631067961165,\n \"acc_stderr\": 0.049486373240266356,\n\ \ \"acc_norm\": 0.5145631067961165,\n \"acc_norm_stderr\": 0.049486373240266356\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.6752136752136753,\n\ \ \"acc_stderr\": 0.03067902276549883,\n \"acc_norm\": 0.6752136752136753,\n\ \ \"acc_norm_stderr\": 0.03067902276549883\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.52,\n \"acc_stderr\": 0.05021167315686779,\n \ \ \"acc_norm\": 0.52,\n \"acc_norm_stderr\": 0.05021167315686779\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.6372924648786717,\n\ \ \"acc_stderr\": 0.017192708674602302,\n \"acc_norm\": 0.6372924648786717,\n\ \ \"acc_norm_stderr\": 0.017192708674602302\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.4797687861271676,\n \"acc_stderr\": 0.026897049996382868,\n\ \ \"acc_norm\": 0.4797687861271676,\n \"acc_norm_stderr\": 0.026897049996382868\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.30837988826815643,\n\ \ \"acc_stderr\": 0.015445716910998877,\n \"acc_norm\": 0.30837988826815643,\n\ \ \"acc_norm_stderr\": 0.015445716910998877\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.5130718954248366,\n \"acc_stderr\": 0.028620130800700246,\n\ \ \"acc_norm\": 0.5130718954248366,\n \"acc_norm_stderr\": 0.028620130800700246\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.5305466237942122,\n\ \ \"acc_stderr\": 0.028345045864840622,\n \"acc_norm\": 0.5305466237942122,\n\ \ \"acc_norm_stderr\": 0.028345045864840622\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.5061728395061729,\n \"acc_stderr\": 0.027818623962583295,\n\ \ \"acc_norm\": 0.5061728395061729,\n \"acc_norm_stderr\": 0.027818623962583295\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.36879432624113473,\n \"acc_stderr\": 0.028782227561347247,\n \ \ \"acc_norm\": 0.36879432624113473,\n \"acc_norm_stderr\": 0.028782227561347247\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.35071707953063885,\n\ \ \"acc_stderr\": 0.01218777337074152,\n \"acc_norm\": 0.35071707953063885,\n\ \ \"acc_norm_stderr\": 0.01218777337074152\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.5036764705882353,\n \"acc_stderr\": 0.030372015885428188,\n\ \ \"acc_norm\": 0.5036764705882353,\n \"acc_norm_stderr\": 0.030372015885428188\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.43300653594771243,\n \"acc_stderr\": 0.02004544247332423,\n \ \ \"acc_norm\": 0.43300653594771243,\n \"acc_norm_stderr\": 0.02004544247332423\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.5363636363636364,\n\ \ \"acc_stderr\": 0.04776449162396197,\n \"acc_norm\": 0.5363636363636364,\n\ \ \"acc_norm_stderr\": 0.04776449162396197\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.49795918367346936,\n \"acc_stderr\": 0.0320089533497105,\n\ \ \"acc_norm\": 0.49795918367346936,\n \"acc_norm_stderr\": 0.0320089533497105\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.5970149253731343,\n\ \ \"acc_stderr\": 0.034683432951111266,\n \"acc_norm\": 0.5970149253731343,\n\ \ \"acc_norm_stderr\": 0.034683432951111266\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.72,\n \"acc_stderr\": 0.04512608598542128,\n \ \ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.04512608598542128\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.39759036144578314,\n\ \ \"acc_stderr\": 0.038099730845402184,\n \"acc_norm\": 0.39759036144578314,\n\ \ \"acc_norm_stderr\": 0.038099730845402184\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.6842105263157895,\n \"acc_stderr\": 0.03565079670708312,\n\ \ \"acc_norm\": 0.6842105263157895,\n \"acc_norm_stderr\": 0.03565079670708312\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.27906976744186046,\n\ \ \"mc1_stderr\": 0.0157021070906279,\n \"mc2\": 0.44677492914800465,\n\ \ \"mc2_stderr\": 0.015984529713376692\n }\n}\n```" repo_url: https://huggingface.co/xzuyn/LLaMa-2-PeanutButter_v14-7B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|arc:challenge|25_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hellaswag|10_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-31T13:28:42.641649.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-management|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-virology|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-31T13:28:42.641649.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_31T13_28_42.641649 path: - '**/details_harness|truthfulqa:mc|0_2023-08-31T13:28:42.641649.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-08-31T13:28:42.641649.parquet' - config_name: results data_files: - split: 2023_08_31T13_28_42.641649 path: - results_2023-08-31T13:28:42.641649.parquet - split: latest path: - results_2023-08-31T13:28:42.641649.parquet --- # Dataset Card for Evaluation run of xzuyn/LLaMa-2-PeanutButter_v14-7B ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/xzuyn/LLaMa-2-PeanutButter_v14-7B - **Paper:** - **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - **Point of Contact:** clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [xzuyn/LLaMa-2-PeanutButter_v14-7B](https://huggingface.co/xzuyn/LLaMa-2-PeanutButter_v14-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_xzuyn__LLaMa-2-PeanutButter_v14-7B", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-08-31T13:28:42.641649](https://huggingface.co/datasets/open-llm-leaderboard/details_xzuyn__LLaMa-2-PeanutButter_v14-7B/blob/main/results_2023-08-31T13%3A28%3A42.641649.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": 0.46314650559918413, "acc_stderr": 0.0353597619312551, "acc_norm": 0.4669718546477287, "acc_norm_stderr": 0.03534376319528717, "mc1": 0.27906976744186046, "mc1_stderr": 0.0157021070906279, "mc2": 0.44677492914800465, "mc2_stderr": 0.015984529713376692 }, "harness|arc:challenge|25": { "acc": 0.5051194539249146, "acc_stderr": 0.014610624890309157, "acc_norm": 0.5418088737201365, "acc_norm_stderr": 0.014560220308714697 }, "harness|hellaswag|10": { "acc": 0.6148177653853814, "acc_stderr": 0.004856437955719853, "acc_norm": 0.803823939454292, "acc_norm_stderr": 0.003962917115206181 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.32, "acc_stderr": 0.04688261722621502, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621502 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4962962962962963, "acc_stderr": 0.04319223625811331, "acc_norm": 0.4962962962962963, "acc_norm_stderr": 0.04319223625811331 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.4407894736842105, "acc_stderr": 0.040403110624904356, "acc_norm": 0.4407894736842105, "acc_norm_stderr": 0.040403110624904356 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.4867924528301887, "acc_stderr": 0.030762134874500476, "acc_norm": 0.4867924528301887, "acc_norm_stderr": 0.030762134874500476 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4861111111111111, "acc_stderr": 0.04179596617581002, "acc_norm": 0.4861111111111111, "acc_norm_stderr": 0.04179596617581002 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.41040462427745666, "acc_stderr": 0.03750757044895537, "acc_norm": 0.41040462427745666, "acc_norm_stderr": 0.03750757044895537 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.19607843137254902, "acc_stderr": 0.03950581861179963, "acc_norm": 0.19607843137254902, "acc_norm_stderr": 0.03950581861179963 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.51, "acc_stderr": 0.05024183937956913, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956913 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.425531914893617, "acc_stderr": 0.03232146916224468, "acc_norm": 0.425531914893617, "acc_norm_stderr": 0.03232146916224468 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.32456140350877194, "acc_stderr": 0.04404556157374767, "acc_norm": 0.32456140350877194, "acc_norm_stderr": 0.04404556157374767 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4413793103448276, "acc_stderr": 0.04137931034482758, "acc_norm": 0.4413793103448276, "acc_norm_stderr": 0.04137931034482758 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3148148148148148, "acc_stderr": 0.02391998416404773, "acc_norm": 0.3148148148148148, "acc_norm_stderr": 0.02391998416404773 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.23809523809523808, "acc_stderr": 0.03809523809523811, "acc_norm": 0.23809523809523808, "acc_norm_stderr": 0.03809523809523811 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.4935483870967742, "acc_stderr": 0.02844163823354051, "acc_norm": 0.4935483870967742, "acc_norm_stderr": 0.02844163823354051 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3891625615763547, "acc_stderr": 0.03430462416103872, "acc_norm": 0.3891625615763547, "acc_norm_stderr": 0.03430462416103872 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.45, "acc_stderr": 0.049999999999999996, "acc_norm": 0.45, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.5393939393939394, "acc_stderr": 0.03892207016552013, "acc_norm": 0.5393939393939394, "acc_norm_stderr": 0.03892207016552013 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5303030303030303, "acc_stderr": 0.03555804051763929, "acc_norm": 0.5303030303030303, "acc_norm_stderr": 0.03555804051763929 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6528497409326425, "acc_stderr": 0.03435696168361355, "acc_norm": 0.6528497409326425, "acc_norm_stderr": 0.03435696168361355 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.43333333333333335, "acc_stderr": 0.025124653525885124, "acc_norm": 0.43333333333333335, "acc_norm_stderr": 0.025124653525885124 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.29259259259259257, "acc_stderr": 0.027738969632176088, "acc_norm": 0.29259259259259257, "acc_norm_stderr": 0.027738969632176088 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.4327731092436975, "acc_stderr": 0.03218358107742613, "acc_norm": 0.4327731092436975, "acc_norm_stderr": 0.03218358107742613 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.304635761589404, "acc_stderr": 0.03757949922943342, "acc_norm": 0.304635761589404, "acc_norm_stderr": 0.03757949922943342 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.6238532110091743, "acc_stderr": 0.020769231968205085, "acc_norm": 0.6238532110091743, "acc_norm_stderr": 0.020769231968205085 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.27314814814814814, "acc_stderr": 0.030388051301678116, "acc_norm": 0.27314814814814814, "acc_norm_stderr": 0.030388051301678116 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.5686274509803921, "acc_stderr": 0.03476099060501636, "acc_norm": 0.5686274509803921, "acc_norm_stderr": 0.03476099060501636 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.5907172995780591, "acc_stderr": 0.032007041833595914, "acc_norm": 0.5907172995780591, "acc_norm_stderr": 0.032007041833595914 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.48878923766816146, "acc_stderr": 0.033549366530984746, "acc_norm": 0.48878923766816146, "acc_norm_stderr": 0.033549366530984746 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.5114503816793893, "acc_stderr": 0.043841400240780176, "acc_norm": 0.5114503816793893, "acc_norm_stderr": 0.043841400240780176 }, "harness|hendrycksTest-international_law|5": { "acc": 0.5950413223140496, "acc_stderr": 0.04481137755942469, "acc_norm": 0.5950413223140496, "acc_norm_stderr": 0.04481137755942469 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.4722222222222222, "acc_stderr": 0.04826217294139894, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.04826217294139894 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.5030674846625767, "acc_stderr": 0.03928297078179663, "acc_norm": 0.5030674846625767, "acc_norm_stderr": 0.03928297078179663 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.375, "acc_stderr": 0.04595091388086298, "acc_norm": 0.375, "acc_norm_stderr": 0.04595091388086298 }, "harness|hendrycksTest-management|5": { "acc": 0.5145631067961165, "acc_stderr": 0.049486373240266356, "acc_norm": 0.5145631067961165, "acc_norm_stderr": 0.049486373240266356 }, "harness|hendrycksTest-marketing|5": { "acc": 0.6752136752136753, "acc_stderr": 0.03067902276549883, "acc_norm": 0.6752136752136753, "acc_norm_stderr": 0.03067902276549883 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.52, "acc_stderr": 0.05021167315686779, "acc_norm": 0.52, "acc_norm_stderr": 0.05021167315686779 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.6372924648786717, "acc_stderr": 0.017192708674602302, "acc_norm": 0.6372924648786717, "acc_norm_stderr": 0.017192708674602302 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.4797687861271676, "acc_stderr": 0.026897049996382868, "acc_norm": 0.4797687861271676, "acc_norm_stderr": 0.026897049996382868 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.30837988826815643, "acc_stderr": 0.015445716910998877, "acc_norm": 0.30837988826815643, "acc_norm_stderr": 0.015445716910998877 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.5130718954248366, "acc_stderr": 0.028620130800700246, "acc_norm": 0.5130718954248366, "acc_norm_stderr": 0.028620130800700246 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.5305466237942122, "acc_stderr": 0.028345045864840622, "acc_norm": 0.5305466237942122, "acc_norm_stderr": 0.028345045864840622 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.5061728395061729, "acc_stderr": 0.027818623962583295, "acc_norm": 0.5061728395061729, "acc_norm_stderr": 0.027818623962583295 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.36879432624113473, "acc_stderr": 0.028782227561347247, "acc_norm": 0.36879432624113473, "acc_norm_stderr": 0.028782227561347247 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.35071707953063885, "acc_stderr": 0.01218777337074152, "acc_norm": 0.35071707953063885, "acc_norm_stderr": 0.01218777337074152 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.5036764705882353, "acc_stderr": 0.030372015885428188, "acc_norm": 0.5036764705882353, "acc_norm_stderr": 0.030372015885428188 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.43300653594771243, "acc_stderr": 0.02004544247332423, "acc_norm": 0.43300653594771243, "acc_norm_stderr": 0.02004544247332423 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.5363636363636364, "acc_stderr": 0.04776449162396197, "acc_norm": 0.5363636363636364, "acc_norm_stderr": 0.04776449162396197 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.49795918367346936, "acc_stderr": 0.0320089533497105, "acc_norm": 0.49795918367346936, "acc_norm_stderr": 0.0320089533497105 }, "harness|hendrycksTest-sociology|5": { "acc": 0.5970149253731343, "acc_stderr": 0.034683432951111266, "acc_norm": 0.5970149253731343, "acc_norm_stderr": 0.034683432951111266 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-virology|5": { "acc": 0.39759036144578314, "acc_stderr": 0.038099730845402184, "acc_norm": 0.39759036144578314, "acc_norm_stderr": 0.038099730845402184 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.6842105263157895, "acc_stderr": 0.03565079670708312, "acc_norm": 0.6842105263157895, "acc_norm_stderr": 0.03565079670708312 }, "harness|truthfulqa:mc|0": { "mc1": 0.27906976744186046, "mc1_stderr": 0.0157021070906279, "mc2": 0.44677492914800465, "mc2_stderr": 0.015984529713376692 } } ``` ### 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]
adilhabibi/bioacoustic_segment_img
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': Bare-throated Whistler '1': Common Paradise Kingfisher '2': Dusky Megapode '3': Green-backed Kingfisher '4': Ivory-breasted Pitta '5': Red Bird-of-paradise '6': Rusty-breasted Cuckoo '7': Standardwing '8': Sulawesi Bush Warbler '9': Sulawesi Scops Owl '10': Wilson's Bird-of-paradise splits: - name: train num_bytes: 8842324.329 num_examples: 1457 download_size: 8825727 dataset_size: 8842324.329 configs: - config_name: default data_files: - split: train path: data/train-* ---
Laurie/bytedance_rag_eval
--- license: mit ---
communityai/HuggingFaceH4___deita-10k-v0-sft
--- dataset_info: features: - name: source dtype: string - name: conversations list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 345005293.0 num_examples: 9500 download_size: 136782991 dataset_size: 345005293.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
Aniemore/resd_annotated_multi
--- dataset_info: features: - name: name dtype: string - name: path dtype: string - name: speech sequence: float64 - name: text dtype: string - name: emotion dtype: string - name: text_emotions sequence: string splits: - name: train num_bytes: 866818029 num_examples: 1116 - name: test num_bytes: 212496333 num_examples: 280 download_size: 615228382 dataset_size: 1079314362 --- # Dataset Card for "resd_annotated_multi" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
coding-assistant-custom/dummy-dataset-sayak
--- dataset_info: features: - name: reponame dtype: string - name: filepath dtype: string - name: content dtype: string splits: - name: train num_bytes: 79032 num_examples: 18 download_size: 27713 dataset_size: 79032 --- # Dataset Card for "dummy-dataset-sayak" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
malaysia-ai/Multiturn-JPJ-Test-Prep
--- license: apache-2.0 --- Multi-turn conversation generated using Mistral-V4 on JPJ-Test-Prep questions.
juancopi81/binomial_3blue1brown_test
--- dataset_info: features: - name: CHANNEL_NAME dtype: string - name: URL dtype: string - name: TITLE dtype: string - name: DESCRIPTION dtype: string - name: TRANSCRIPTION dtype: string - name: SEGMENTS dtype: string splits: - name: train num_bytes: 59462 num_examples: 2 download_size: 44700 dataset_size: 59462 --- # Dataset Card for "binomial_3blue1brown_test" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
HoangHa/SMILES-250M
--- dataset_info: features: - name: SMILES dtype: string splits: - name: train num_bytes: 1626837623.1854794 num_examples: 84345972 download_size: 1799608655 dataset_size: 1626837623.1854794 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "SMILES-250M" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Seanxh/twitter_dataset_1713199616
--- 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: 102146 num_examples: 238 download_size: 40787 dataset_size: 102146 configs: - config_name: default data_files: - split: train path: data/train-* ---
GETALP/FLUE_WSD
--- license: lgpl multilinguality: - monolingual language: - fr task_categories: - other task_ids: - word-sense-disambiguation dataset_info: features: - name: document_id dtype: string - name: sentence dtype: string - name: sentence_label dtype: string - name: sentence_first_label dtype: string - name: surface_forms sequence: string - name: labels sequence: string - name: first_labels sequence: string - name: word_id sequence: string - name: scores sequence: string - name: lemmas sequence: string - name: pos sequence: string splits: - name: SemCor num_bytes: 71632913 num_examples: 37176 - name: SemEval num_bytes: 749832 num_examples: 306 - name: WNGT num_bytes: 206691837 num_examples: 117659 download_size: 41831981 dataset_size: 279074582 --- # Word Sense Disambiguation for FLUE ## Dataset Description - **Homepage:** - **Repository:** - **https://arxiv.org/pdf/1905.05677.pdf** - **Leaderboard:** - **loic.vial@univ-grenoble-alpes.fr** ### Dataset Summary This dataset is splitted in 3 sub-datasets: FrenchSemEval-Task12, French WNGT and an automatic translation of SemCor. ### Supported Tasks and Leaderboards Word Sense Disambiguation for French. ### Language French ### Licensing Information ``` GNU Lesser General Public License ``` ### Citation Information ```bibtex @inproceedings{vial-etal-2019-sense, title = "Sense Vocabulary Compression through the Semantic Knowledge of {W}ord{N}et for Neural Word Sense Disambiguation", author = {Vial, Lo{\"\i}c and Lecouteux, Benjamin and Schwab, Didier}, booktitle = "Proceedings of the 10th Global Wordnet Conference", month = jul, year = "2019", address = "Wroclaw, Poland", publisher = "Global Wordnet Association", url = "https://aclanthology.org/2019.gwc-1.14", pages = "108--117", abstract = "In this article, we tackle the issue of the limited quantity of manually sense annotated corpora for the task of word sense disambiguation, by exploiting the semantic relationships between senses such as synonymy, hypernymy and hyponymy, in order to compress the sense vocabulary of Princeton WordNet, and thus reduce the number of different sense tags that must be observed to disambiguate all words of the lexical database. We propose two different methods that greatly reduce the size of neural WSD models, with the benefit of improving their coverage without additional training data, and without impacting their precision. In addition to our methods, we present a WSD system which relies on pre-trained BERT word vectors in order to achieve results that significantly outperforms the state of the art on all WSD evaluation tasks.", } ``` ### Contributions * loic.vial@univ-grenoble-alpes.fr * benjamin.lecouteux@univ-grenoble-alpes.fr * didier.schwab@univ-grenoble-alpes.fr
xingkunliuxtracta/processed_demo
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: id dtype: string - name: package_name dtype: string - name: review dtype: string - name: date dtype: string - name: star dtype: int64 - name: version_id dtype: int64 splits: - name: train num_bytes: 1508 num_examples: 5 - name: test num_bytes: 956 num_examples: 5 download_size: 9453 dataset_size: 2464 --- # Dataset Card for "processed_demo" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
navinaananthan/Kurdish-Sorani-Parallel-Corpus
--- language: - ku ---
fivetech/tao
--- license: mit ---
joey234/mmlu-high_school_microeconomics-neg
--- dataset_info: features: - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: question dtype: string splits: - name: test num_bytes: 71310 num_examples: 238 download_size: 36920 dataset_size: 71310 --- # Dataset Card for "mmlu-high_school_microeconomics-neg" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
nluai/ZaloAI_NouResearch
--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: validation num_bytes: 261148 num_examples: 687 download_size: 131765 dataset_size: 261148 configs: - config_name: default data_files: - split: validation path: data/validation-* ---
mgane/2D_Video_Game_Cartoon_Character_Sprite-Sheets
--- task_categories: - text-to-image - image-classification - image-to-image language: - en tags: - art - video games size_categories: - n<1K --- # Dataset Card for Dataset Name ## Dataset Details Experimental composition of 76 cartoon art-style video game character spritesheets. Resized to 512x512, mixed variation of animation styles. ### Dataset Description All images editted using Tiled image editting software as most assets are typically downloaded individually and not in sequence. I compiled each animation sequence into one img to display animations frame-by-frame evenly distributed across some common animations seen in 2D video game art (Idle, Attack, Walk, Running, etc). I had used this same image set for some experimental tests on Stable Diffusion XL via LORA and Dreambooth training methods for some solid results post-training. - **Curated by:** [m-gane] ### Disclaimer None of these characters were from my original making, but a compilation from open-source 2D video game asset sites from various artists. For more information regarding source assets please check out: https://itch.io/game-assets/tag-2d and https://opengameart.org/.
indiejoseph/wikipedia-zh-yue-summaries
--- dataset_info: features: - name: summary dtype: string - name: title dtype: string - name: category dtype: string - name: content dtype: string splits: - name: train num_bytes: 9555531 num_examples: 7109 download_size: 6795226 dataset_size: 9555531 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "wikipedia-zh-yue-summaries" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
AnonymousPaperSubmissions/Testing_all_variables
--- license: mit ---
tyzhu/squad_qa_title_v5_full_recite_full_passage_random_permute_rerun_8
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers sequence: - name: text dtype: string - name: answer_start dtype: int32 - name: answer dtype: string - name: context_id dtype: string - name: inputs dtype: string - name: targets dtype: string splits: - name: train num_bytes: 11290731.700778643 num_examples: 6305 - name: validation num_bytes: 590772 num_examples: 300 download_size: 1824305 dataset_size: 11881503.700778643 --- # Dataset Card for "squad_qa_title_v5_full_recite_full_passage_random_permute_rerun_8" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
lmqg/qa_squadshifts_synthetic
--- license: cc-by-4.0 pretty_name: Synthetic QA dataset on SQuADShifts. language: en multilinguality: monolingual size_categories: 10K<n<100K source_datasets: - extended|wikipedia task_categories: - question-answering task_ids: - extractive-qa --- # Dataset Card for "lmqg/qa_squadshifts_synthetic" ## Dataset Description - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation) - **Paper:** [https://arxiv.org/abs/2210.03992](https://arxiv.org/abs/2210.03992) - **Point of Contact:** [Asahi Ushio](http://asahiushio.com/) ### Dataset Summary This is a synthetic QA dataset generated with fine-tuned QG models over [`lmqg/qa_squadshifts`](https://huggingface.co/datasets/lmqg/qa_squadshifts), made for question-answering based evaluation (QAE) for question generation model proposed by [Zhang and Bansal, 2019](https://aclanthology.org/D19-1253/). The test split is the original validation set of [`lmqg/qa_squadshifts`](https://huggingface.co/datasets/lmqg/qa_squadshifts), where the model should be evaluate on. ### Supported Tasks and Leaderboards * `question-answering` ### Languages English (en) ## Dataset Structure ### Data Fields The data fields are the same among all splits. #### plain_text - `id`: a `string` feature of id - `title`: a `string` feature of title of the paragraph - `context`: a `string` feature of paragraph - `question`: a `string` feature of question - `answers`: a `json` feature of answers ### Data Splits TBA ## Citation Information ``` @inproceedings{ushio-etal-2022-generative, title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration", author = "Ushio, Asahi and Alva-Manchego, Fernando and Camacho-Collados, Jose", booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing", month = dec, year = "2022", address = "Abu Dhabi, U.A.E.", publisher = "Association for Computational Linguistics", } ```
mrseeker87/bittensor_qa
--- license: cc-by-sa-4.0 task_categories: - question-answering language: - en size_categories: - 1K<n<10K --- Dataset created from bittensor's subnet1. Will be constantly updated as I add more Q/A. Dataset is currently in "raw" format, would love to have something prettier for loading into datasets.
moizsajid/dreambooth-markhor
--- title: Markhor images from iStock tags: - keras-dreambooth - nature - diffusers - text-to-image ---
open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r128_a64
--- pretty_name: Evaluation run of BFauber/lora_llama2-13b_10e5_r128_a64 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [BFauber/lora_llama2-13b_10e5_r128_a64](https://huggingface.co/BFauber/lora_llama2-13b_10e5_r128_a64)\ \ 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_BFauber__lora_llama2-13b_10e5_r128_a64\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-10T01:12:24.322159](https://huggingface.co/datasets/open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r128_a64/blob/main/results_2024-02-10T01-12-24.322159.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\": 0.5547782267581419,\n\ \ \"acc_stderr\": 0.03364758987723506,\n \"acc_norm\": 0.5605657594957815,\n\ \ \"acc_norm_stderr\": 0.034369652344960734,\n \"mc1\": 0.2582619339045288,\n\ \ \"mc1_stderr\": 0.0153218216884762,\n \"mc2\": 0.37196197837880757,\n\ \ \"mc2_stderr\": 0.013661684990590431\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5639931740614335,\n \"acc_stderr\": 0.014491225699230916,\n\ \ \"acc_norm\": 0.590443686006826,\n \"acc_norm_stderr\": 0.014370358632472434\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6166102370045807,\n\ \ \"acc_stderr\": 0.004852182621274261,\n \"acc_norm\": 0.8227444732125074,\n\ \ \"acc_norm_stderr\": 0.00381104341202466\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\": 0.5037037037037037,\n\ \ \"acc_stderr\": 0.04319223625811331,\n \"acc_norm\": 0.5037037037037037,\n\ \ \"acc_norm_stderr\": 0.04319223625811331\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.5394736842105263,\n \"acc_stderr\": 0.04056242252249033,\n\ \ \"acc_norm\": 0.5394736842105263,\n \"acc_norm_stderr\": 0.04056242252249033\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.51,\n\ \ \"acc_stderr\": 0.05024183937956913,\n \"acc_norm\": 0.51,\n \ \ \"acc_norm_stderr\": 0.05024183937956913\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.6415094339622641,\n \"acc_stderr\": 0.029514703583981765,\n\ \ \"acc_norm\": 0.6415094339622641,\n \"acc_norm_stderr\": 0.029514703583981765\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.625,\n\ \ \"acc_stderr\": 0.04048439222695598,\n \"acc_norm\": 0.625,\n \ \ \"acc_norm_stderr\": 0.04048439222695598\n },\n \"harness|hendrycksTest-college_chemistry|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_computer_science|5\": {\n \"acc\"\ : 0.46,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.46,\n\ \ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.5606936416184971,\n\ \ \"acc_stderr\": 0.037842719328874674,\n \"acc_norm\": 0.5606936416184971,\n\ \ \"acc_norm_stderr\": 0.037842719328874674\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.2549019607843137,\n \"acc_stderr\": 0.043364327079931785,\n\ \ \"acc_norm\": 0.2549019607843137,\n \"acc_norm_stderr\": 0.043364327079931785\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.69,\n\ \ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.46382978723404256,\n \"acc_stderr\": 0.032600385118357715,\n\ \ \"acc_norm\": 0.46382978723404256,\n \"acc_norm_stderr\": 0.032600385118357715\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2982456140350877,\n\ \ \"acc_stderr\": 0.04303684033537314,\n \"acc_norm\": 0.2982456140350877,\n\ \ \"acc_norm_stderr\": 0.04303684033537314\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5310344827586206,\n \"acc_stderr\": 0.04158632762097828,\n\ \ \"acc_norm\": 0.5310344827586206,\n \"acc_norm_stderr\": 0.04158632762097828\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.31216931216931215,\n \"acc_stderr\": 0.023865206836972606,\n \"\ acc_norm\": 0.31216931216931215,\n \"acc_norm_stderr\": 0.023865206836972606\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.31746031746031744,\n\ \ \"acc_stderr\": 0.04163453031302859,\n \"acc_norm\": 0.31746031746031744,\n\ \ \"acc_norm_stderr\": 0.04163453031302859\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.047937248544110196,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.047937248544110196\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.6709677419354839,\n \"acc_stderr\": 0.026729499068349958,\n \"\ acc_norm\": 0.6709677419354839,\n \"acc_norm_stderr\": 0.026729499068349958\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.45320197044334976,\n \"acc_stderr\": 0.03502544650845872,\n \"\ acc_norm\": 0.45320197044334976,\n \"acc_norm_stderr\": 0.03502544650845872\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.59,\n \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\"\ : 0.59,\n \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.6484848484848484,\n \"acc_stderr\": 0.037282069986826503,\n\ \ \"acc_norm\": 0.6484848484848484,\n \"acc_norm_stderr\": 0.037282069986826503\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.6818181818181818,\n \"acc_stderr\": 0.0331847733384533,\n \"acc_norm\"\ : 0.6818181818181818,\n \"acc_norm_stderr\": 0.0331847733384533\n },\n\ \ \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n \ \ \"acc\": 0.7927461139896373,\n \"acc_stderr\": 0.02925282329180363,\n\ \ \"acc_norm\": 0.7927461139896373,\n \"acc_norm_stderr\": 0.02925282329180363\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.5256410256410257,\n \"acc_stderr\": 0.02531764972644866,\n \ \ \"acc_norm\": 0.5256410256410257,\n \"acc_norm_stderr\": 0.02531764972644866\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.32222222222222224,\n \"acc_stderr\": 0.028493465091028604,\n \ \ \"acc_norm\": 0.32222222222222224,\n \"acc_norm_stderr\": 0.028493465091028604\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.5462184873949579,\n \"acc_stderr\": 0.03233943468182088,\n \ \ \"acc_norm\": 0.5462184873949579,\n \"acc_norm_stderr\": 0.03233943468182088\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.3443708609271523,\n \"acc_stderr\": 0.038796870240733264,\n \"\ acc_norm\": 0.3443708609271523,\n \"acc_norm_stderr\": 0.038796870240733264\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.7431192660550459,\n \"acc_stderr\": 0.01873249292834246,\n \"\ acc_norm\": 0.7431192660550459,\n \"acc_norm_stderr\": 0.01873249292834246\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.47685185185185186,\n \"acc_stderr\": 0.03406315360711507,\n \"\ acc_norm\": 0.47685185185185186,\n \"acc_norm_stderr\": 0.03406315360711507\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.7352941176470589,\n \"acc_stderr\": 0.030964517926923403,\n \"\ acc_norm\": 0.7352941176470589,\n \"acc_norm_stderr\": 0.030964517926923403\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7130801687763713,\n \"acc_stderr\": 0.02944377302259469,\n \ \ \"acc_norm\": 0.7130801687763713,\n \"acc_norm_stderr\": 0.02944377302259469\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6457399103139013,\n\ \ \"acc_stderr\": 0.032100621541349864,\n \"acc_norm\": 0.6457399103139013,\n\ \ \"acc_norm_stderr\": 0.032100621541349864\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.6259541984732825,\n \"acc_stderr\": 0.042438692422305246,\n\ \ \"acc_norm\": 0.6259541984732825,\n \"acc_norm_stderr\": 0.042438692422305246\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7355371900826446,\n \"acc_stderr\": 0.04026187527591207,\n \"\ acc_norm\": 0.7355371900826446,\n \"acc_norm_stderr\": 0.04026187527591207\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7314814814814815,\n\ \ \"acc_stderr\": 0.042844679680521934,\n \"acc_norm\": 0.7314814814814815,\n\ \ \"acc_norm_stderr\": 0.042844679680521934\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.6809815950920245,\n \"acc_stderr\": 0.03661997551073836,\n\ \ \"acc_norm\": 0.6809815950920245,\n \"acc_norm_stderr\": 0.03661997551073836\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.30357142857142855,\n\ \ \"acc_stderr\": 0.04364226155841044,\n \"acc_norm\": 0.30357142857142855,\n\ \ \"acc_norm_stderr\": 0.04364226155841044\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\": 0.7991452991452992,\n\ \ \"acc_stderr\": 0.026246772946890474,\n \"acc_norm\": 0.7991452991452992,\n\ \ \"acc_norm_stderr\": 0.026246772946890474\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.55,\n \"acc_stderr\": 0.04999999999999999,\n \ \ \"acc_norm\": 0.55,\n \"acc_norm_stderr\": 0.04999999999999999\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7458492975734355,\n\ \ \"acc_stderr\": 0.015569254692045757,\n \"acc_norm\": 0.7458492975734355,\n\ \ \"acc_norm_stderr\": 0.015569254692045757\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6213872832369942,\n \"acc_stderr\": 0.026113749361310345,\n\ \ \"acc_norm\": 0.6213872832369942,\n \"acc_norm_stderr\": 0.026113749361310345\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.27039106145251396,\n\ \ \"acc_stderr\": 0.014854993938010066,\n \"acc_norm\": 0.27039106145251396,\n\ \ \"acc_norm_stderr\": 0.014854993938010066\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.6405228758169934,\n \"acc_stderr\": 0.027475969910660952,\n\ \ \"acc_norm\": 0.6405228758169934,\n \"acc_norm_stderr\": 0.027475969910660952\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6527331189710611,\n\ \ \"acc_stderr\": 0.027040745502307336,\n \"acc_norm\": 0.6527331189710611,\n\ \ \"acc_norm_stderr\": 0.027040745502307336\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.6388888888888888,\n \"acc_stderr\": 0.026725868809100793,\n\ \ \"acc_norm\": 0.6388888888888888,\n \"acc_norm_stderr\": 0.026725868809100793\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.41134751773049644,\n \"acc_stderr\": 0.029354911159940985,\n \ \ \"acc_norm\": 0.41134751773049644,\n \"acc_norm_stderr\": 0.029354911159940985\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.41916558018252936,\n\ \ \"acc_stderr\": 0.012602244505788233,\n \"acc_norm\": 0.41916558018252936,\n\ \ \"acc_norm_stderr\": 0.012602244505788233\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.5257352941176471,\n \"acc_stderr\": 0.03033257809455502,\n\ \ \"acc_norm\": 0.5257352941176471,\n \"acc_norm_stderr\": 0.03033257809455502\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.5522875816993464,\n \"acc_stderr\": 0.020116925347422425,\n \ \ \"acc_norm\": 0.5522875816993464,\n \"acc_norm_stderr\": 0.020116925347422425\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\": 0.6244897959183674,\n \"acc_stderr\": 0.03100120903989484,\n\ \ \"acc_norm\": 0.6244897959183674,\n \"acc_norm_stderr\": 0.03100120903989484\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7263681592039801,\n\ \ \"acc_stderr\": 0.031524391865554016,\n \"acc_norm\": 0.7263681592039801,\n\ \ \"acc_norm_stderr\": 0.031524391865554016\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.81,\n \"acc_stderr\": 0.03942772444036625,\n \ \ \"acc_norm\": 0.81,\n \"acc_norm_stderr\": 0.03942772444036625\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.45180722891566266,\n\ \ \"acc_stderr\": 0.038743715565879536,\n \"acc_norm\": 0.45180722891566266,\n\ \ \"acc_norm_stderr\": 0.038743715565879536\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.7777777777777778,\n \"acc_stderr\": 0.03188578017686398,\n\ \ \"acc_norm\": 0.7777777777777778,\n \"acc_norm_stderr\": 0.03188578017686398\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.2582619339045288,\n\ \ \"mc1_stderr\": 0.0153218216884762,\n \"mc2\": 0.37196197837880757,\n\ \ \"mc2_stderr\": 0.013661684990590431\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7671665351223362,\n \"acc_stderr\": 0.011878201073856544\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.23351023502653526,\n \ \ \"acc_stderr\": 0.011653286808791043\n }\n}\n```" repo_url: https://huggingface.co/BFauber/lora_llama2-13b_10e5_r128_a64 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_10T01_12_24.322159 path: - '**/details_harness|arc:challenge|25_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-02-10T01-12-24.322159.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|gsm8k|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hellaswag|10_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-management|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-02-10T01-12-24.322159.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-management|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-virology|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-02-10T01-12-24.322159.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|truthfulqa:mc|0_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-02-10T01-12-24.322159.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_10T01_12_24.322159 path: - '**/details_harness|winogrande|5_2024-02-10T01-12-24.322159.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-02-10T01-12-24.322159.parquet' - config_name: results data_files: - split: 2024_02_10T01_12_24.322159 path: - results_2024-02-10T01-12-24.322159.parquet - split: latest path: - results_2024-02-10T01-12-24.322159.parquet --- # Dataset Card for Evaluation run of BFauber/lora_llama2-13b_10e5_r128_a64 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [BFauber/lora_llama2-13b_10e5_r128_a64](https://huggingface.co/BFauber/lora_llama2-13b_10e5_r128_a64) 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_BFauber__lora_llama2-13b_10e5_r128_a64", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-10T01:12:24.322159](https://huggingface.co/datasets/open-llm-leaderboard/details_BFauber__lora_llama2-13b_10e5_r128_a64/blob/main/results_2024-02-10T01-12-24.322159.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": 0.5547782267581419, "acc_stderr": 0.03364758987723506, "acc_norm": 0.5605657594957815, "acc_norm_stderr": 0.034369652344960734, "mc1": 0.2582619339045288, "mc1_stderr": 0.0153218216884762, "mc2": 0.37196197837880757, "mc2_stderr": 0.013661684990590431 }, "harness|arc:challenge|25": { "acc": 0.5639931740614335, "acc_stderr": 0.014491225699230916, "acc_norm": 0.590443686006826, "acc_norm_stderr": 0.014370358632472434 }, "harness|hellaswag|10": { "acc": 0.6166102370045807, "acc_stderr": 0.004852182621274261, "acc_norm": 0.8227444732125074, "acc_norm_stderr": 0.00381104341202466 }, "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": 0.5037037037037037, "acc_stderr": 0.04319223625811331, "acc_norm": 0.5037037037037037, "acc_norm_stderr": 0.04319223625811331 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5394736842105263, "acc_stderr": 0.04056242252249033, "acc_norm": 0.5394736842105263, "acc_norm_stderr": 0.04056242252249033 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.51, "acc_stderr": 0.05024183937956913, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956913 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6415094339622641, "acc_stderr": 0.029514703583981765, "acc_norm": 0.6415094339622641, "acc_norm_stderr": 0.029514703583981765 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.625, "acc_stderr": 0.04048439222695598, "acc_norm": 0.625, "acc_norm_stderr": 0.04048439222695598 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5606936416184971, "acc_stderr": 0.037842719328874674, "acc_norm": 0.5606936416184971, "acc_norm_stderr": 0.037842719328874674 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.2549019607843137, "acc_stderr": 0.043364327079931785, "acc_norm": 0.2549019607843137, "acc_norm_stderr": 0.043364327079931785 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.46382978723404256, "acc_stderr": 0.032600385118357715, "acc_norm": 0.46382978723404256, "acc_norm_stderr": 0.032600385118357715 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2982456140350877, "acc_stderr": 0.04303684033537314, "acc_norm": 0.2982456140350877, "acc_norm_stderr": 0.04303684033537314 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5310344827586206, "acc_stderr": 0.04158632762097828, "acc_norm": 0.5310344827586206, "acc_norm_stderr": 0.04158632762097828 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.31216931216931215, "acc_stderr": 0.023865206836972606, "acc_norm": 0.31216931216931215, "acc_norm_stderr": 0.023865206836972606 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.31746031746031744, "acc_stderr": 0.04163453031302859, "acc_norm": 0.31746031746031744, "acc_norm_stderr": 0.04163453031302859 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6709677419354839, "acc_stderr": 0.026729499068349958, "acc_norm": 0.6709677419354839, "acc_norm_stderr": 0.026729499068349958 }, 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"acc_stderr": 0.0469237132203465, "acc_norm": 0.6, "acc_norm_stderr": 0.0469237132203465 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6244897959183674, "acc_stderr": 0.03100120903989484, "acc_norm": 0.6244897959183674, "acc_norm_stderr": 0.03100120903989484 }, "harness|hendrycksTest-sociology|5": { "acc": 0.7263681592039801, "acc_stderr": 0.031524391865554016, "acc_norm": 0.7263681592039801, "acc_norm_stderr": 0.031524391865554016 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.81, "acc_stderr": 0.03942772444036625, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036625 }, "harness|hendrycksTest-virology|5": { "acc": 0.45180722891566266, "acc_stderr": 0.038743715565879536, "acc_norm": 0.45180722891566266, "acc_norm_stderr": 0.038743715565879536 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.7777777777777778, "acc_stderr": 0.03188578017686398, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.03188578017686398 }, "harness|truthfulqa:mc|0": { "mc1": 0.2582619339045288, "mc1_stderr": 0.0153218216884762, "mc2": 0.37196197837880757, "mc2_stderr": 0.013661684990590431 }, "harness|winogrande|5": { "acc": 0.7671665351223362, "acc_stderr": 0.011878201073856544 }, "harness|gsm8k|5": { "acc": 0.23351023502653526, "acc_stderr": 0.011653286808791043 } } ``` ## 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]
cboard-org/arasaac
--- license: mit ---
gunz0007/indo
--- license: apache-2.0 ---
Hack90/ncbi_genbank_part_41
--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: id dtype: string - name: sequence dtype: string - name: name dtype: string - name: description dtype: string - name: features dtype: int64 - name: seq_length dtype: int64 splits: - name: train num_bytes: 31049128200 num_examples: 273326 download_size: 13996445609 dataset_size: 31049128200 --- # Dataset Card for "ncbi_genbank_part_41" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
TPM-28/emotion-FR
--- license: apache-2.0 task_categories: - text-classification language: - fr tags: - multi-class-classification size_categories: - 10K<n<100K ---
M-A-D/ArabicDarija-xP3x
--- dataset_info: features: - name: text dtype: string - name: language dtype: string - name: template dtype: string - name: dataset dtype: string splits: - name: train num_bytes: 308250831 num_examples: 1223481 download_size: 129951272 dataset_size: 308250831 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "ArabicDarija-xP3x" part of "xP3x" by [Muennighoff](https://huggingface.co/Muennighoff) ## Find below part of the original dataset card ## Dataset Description - **Repository:** https://github.com/bigscience-workshop/xmtf - **Paper:** [Crosslingual Generalization through Multitask Finetuning](https://arxiv.org/abs/2211.01786) - **Point of Contact:** [Niklas Muennighoff](mailto:n.muennighoff@gmail.com) ### Dataset Summary > xP3x (Crosslingual Public Pool of Prompts eXtended) is a collection of prompts & datasets across 277 languages & 16 NLP tasks. It contains all of xP3 + much more! It is used for training future contenders of mT0 & BLOOMZ at project Aya @[C4AI](https://cohere.for.ai/) 🧡 > - **Creation:** The dataset can be recreated using instructions available [here](https://github.com/bigscience-workshop/xmtf#create-xp3) together with the file in this repository named `xp3x_create.py`. We provide this version to save processing time. - **Languages:** 277 - **xP3 Dataset Family:** <table> <tr> <th>Name</th> <th>Explanation</th> <th>Example models</th> </tr> <tr> <td><a href=https://huggingface.co/datasets/Muennighoff/xP3x>xP3x</a></t> <td>Mixture of 17 tasks in 277 languages with English prompts</td> <td>WIP - Join us at Project Aya @<a href=https://cohere.for.ai/>C4AI</a> to help!</td> </tr> <tr> <td><a href=https://huggingface.co/datasets/bigscience/xP3>xP3</a></t> <td>Mixture of 13 training tasks in 46 languages with English prompts</td> <td><a href=https://huggingface.co/bigscience/bloomz>bloomz</a> & <a href=https://huggingface.co/bigscience/mt0-xxl>mt0-xxl</a></td> </tr> <tr> <td><a href=https://huggingface.co/datasets/bigscience/xP3mt>xP3mt</a></t> <td>Mixture of 13 training tasks in 46 languages with prompts in 20 languages (machine-translated from English)</td> <td><a href=https://huggingface.co/bigscience/bloomz-mt>bloomz-mt</a> & <a href=https://huggingface.co/bigscience/mt0-xxl-mt>mt0-xxl-mt</a></td> </tr> <tr> <td><a href=https://huggingface.co/datasets/bigscience/xP3all>xP3all</a></t> <td>xP3 + evaluation datasets adding an additional 3 tasks for a total of 16 tasks in 46 languages with English prompts</td> <td></td> </tr> <tr> <td><a href=https://huggingface.co/datasets/bigscience/xP3megds>xP3megds</a></t> <td><a href=https://github.com/bigscience-workshop/Megatron-DeepSpeed>Megatron-DeepSpeed</a> processed version of xP3</td> <td><a href=https://huggingface.co/bigscience/bloomz>bloomz</a></td> </tr> <tr> <td><a href=https://huggingface.co/datasets/Muennighoff/P3>P3</a></t> <td>Repreprocessed version of the English-only <a href=https://huggingface.co/datasets/bigscience/P3>P3</a> with 8 training tasks</td> <td><a href=https://huggingface.co/bigscience/bloomz-p3>bloomz-p3</a> & <a href=https://huggingface.co/bigscience/mt0-xxl-p3>mt0-xxl-p3</a></td> </tr> </table> [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
vikenkd/mini-python_code_instructions_research
--- license: mit dataset_info: features: - name: Instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 2766589.5 num_examples: 750 - name: test num_bytes: 922196.5 num_examples: 250 download_size: 1612042 dataset_size: 3688786.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
freshpearYoon/v3_val_free_3
--- dataset_info: features: - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 15366825976 num_examples: 10000 download_size: 2259862247 dataset_size: 15366825976 configs: - config_name: default data_files: - split: train path: data/train-* ---
smithclay/nortonstories
--- license: apache-2.0 dataset_info: features: - name: text dtype: string - name: year dtype: string - name: intelligibility dtype: float64 splits: - name: train num_bytes: 1122541753.1327753 num_examples: 780578 download_size: 801736082 dataset_size: 1122541753.1327753 configs: - config_name: default data_files: - split: train path: data/train-* ---
DTU54DL/common-native
--- annotations_creators: - expert-generated language: - en language_creators: - found license: - mit multilinguality: - monolingual paperswithcode_id: acronym-identification pretty_name: Acronym Identification Dataset size_categories: - 10K<n<100K source_datasets: - original task_categories: - token-classification task_ids: - token-classification-other-acronym-identification train-eval-index: - col_mapping: labels: tags tokens: tokens config: default splits: eval_split: test task: token-classification task_id: entity_extraction dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 - name: sentence dtype: string - name: accent dtype: string splits: - name: train num_bytes: 419902426.3910719 num_examples: 10000 - name: test num_bytes: 41430604.33704293 num_examples: 994 download_size: 440738761 dataset_size: 461333030.72811484 --- # Dataset Card for [Dataset Name] ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary [More Information Needed] ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
xed_en_fi
--- annotations_creators: - expert-generated language_creators: - found language: - en - fi license: - cc-by-4.0 multilinguality: - multilingual size_categories: - 10K<n<100K - 1K<n<10K source_datasets: - extended|other-OpenSubtitles2016 task_categories: - text-classification task_ids: - intent-classification - multi-class-classification - multi-label-classification - sentiment-classification paperswithcode_id: xed pretty_name: XedEnglishFinnish dataset_info: - config_name: en_annotated features: - name: sentence dtype: string - name: labels sequence: class_label: names: '0': neutral '1': anger '2': anticipation '3': disgust '4': fear '5': joy '6': sadness '7': surprise '8': trust splits: - name: train num_bytes: 1018485 num_examples: 17528 download_size: 2421235 dataset_size: 1018485 - config_name: en_neutral features: - name: sentence dtype: string - name: labels dtype: class_label: names: '0': neutral '1': anger '2': anticipation '3': disgust '4': fear '5': joy '6': sadness '7': surprise '8': trust splits: - name: train num_bytes: 401129 num_examples: 9675 download_size: 2421235 dataset_size: 401129 - config_name: fi_annotated features: - name: sentence dtype: string - name: labels sequence: class_label: names: '0': neutral '1': anger '2': anticipation '3': disgust '4': fear '5': joy '6': sadness '7': surprise '8': trust splits: - name: train num_bytes: 756224 num_examples: 14449 download_size: 2421235 dataset_size: 756224 - config_name: fi_neutral features: - name: sentence dtype: string - name: labels dtype: class_label: names: '0': neutral '1': anger '2': anticipation '3': disgust '4': fear '5': joy '6': sadness '7': surprise '8': trust splits: - name: train num_bytes: 427499 num_examples: 10794 download_size: 2421235 dataset_size: 427499 config_names: - en_annotated - en_neutral - fi_annotated - fi_neutral --- # Dataset Card for xed_english_finnish ## 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:** [Github](https://github.com/Helsinki-NLP/XED) - **Paper:** [Arxiv](https://arxiv.org/abs/2011.01612) - **Leaderboard:** - **Point of Contact:** ### Dataset Summary This is the XED dataset. The dataset consists of emotion annotated movie subtitles from OPUS. We use Plutchik's 8 core emotions to annotate. The data is multilabel. The original annotations have been sourced for mainly English and Finnish. For the English data we used Stanford NER (named entity recognition) (Finkel et al., 2005) to replace names and locations with the tags: [PERSON] and [LOCATION] respectively. For the Finnish data, we replaced names and locations using the Turku NER corpus (Luoma et al., 2020). ### Supported Tasks and Leaderboards Sentiment Classification, Multilabel Classification, Multilabel Classification, Intent Classification ### Languages English, Finnish ## Dataset Structure ### Data Instances ``` { "sentence": "A confession that you hired [PERSON] ... and are responsible for my father's murder." "labels": [1, 6] # anger, sadness } ``` ### Data Fields - sentence: a line from the dataset - labels: labels corresponding to the emotion as an integer Where the number indicates the emotion in ascending alphabetical order: anger:1, anticipation:2, disgust:3, fear:4, joy:5, sadness:6, surprise:7, trust:8, with neutral:0 where applicable. ### Data Splits For English: Number of unique data points: 17528 ('en_annotated' config) + 9675 ('en_neutral' config) Number of emotions: 8 (+neutral) For Finnish: Number of unique data points: 14449 ('fi_annotated' config) + 10794 ('fi_neutral' config) Number of emotions: 8 (+neutral) ## 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 License: Creative Commons Attribution 4.0 International License (CC-BY) ### Citation Information @inproceedings{ohman2020xed, title={XED: A Multilingual Dataset for Sentiment Analysis and Emotion Detection}, author={{\"O}hman, Emily and P{\`a}mies, Marc and Kajava, Kaisla and Tiedemann, J{\"o}rg}, booktitle={The 28th International Conference on Computational Linguistics (COLING 2020)}, year={2020} } ### Contributions Thanks to [@lhoestq](https://github.com/lhoestq), [@harshalmittal4](https://github.com/harshalmittal4) for adding this dataset.
open-llm-leaderboard/details_JunchengXie__zephyr-7b-beta-gpt-4-80k
--- pretty_name: Evaluation run of JunchengXie/zephyr-7b-beta-gpt-4-80k dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [JunchengXie/zephyr-7b-beta-gpt-4-80k](https://huggingface.co/JunchengXie/zephyr-7b-beta-gpt-4-80k)\ \ 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_JunchengXie__zephyr-7b-beta-gpt-4-80k\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-27T23:53:43.783934](https://huggingface.co/datasets/open-llm-leaderboard/details_JunchengXie__zephyr-7b-beta-gpt-4-80k/blob/main/results_2024-03-27T23-53-43.783934.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\": 0.602574862684413,\n\ \ \"acc_stderr\": 0.03340581138036985,\n \"acc_norm\": 0.6098452767259759,\n\ \ \"acc_norm_stderr\": 0.0341057144449039,\n \"mc1\": 0.4186046511627907,\n\ \ \"mc1_stderr\": 0.01727001528447685,\n \"mc2\": 0.584043219666108,\n\ \ \"mc2_stderr\": 0.015523976744619418\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5802047781569966,\n \"acc_stderr\": 0.014422181226303026,\n\ \ \"acc_norm\": 0.6083617747440273,\n \"acc_norm_stderr\": 0.014264122124938213\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5879306910973909,\n\ \ \"acc_stderr\": 0.004912015369160072,\n \"acc_norm\": 0.7907787293367855,\n\ \ \"acc_norm_stderr\": 0.004059213774735556\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.6074074074074074,\n\ \ \"acc_stderr\": 0.04218506215368881,\n \"acc_norm\": 0.6074074074074074,\n\ \ \"acc_norm_stderr\": 0.04218506215368881\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6381578947368421,\n \"acc_stderr\": 0.03910525752849724,\n\ \ \"acc_norm\": 0.6381578947368421,\n \"acc_norm_stderr\": 0.03910525752849724\n\ \ },\n \"harness|hendrycksTest-business_ethics|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-clinical_knowledge|5\"\ : {\n \"acc\": 0.6792452830188679,\n \"acc_stderr\": 0.028727502957880267,\n\ \ \"acc_norm\": 0.6792452830188679,\n \"acc_norm_stderr\": 0.028727502957880267\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7152777777777778,\n\ \ \"acc_stderr\": 0.037738099906869334,\n \"acc_norm\": 0.7152777777777778,\n\ \ \"acc_norm_stderr\": 0.037738099906869334\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\"\ : 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \"acc_norm\": 0.5,\n\ \ \"acc_norm_stderr\": 0.050251890762960605\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.04878317312145633,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.04878317312145633\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6127167630057804,\n\ \ \"acc_stderr\": 0.03714325906302065,\n \"acc_norm\": 0.6127167630057804,\n\ \ \"acc_norm_stderr\": 0.03714325906302065\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.43137254901960786,\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\":\ \ 0.72,\n \"acc_stderr\": 0.04512608598542129,\n \"acc_norm\": 0.72,\n\ \ \"acc_norm_stderr\": 0.04512608598542129\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5191489361702127,\n \"acc_stderr\": 0.03266204299064678,\n\ \ \"acc_norm\": 0.5191489361702127,\n \"acc_norm_stderr\": 0.03266204299064678\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4298245614035088,\n\ \ \"acc_stderr\": 0.04657047260594962,\n \"acc_norm\": 0.4298245614035088,\n\ \ \"acc_norm_stderr\": 0.04657047260594962\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5448275862068965,\n \"acc_stderr\": 0.04149886942192117,\n\ \ \"acc_norm\": 0.5448275862068965,\n \"acc_norm_stderr\": 0.04149886942192117\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.38095238095238093,\n \"acc_stderr\": 0.0250107491161376,\n \"\ acc_norm\": 0.38095238095238093,\n \"acc_norm_stderr\": 0.0250107491161376\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.373015873015873,\n\ \ \"acc_stderr\": 0.04325506042017086,\n \"acc_norm\": 0.373015873015873,\n\ \ \"acc_norm_stderr\": 0.04325506042017086\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \ \ \"acc_norm\": 0.44,\n \"acc_norm_stderr\": 0.04988876515698589\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7677419354838709,\n\ \ \"acc_stderr\": 0.024022256130308235,\n \"acc_norm\": 0.7677419354838709,\n\ \ \"acc_norm_stderr\": 0.024022256130308235\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.47783251231527096,\n \"acc_stderr\": 0.03514528562175008,\n\ \ \"acc_norm\": 0.47783251231527096,\n \"acc_norm_stderr\": 0.03514528562175008\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.64,\n \"acc_stderr\": 0.04824181513244218,\n \"acc_norm\"\ : 0.64,\n \"acc_norm_stderr\": 0.04824181513244218\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7212121212121212,\n \"acc_stderr\": 0.03501438706296781,\n\ \ \"acc_norm\": 0.7212121212121212,\n \"acc_norm_stderr\": 0.03501438706296781\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7272727272727273,\n \"acc_stderr\": 0.03173071239071724,\n \"\ acc_norm\": 0.7272727272727273,\n \"acc_norm_stderr\": 0.03173071239071724\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8341968911917098,\n \"acc_stderr\": 0.026839845022314415,\n\ \ \"acc_norm\": 0.8341968911917098,\n \"acc_norm_stderr\": 0.026839845022314415\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6,\n \"acc_stderr\": 0.024838811988033165,\n \"acc_norm\"\ : 0.6,\n \"acc_norm_stderr\": 0.024838811988033165\n },\n \"harness|hendrycksTest-high_school_mathematics|5\"\ : {\n \"acc\": 0.35185185185185186,\n \"acc_stderr\": 0.029116617606083004,\n\ \ \"acc_norm\": 0.35185185185185186,\n \"acc_norm_stderr\": 0.029116617606083004\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.7016806722689075,\n \"acc_stderr\": 0.02971914287634286,\n \ \ \"acc_norm\": 0.7016806722689075,\n \"acc_norm_stderr\": 0.02971914287634286\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.33774834437086093,\n \"acc_stderr\": 0.03861557546255169,\n \"\ acc_norm\": 0.33774834437086093,\n \"acc_norm_stderr\": 0.03861557546255169\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8055045871559633,\n \"acc_stderr\": 0.016970289090458033,\n \"\ acc_norm\": 0.8055045871559633,\n \"acc_norm_stderr\": 0.016970289090458033\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5601851851851852,\n \"acc_stderr\": 0.0338517797604481,\n \"acc_norm\"\ : 0.5601851851851852,\n \"acc_norm_stderr\": 0.0338517797604481\n },\n\ \ \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\": 0.7549019607843137,\n\ \ \"acc_stderr\": 0.030190282453501943,\n \"acc_norm\": 0.7549019607843137,\n\ \ \"acc_norm_stderr\": 0.030190282453501943\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\ : {\n \"acc\": 0.7046413502109705,\n \"acc_stderr\": 0.02969633871342288,\n\ \ \"acc_norm\": 0.7046413502109705,\n \"acc_norm_stderr\": 0.02969633871342288\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6143497757847534,\n\ \ \"acc_stderr\": 0.03266842214289201,\n \"acc_norm\": 0.6143497757847534,\n\ \ \"acc_norm_stderr\": 0.03266842214289201\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7175572519083969,\n \"acc_stderr\": 0.03948406125768361,\n\ \ \"acc_norm\": 0.7175572519083969,\n \"acc_norm_stderr\": 0.03948406125768361\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.71900826446281,\n \"acc_stderr\": 0.04103203830514512,\n \"acc_norm\"\ : 0.71900826446281,\n \"acc_norm_stderr\": 0.04103203830514512\n },\n\ \ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.75,\n \ \ \"acc_stderr\": 0.04186091791394607,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04186091791394607\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.6809815950920245,\n \"acc_stderr\": 0.03661997551073836,\n\ \ \"acc_norm\": 0.6809815950920245,\n \"acc_norm_stderr\": 0.03661997551073836\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.38392857142857145,\n\ \ \"acc_stderr\": 0.04616143075028547,\n \"acc_norm\": 0.38392857142857145,\n\ \ \"acc_norm_stderr\": 0.04616143075028547\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7281553398058253,\n \"acc_stderr\": 0.044052680241409216,\n\ \ \"acc_norm\": 0.7281553398058253,\n \"acc_norm_stderr\": 0.044052680241409216\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8205128205128205,\n\ \ \"acc_stderr\": 0.02514093595033543,\n \"acc_norm\": 0.8205128205128205,\n\ \ \"acc_norm_stderr\": 0.02514093595033543\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\": 0.7777777777777778,\n\ \ \"acc_stderr\": 0.014866821664709583,\n \"acc_norm\": 0.7777777777777778,\n\ \ \"acc_norm_stderr\": 0.014866821664709583\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6907514450867052,\n \"acc_stderr\": 0.02488314057007176,\n\ \ \"acc_norm\": 0.6907514450867052,\n \"acc_norm_stderr\": 0.02488314057007176\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.36201117318435755,\n\ \ \"acc_stderr\": 0.016073067350153087,\n \"acc_norm\": 0.36201117318435755,\n\ \ \"acc_norm_stderr\": 0.016073067350153087\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.6862745098039216,\n \"acc_stderr\": 0.02656892101545715,\n\ \ \"acc_norm\": 0.6862745098039216,\n \"acc_norm_stderr\": 0.02656892101545715\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.6752411575562701,\n\ \ \"acc_stderr\": 0.026596782287697043,\n \"acc_norm\": 0.6752411575562701,\n\ \ \"acc_norm_stderr\": 0.026596782287697043\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.6728395061728395,\n \"acc_stderr\": 0.026105673861409825,\n\ \ \"acc_norm\": 0.6728395061728395,\n \"acc_norm_stderr\": 0.026105673861409825\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4326241134751773,\n \"acc_stderr\": 0.02955545423677885,\n \ \ \"acc_norm\": 0.4326241134751773,\n \"acc_norm_stderr\": 0.02955545423677885\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.41264667535853977,\n\ \ \"acc_stderr\": 0.012573836633799016,\n \"acc_norm\": 0.41264667535853977,\n\ \ \"acc_norm_stderr\": 0.012573836633799016\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6691176470588235,\n \"acc_stderr\": 0.02858270975389845,\n\ \ \"acc_norm\": 0.6691176470588235,\n \"acc_norm_stderr\": 0.02858270975389845\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6356209150326797,\n \"acc_stderr\": 0.019469518221573695,\n \ \ \"acc_norm\": 0.6356209150326797,\n \"acc_norm_stderr\": 0.019469518221573695\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6363636363636364,\n\ \ \"acc_stderr\": 0.046075820907199756,\n \"acc_norm\": 0.6363636363636364,\n\ \ \"acc_norm_stderr\": 0.046075820907199756\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.6530612244897959,\n \"acc_stderr\": 0.030472526026726496,\n\ \ \"acc_norm\": 0.6530612244897959,\n \"acc_norm_stderr\": 0.030472526026726496\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7910447761194029,\n\ \ \"acc_stderr\": 0.028748298931728655,\n \"acc_norm\": 0.7910447761194029,\n\ \ \"acc_norm_stderr\": 0.028748298931728655\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.79,\n \"acc_stderr\": 0.040936018074033256,\n \ \ \"acc_norm\": 0.79,\n \"acc_norm_stderr\": 0.040936018074033256\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.4939759036144578,\n\ \ \"acc_stderr\": 0.03892212195333045,\n \"acc_norm\": 0.4939759036144578,\n\ \ \"acc_norm_stderr\": 0.03892212195333045\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8011695906432749,\n \"acc_stderr\": 0.030611116557432528,\n\ \ \"acc_norm\": 0.8011695906432749,\n \"acc_norm_stderr\": 0.030611116557432528\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.4186046511627907,\n\ \ \"mc1_stderr\": 0.01727001528447685,\n \"mc2\": 0.584043219666108,\n\ \ \"mc2_stderr\": 0.015523976744619418\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7403314917127072,\n \"acc_stderr\": 0.012322700705552669\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.266868840030326,\n \ \ \"acc_stderr\": 0.012183780551887962\n }\n}\n```" repo_url: https://huggingface.co/JunchengXie/zephyr-7b-beta-gpt-4-80k leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|arc:challenge|25_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-27T23-53-43.783934.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|gsm8k|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hellaswag|10_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-27T23-53-43.783934.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-management|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-27T23-53-43.783934.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|truthfulqa:mc|0_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-27T23-53-43.783934.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_27T23_53_43.783934 path: - '**/details_harness|winogrande|5_2024-03-27T23-53-43.783934.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-27T23-53-43.783934.parquet' - config_name: results data_files: - split: 2024_03_27T23_53_43.783934 path: - results_2024-03-27T23-53-43.783934.parquet - split: latest path: - results_2024-03-27T23-53-43.783934.parquet --- # Dataset Card for Evaluation run of JunchengXie/zephyr-7b-beta-gpt-4-80k <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [JunchengXie/zephyr-7b-beta-gpt-4-80k](https://huggingface.co/JunchengXie/zephyr-7b-beta-gpt-4-80k) 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_JunchengXie__zephyr-7b-beta-gpt-4-80k", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-27T23:53:43.783934](https://huggingface.co/datasets/open-llm-leaderboard/details_JunchengXie__zephyr-7b-beta-gpt-4-80k/blob/main/results_2024-03-27T23-53-43.783934.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": 0.602574862684413, "acc_stderr": 0.03340581138036985, "acc_norm": 0.6098452767259759, "acc_norm_stderr": 0.0341057144449039, "mc1": 0.4186046511627907, "mc1_stderr": 0.01727001528447685, "mc2": 0.584043219666108, "mc2_stderr": 0.015523976744619418 }, "harness|arc:challenge|25": { "acc": 0.5802047781569966, "acc_stderr": 0.014422181226303026, "acc_norm": 0.6083617747440273, "acc_norm_stderr": 0.014264122124938213 }, "harness|hellaswag|10": { "acc": 0.5879306910973909, "acc_stderr": 0.004912015369160072, "acc_norm": 0.7907787293367855, "acc_norm_stderr": 0.004059213774735556 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6074074074074074, "acc_stderr": 0.04218506215368881, "acc_norm": 0.6074074074074074, "acc_norm_stderr": 0.04218506215368881 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6381578947368421, "acc_stderr": 0.03910525752849724, "acc_norm": 0.6381578947368421, "acc_norm_stderr": 0.03910525752849724 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6792452830188679, "acc_stderr": 0.028727502957880267, "acc_norm": 0.6792452830188679, "acc_norm_stderr": 0.028727502957880267 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7152777777777778, "acc_stderr": 0.037738099906869334, "acc_norm": 0.7152777777777778, "acc_norm_stderr": 0.037738099906869334 }, "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": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.38, "acc_stderr": 0.04878317312145633, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145633 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6127167630057804, "acc_stderr": 0.03714325906302065, "acc_norm": 0.6127167630057804, "acc_norm_stderr": 0.03714325906302065 }, "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": 0.72, "acc_stderr": 0.04512608598542129, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542129 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5191489361702127, "acc_stderr": 0.03266204299064678, "acc_norm": 0.5191489361702127, "acc_norm_stderr": 0.03266204299064678 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4298245614035088, "acc_stderr": 0.04657047260594962, "acc_norm": 0.4298245614035088, "acc_norm_stderr": 0.04657047260594962 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5448275862068965, "acc_stderr": 0.04149886942192117, "acc_norm": 0.5448275862068965, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.38095238095238093, "acc_stderr": 0.0250107491161376, "acc_norm": 0.38095238095238093, "acc_norm_stderr": 0.0250107491161376 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.373015873015873, "acc_stderr": 0.04325506042017086, "acc_norm": 0.373015873015873, "acc_norm_stderr": 0.04325506042017086 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7677419354838709, "acc_stderr": 0.024022256130308235, "acc_norm": 0.7677419354838709, "acc_norm_stderr": 0.024022256130308235 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.47783251231527096, "acc_stderr": 0.03514528562175008, "acc_norm": 0.47783251231527096, "acc_norm_stderr": 0.03514528562175008 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7212121212121212, "acc_stderr": 0.03501438706296781, "acc_norm": 0.7212121212121212, "acc_norm_stderr": 0.03501438706296781 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7272727272727273, "acc_stderr": 0.03173071239071724, "acc_norm": 0.7272727272727273, "acc_norm_stderr": 0.03173071239071724 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8341968911917098, "acc_stderr": 0.026839845022314415, "acc_norm": 0.8341968911917098, "acc_norm_stderr": 0.026839845022314415 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6, "acc_stderr": 0.024838811988033165, "acc_norm": 0.6, "acc_norm_stderr": 0.024838811988033165 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.35185185185185186, "acc_stderr": 0.029116617606083004, "acc_norm": 0.35185185185185186, "acc_norm_stderr": 0.029116617606083004 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.7016806722689075, "acc_stderr": 0.02971914287634286, "acc_norm": 0.7016806722689075, "acc_norm_stderr": 0.02971914287634286 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.33774834437086093, "acc_stderr": 0.03861557546255169, "acc_norm": 0.33774834437086093, "acc_norm_stderr": 0.03861557546255169 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8055045871559633, "acc_stderr": 0.016970289090458033, "acc_norm": 0.8055045871559633, "acc_norm_stderr": 0.016970289090458033 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5601851851851852, "acc_stderr": 0.0338517797604481, "acc_norm": 0.5601851851851852, "acc_norm_stderr": 0.0338517797604481 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.7549019607843137, "acc_stderr": 0.030190282453501943, "acc_norm": 0.7549019607843137, "acc_norm_stderr": 0.030190282453501943 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7046413502109705, "acc_stderr": 0.02969633871342288, "acc_norm": 0.7046413502109705, "acc_norm_stderr": 0.02969633871342288 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6143497757847534, "acc_stderr": 0.03266842214289201, "acc_norm": 0.6143497757847534, "acc_norm_stderr": 0.03266842214289201 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7175572519083969, "acc_stderr": 0.03948406125768361, "acc_norm": 0.7175572519083969, "acc_norm_stderr": 0.03948406125768361 }, "harness|hendrycksTest-international_law|5": { "acc": 0.71900826446281, "acc_stderr": 0.04103203830514512, "acc_norm": 0.71900826446281, "acc_norm_stderr": 0.04103203830514512 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.75, "acc_stderr": 0.04186091791394607, "acc_norm": 0.75, "acc_norm_stderr": 0.04186091791394607 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.6809815950920245, "acc_stderr": 0.03661997551073836, "acc_norm": 0.6809815950920245, "acc_norm_stderr": 0.03661997551073836 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.38392857142857145, "acc_stderr": 0.04616143075028547, "acc_norm": 0.38392857142857145, "acc_norm_stderr": 0.04616143075028547 }, "harness|hendrycksTest-management|5": { "acc": 0.7281553398058253, "acc_stderr": 0.044052680241409216, "acc_norm": 0.7281553398058253, "acc_norm_stderr": 0.044052680241409216 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8205128205128205, "acc_stderr": 0.02514093595033543, "acc_norm": 0.8205128205128205, "acc_norm_stderr": 0.02514093595033543 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.7777777777777778, "acc_stderr": 0.014866821664709583, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.014866821664709583 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.6907514450867052, "acc_stderr": 0.02488314057007176, "acc_norm": 0.6907514450867052, "acc_norm_stderr": 0.02488314057007176 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.36201117318435755, "acc_stderr": 0.016073067350153087, "acc_norm": 0.36201117318435755, "acc_norm_stderr": 0.016073067350153087 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.6862745098039216, "acc_stderr": 0.02656892101545715, "acc_norm": 0.6862745098039216, "acc_norm_stderr": 0.02656892101545715 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.6752411575562701, "acc_stderr": 0.026596782287697043, "acc_norm": 0.6752411575562701, "acc_norm_stderr": 0.026596782287697043 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.6728395061728395, "acc_stderr": 0.026105673861409825, "acc_norm": 0.6728395061728395, "acc_norm_stderr": 0.026105673861409825 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4326241134751773, "acc_stderr": 0.02955545423677885, "acc_norm": 0.4326241134751773, "acc_norm_stderr": 0.02955545423677885 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.41264667535853977, "acc_stderr": 0.012573836633799016, "acc_norm": 0.41264667535853977, "acc_norm_stderr": 0.012573836633799016 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6691176470588235, "acc_stderr": 0.02858270975389845, "acc_norm": 0.6691176470588235, "acc_norm_stderr": 0.02858270975389845 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6356209150326797, "acc_stderr": 0.019469518221573695, "acc_norm": 0.6356209150326797, "acc_norm_stderr": 0.019469518221573695 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6363636363636364, "acc_stderr": 0.046075820907199756, "acc_norm": 0.6363636363636364, "acc_norm_stderr": 0.046075820907199756 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.6530612244897959, "acc_stderr": 0.030472526026726496, "acc_norm": 0.6530612244897959, "acc_norm_stderr": 0.030472526026726496 }, "harness|hendrycksTest-sociology|5": { "acc": 0.7910447761194029, "acc_stderr": 0.028748298931728655, "acc_norm": 0.7910447761194029, "acc_norm_stderr": 0.028748298931728655 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.79, "acc_stderr": 0.040936018074033256, "acc_norm": 0.79, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-virology|5": { "acc": 0.4939759036144578, "acc_stderr": 0.03892212195333045, "acc_norm": 0.4939759036144578, "acc_norm_stderr": 0.03892212195333045 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8011695906432749, "acc_stderr": 0.030611116557432528, "acc_norm": 0.8011695906432749, "acc_norm_stderr": 0.030611116557432528 }, "harness|truthfulqa:mc|0": { "mc1": 0.4186046511627907, "mc1_stderr": 0.01727001528447685, "mc2": 0.584043219666108, "mc2_stderr": 0.015523976744619418 }, "harness|winogrande|5": { "acc": 0.7403314917127072, "acc_stderr": 0.012322700705552669 }, "harness|gsm8k|5": { "acc": 0.266868840030326, "acc_stderr": 0.012183780551887962 } } ``` ## 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]
Kimata/GPT_Driver_dataset
--- dataset_info: features: - name: messages list: - name: role dtype: string - name: content dtype: string splits: - name: train num_bytes: 49269209 num_examples: 23388 - name: test num_bytes: 10693369 num_examples: 5119 download_size: 7321936 dataset_size: 59962578 --- # Dataset Card for "GPT_Driver_dataset" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
kghanlon/processed_SOTUs_parliament_texts
--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 3612825824 num_examples: 2155624 download_size: 1049504347 dataset_size: 3612825824 configs: - config_name: default data_files: - split: train path: data/train-* ---
skvarre/hogskoleprovet-ord-3k
--- dataset_info: features: - name: metadata dtype: string - name: text sequence: string splits: - name: train num_bytes: 262260 num_examples: 3002 download_size: 99081 dataset_size: 262260 configs: - config_name: default data_files: - split: train path: data/train-* ---
RIW/small-coco-wm_1_3
--- dataset_info: features: - name: image dtype: image - name: caption dtype: string - name: url dtype: string - name: key dtype: string - name: status dtype: string - name: error_message dtype: 'null' - name: width dtype: int64 - name: height dtype: int64 - name: original_width dtype: int64 - name: original_height dtype: int64 - name: exif dtype: string - name: sha256 dtype: string splits: - name: train num_bytes: 1886028576.233 num_examples: 9989 - name: validation num_bytes: 1865114007.604 num_examples: 9993 download_size: 888826269 dataset_size: 3751142583.837 --- # Dataset Card for "small-coco-wm_1_3" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
warleagle/1t_chat_bot_data
--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 890558 num_examples: 2083 download_size: 398939 dataset_size: 890558 --- # Dataset Card for "1t_chat_bot_data" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
tyzhu/find_last_sent_train_50_eval_10_baseline
--- 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: 80962 num_examples: 50 - name: validation num_bytes: 15247 num_examples: 10 download_size: 0 dataset_size: 96209 --- # Dataset Card for "find_last_sent_train_50_eval_10_baseline" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ximdeew/hiho_audio_test
--- dataset_info: features: - name: audio dtype: audio - name: sentence dtype: string splits: - name: train num_bytes: 185373604.0 num_examples: 149 download_size: 174626524 dataset_size: 185373604.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
lihongze8/instruc_1M
--- license: llama2 ---
heliosprime/twitter_dataset_1713193258
--- 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: 16516 num_examples: 45 download_size: 16801 dataset_size: 16516 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "twitter_dataset_1713193258" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
UrbanSyn/UrbanSyn
--- license: cc-by-sa-4.0 task_categories: - object-detection - image-segmentation - depth-estimation language: - en tags: - Urban Scenario - Autonomous Driving - Synthethic data size_categories: - 1K<n<10K pretty_name: UrbanSyn --- <img src="front_urbanSyn.png" width=100% /> # UrbanSyn Dataset UrbanSyn is an open synthetic dataset featuring photorealistic driving scenes. It contains ground-truth annotations for semantic segmentation, scene depth, panoptic instance segmentation, and 2-D bounding boxes. Website [https://urbansyn.org](https://urbansyn.org) ## Overview UrbanSyn is a diverse, compact, and photorealistic dataset that provides more than 7.5k synthetic annotated images. It was born to address the synth-to-real domain gap, contributing to unprecedented synthetic-only baselines used by domain adaptation (DA) methods. **- Reduce the synth-to-real domain gap** UrbanSyn dataset helps to reduce the domain gap by contributing to unprecedented synthetic-only baselines used by domain adaptation (DA) methods. **- Ground-truth annotations** UrbanSyn comes with photorealistic color images, per-pixel semantic segmentation, depth, instance panoptic segmentation, and 2-D bounding boxes. **- Open for research and commercial purposes** UrbanSyn may be used for research and commercial purposes. It is released publicly under the Creative Commons Attribution-Commercial-ShareAlike 4.0 license. **- High-degree of photorealism** UrbanSyn features highly realistic and curated driving scenarios leveraging procedurally-generated content and high-quality curated assets. To achieve UrbanSyn photorealism we leverage industry-standard unbiased path-tracing and AI-based denoising techniques. ## White Paper **[[Arxiv]](https://arxiv.org/abs/2312.12176)** When using or referring to the UrbanSyn dataset in your research, please cite our white paper: ```BibTeX @misc{gomez2023one, title={All for One, and One for All: UrbanSyn Dataset, the third Musketeer of Synthetic Driving Scenes}, author={Jose L. Gómez and Manuel Silva and Antonio Seoane and Agnès Borrás and Mario Noriega and Germán Ros and Jose A. Iglesias-Guitian and Antonio M. López}, year={2023}, eprint={2312.12176}, archivePrefix={arXiv}, primaryClass={cs.CV} } ``` ## Terms of Use The UrbanSyn Dataset is provided by the Computer Vision Center (UAB) and CITIC (University of A Coruña). UrbanSyn may be used for research and commercial purposes, and it is subject to the Creative Commons Attribution-Commercial-ShareAlike 4.0. A summary of the CC-BY-SA 4.0 licensing terms can be found **[[here]](https://creativecommons.org/licenses/by-sa/4.0/deed.en)**. Due to constraints from our asset providers for UrbanSyn, we prohibit the use of generative AI technologies for reverse engineering any assets or creating content for stock media platforms based on the UrbanSyn dataset. While we strive to generate precise data, all information is presented 'as is' without any express or implied warranties. We explicitly disclaim all representations and warranties regarding the validity, scope, accuracy, completeness, safety, or utility of the licensed content, including any implied warranties of merchantability, fitness for a particular purpose, or otherwise. ## Acknowledgements Funded by Grant agreement PID2020-115734RB-C21 "SSL-ADA" and Grant agreement PID2020-115734RB-C22 "PGAS-ADA" <img src="MICINN_Gob_AEI_1.jpg" width="300" /> ## For more information about our team members and how to contact us, visit our website [https://urbansyn.org](https://urbansyn.org) ## Folder structure and content - ```rgb```: contains RGB images with a resolution of 2048x1024 in PNG format. - ```ss and ss_colour``` : contains the pixel-level semantic segmentation labels in grayscale (value = Class ID) and colour (value = Class RGB) respectively in PNG format. We follow the 19 training classes defined on Cityscapes: | name | trainId | color | |----------------------|---------|-----------------| | 'road' | 0 | (128, 64,128) | | 'sidewalk' | 1 | (244, 35,232) | | 'building' | 2 | ( 70, 70, 70) | | 'wall' | 3 | (102,102,156) | | 'fence' | 4 | (190,153,153) | | 'pole' | 5 | (153,153,153) | | 'traffic light' | 6 | (250,170, 30) | | 'traffic sign' | 7 | (220,220, 0) | | 'vegetation' | 8 | (107,142, 35) | | 'terrain' | 9 | (152,251,152) | | 'sky' | 10 | ( 70,130,180) | | 'person' | 11 | (220, 20, 60) | | 'rider' | 12 | (255, 0, 0) | | 'car' | 13 | ( 0, 0,142) | | 'truck' | 14 | ( 0, 0, 70) | | 'bus' | 15 | ( 0, 60,100) | | 'train' | 16 | ( 0, 80,100) | | 'motorcycle' | 17 | ( 0, 0,230) | | 'bicycle' | 18 | (119, 11, 32) | | 'unlabeled' | 19 | ( 0, 0, 0) | - ```panoptic```: contains the instance segmentation of the dynamic objects of the image in PNG format. Each instance is codified using the RGB channels, where RG corresponds to the instance number and B to the class ID. Dynamic objects are Person, Rider, Car, Truck, Bus, Train, Motorcycle and Bicycle. - ```bbox2D```: contains the 2D bounding boxes and Instances information for all the dynamic objects in the image up to 110 meters of distance from the camera and bigger than 150 pixels. We provide the annotations in a json file with the next structure: - bbox: provides the bounding box size determined by the top left corner (xMin, yMin) and Bottom right corner (xMax, YMax). - color: corresponds to the colour of the instance in the panoptic instance segmentation map inside panoptic folder. - label: defines the class name - occlusion_percentage: provides the occlusion percentatge of the object. Being 0 not occluded and 100 fully occluded. - ```depth```: contains the depth map of the image in EXR format. ## Download locally with huggingface_hub library - [Install huggingface_hub library](https://huggingface.co/docs/huggingface_hub/installation) - You can download the dataset on Python this way: ``` from huggingface_hub import snapshot_download ``` ``` snapshot_download(repo_id="UrbanSyn/UrbanSyn", repo_type="dataset") ``` - More information about how to download and additional options can be found [here](https://huggingface.co/docs/huggingface_hub/guides/download)
zolak/twitter_dataset_1712986565
--- 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: 4695489 num_examples: 13504 download_size: 2371994 dataset_size: 4695489 configs: - config_name: default data_files: - split: train path: data/train-* ---
iambestfeed/vnexpress_cluster_subset
--- dataset_info: features: - name: label dtype: string - name: text dtype: string - name: embeddings sequence: float64 - name: label-mapping dtype: int64 splits: - name: train num_bytes: 63510854 num_examples: 10000 download_size: 65591860 dataset_size: 63510854 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_mychen76__openmixtral-6x7b-v2
--- pretty_name: Evaluation run of mychen76/openmixtral-6x7b-v2 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mychen76/openmixtral-6x7b-v2](https://huggingface.co/mychen76/openmixtral-6x7b-v2)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_mychen76__openmixtral-6x7b-v2\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-22T03:38:21.830640](https://huggingface.co/datasets/open-llm-leaderboard/details_mychen76__openmixtral-6x7b-v2/blob/main/results_2024-03-22T03-38-21.830640.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\": 0.6549214653780983,\n\ \ \"acc_stderr\": 0.03192694712071088,\n \"acc_norm\": 0.6553162947426028,\n\ \ \"acc_norm_stderr\": 0.03257645266665692,\n \"mc1\": 0.47368421052631576,\n\ \ \"mc1_stderr\": 0.017479241161975526,\n \"mc2\": 0.651312479462047,\n\ \ \"mc2_stderr\": 0.015362786449252212\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6604095563139932,\n \"acc_stderr\": 0.013839039762820167,\n\ \ \"acc_norm\": 0.6851535836177475,\n \"acc_norm_stderr\": 0.013572657703084948\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6938856801433977,\n\ \ \"acc_stderr\": 0.00459935892090954,\n \"acc_norm\": 0.8674566819358693,\n\ \ \"acc_norm_stderr\": 0.003383875172670026\n },\n \"harness|hendrycksTest-abstract_algebra|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-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\": 0.7171052631578947,\n \"acc_stderr\": 0.03665349695640767,\n\ \ \"acc_norm\": 0.7171052631578947,\n \"acc_norm_stderr\": 0.03665349695640767\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.65,\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\": 0.027834912527544067,\n\ \ \"acc_norm\": 0.7132075471698113,\n \"acc_norm_stderr\": 0.027834912527544067\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\": 0.49,\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\": 0.33,\n \"acc_stderr\": 0.04725815626252604,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252604\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6647398843930635,\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\": 0.4215686274509804,\n \"acc_stderr\": 0.049135952012744975,\n\ \ \"acc_norm\": 0.4215686274509804,\n \"acc_norm_stderr\": 0.049135952012744975\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.76,\n \"acc_stderr\": 0.04292346959909282,\n \"acc_norm\": 0.76,\n\ \ \"acc_norm_stderr\": 0.04292346959909282\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5829787234042553,\n \"acc_stderr\": 0.03223276266711712,\n\ \ \"acc_norm\": 0.5829787234042553,\n \"acc_norm_stderr\": 0.03223276266711712\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5,\n\ \ \"acc_stderr\": 0.047036043419179864,\n \"acc_norm\": 0.5,\n \ \ \"acc_norm_stderr\": 0.047036043419179864\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5724137931034483,\n \"acc_stderr\": 0.04122737111370333,\n\ \ \"acc_norm\": 0.5724137931034483,\n \"acc_norm_stderr\": 0.04122737111370333\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.41005291005291006,\n \"acc_stderr\": 0.025331202438944437,\n \"\ acc_norm\": 0.41005291005291006,\n \"acc_norm_stderr\": 0.025331202438944437\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.48412698412698413,\n\ \ \"acc_stderr\": 0.04469881854072606,\n \"acc_norm\": 0.48412698412698413,\n\ \ \"acc_norm_stderr\": 0.04469881854072606\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.047258156262526045\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\"\ : 0.7903225806451613,\n \"acc_stderr\": 0.023157879349083525,\n \"\ acc_norm\": 0.7903225806451613,\n \"acc_norm_stderr\": 0.023157879349083525\n\ \ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\ : 0.49261083743842365,\n \"acc_stderr\": 0.03517603540361008,\n \"\ acc_norm\": 0.49261083743842365,\n \"acc_norm_stderr\": 0.03517603540361008\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.71,\n \"acc_stderr\": 0.045604802157206845,\n \"acc_norm\"\ : 0.71,\n \"acc_norm_stderr\": 0.045604802157206845\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7818181818181819,\n \"acc_stderr\": 0.03225078108306289,\n\ \ \"acc_norm\": 0.7818181818181819,\n \"acc_norm_stderr\": 0.03225078108306289\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7878787878787878,\n \"acc_stderr\": 0.029126522834586815,\n \"\ acc_norm\": 0.7878787878787878,\n \"acc_norm_stderr\": 0.029126522834586815\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.9015544041450777,\n \"acc_stderr\": 0.02150024957603348,\n\ \ \"acc_norm\": 0.9015544041450777,\n \"acc_norm_stderr\": 0.02150024957603348\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6692307692307692,\n \"acc_stderr\": 0.023854795680971114,\n\ \ \"acc_norm\": 0.6692307692307692,\n \"acc_norm_stderr\": 0.023854795680971114\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.3111111111111111,\n \"acc_stderr\": 0.02822644674968351,\n \ \ \"acc_norm\": 0.3111111111111111,\n \"acc_norm_stderr\": 0.02822644674968351\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6890756302521008,\n \"acc_stderr\": 0.030066761582977927,\n\ \ \"acc_norm\": 0.6890756302521008,\n \"acc_norm_stderr\": 0.030066761582977927\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.33774834437086093,\n \"acc_stderr\": 0.03861557546255169,\n \"\ acc_norm\": 0.33774834437086093,\n \"acc_norm_stderr\": 0.03861557546255169\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8532110091743119,\n \"acc_stderr\": 0.015173141845126243,\n \"\ acc_norm\": 0.8532110091743119,\n \"acc_norm_stderr\": 0.015173141845126243\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5277777777777778,\n \"acc_stderr\": 0.0340470532865388,\n \"acc_norm\"\ : 0.5277777777777778,\n \"acc_norm_stderr\": 0.0340470532865388\n },\n\ \ \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\": 0.8529411764705882,\n\ \ \"acc_stderr\": 0.024857478080250434,\n \"acc_norm\": 0.8529411764705882,\n\ \ \"acc_norm_stderr\": 0.024857478080250434\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\ : {\n \"acc\": 0.8143459915611815,\n \"acc_stderr\": 0.025310495376944867,\n\ \ \"acc_norm\": 0.8143459915611815,\n \"acc_norm_stderr\": 0.025310495376944867\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6905829596412556,\n\ \ \"acc_stderr\": 0.03102441174057221,\n \"acc_norm\": 0.6905829596412556,\n\ \ \"acc_norm_stderr\": 0.03102441174057221\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7709923664122137,\n \"acc_stderr\": 0.036853466317118506,\n\ \ \"acc_norm\": 0.7709923664122137,\n \"acc_norm_stderr\": 0.036853466317118506\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.8099173553719008,\n \"acc_stderr\": 0.03581796951709282,\n \"\ acc_norm\": 0.8099173553719008,\n \"acc_norm_stderr\": 0.03581796951709282\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8055555555555556,\n\ \ \"acc_stderr\": 0.038260763248848646,\n \"acc_norm\": 0.8055555555555556,\n\ \ \"acc_norm_stderr\": 0.038260763248848646\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7484662576687117,\n \"acc_stderr\": 0.03408997886857529,\n\ \ \"acc_norm\": 0.7484662576687117,\n \"acc_norm_stderr\": 0.03408997886857529\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.44642857142857145,\n\ \ \"acc_stderr\": 0.047184714852195886,\n \"acc_norm\": 0.44642857142857145,\n\ \ \"acc_norm_stderr\": 0.047184714852195886\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.8155339805825242,\n \"acc_stderr\": 0.03840423627288276,\n\ \ \"acc_norm\": 0.8155339805825242,\n \"acc_norm_stderr\": 0.03840423627288276\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\": 0.75,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8390804597701149,\n\ \ \"acc_stderr\": 0.013140225515611729,\n \"acc_norm\": 0.8390804597701149,\n\ \ \"acc_norm_stderr\": 0.013140225515611729\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7312138728323699,\n \"acc_stderr\": 0.023868003262500104,\n\ \ \"acc_norm\": 0.7312138728323699,\n \"acc_norm_stderr\": 0.023868003262500104\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.4424581005586592,\n\ \ \"acc_stderr\": 0.016611393687268577,\n \"acc_norm\": 0.4424581005586592,\n\ \ \"acc_norm_stderr\": 0.016611393687268577\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7254901960784313,\n \"acc_stderr\": 0.02555316999182652,\n\ \ \"acc_norm\": 0.7254901960784313,\n \"acc_norm_stderr\": 0.02555316999182652\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7138263665594855,\n\ \ \"acc_stderr\": 0.025670259242188926,\n \"acc_norm\": 0.7138263665594855,\n\ \ \"acc_norm_stderr\": 0.025670259242188926\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7530864197530864,\n \"acc_stderr\": 0.0239935017090421,\n\ \ \"acc_norm\": 0.7530864197530864,\n \"acc_norm_stderr\": 0.0239935017090421\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4858156028368794,\n \"acc_stderr\": 0.02981549448368206,\n \ \ \"acc_norm\": 0.4858156028368794,\n \"acc_norm_stderr\": 0.02981549448368206\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4530638852672751,\n\ \ \"acc_stderr\": 0.01271384597235898,\n \"acc_norm\": 0.4530638852672751,\n\ \ \"acc_norm_stderr\": 0.01271384597235898\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6985294117647058,\n \"acc_stderr\": 0.027875982114273168,\n\ \ \"acc_norm\": 0.6985294117647058,\n \"acc_norm_stderr\": 0.027875982114273168\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6666666666666666,\n \"acc_stderr\": 0.019070985589687495,\n \ \ \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.019070985589687495\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6636363636363637,\n\ \ \"acc_stderr\": 0.04525393596302506,\n \"acc_norm\": 0.6636363636363637,\n\ \ \"acc_norm_stderr\": 0.04525393596302506\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7142857142857143,\n \"acc_stderr\": 0.028920583220675606,\n\ \ \"acc_norm\": 0.7142857142857143,\n \"acc_norm_stderr\": 0.028920583220675606\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.845771144278607,\n\ \ \"acc_stderr\": 0.025538433368578337,\n \"acc_norm\": 0.845771144278607,\n\ \ \"acc_norm_stderr\": 0.025538433368578337\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.0358870281282637,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.0358870281282637\n },\n\ \ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.536144578313253,\n\ \ \"acc_stderr\": 0.03882310850890594,\n \"acc_norm\": 0.536144578313253,\n\ \ \"acc_norm_stderr\": 0.03882310850890594\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.029547741687640044,\n\ \ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.029547741687640044\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.47368421052631576,\n\ \ \"mc1_stderr\": 0.017479241161975526,\n \"mc2\": 0.651312479462047,\n\ \ \"mc2_stderr\": 0.015362786449252212\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7987371744277821,\n \"acc_stderr\": 0.01126851997157768\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.686125852918878,\n \ \ \"acc_stderr\": 0.012782681251053205\n }\n}\n```" repo_url: https://huggingface.co/mychen76/openmixtral-6x7b-v2 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|arc:challenge|25_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-22T03-38-21.830640.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|gsm8k|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hellaswag|10_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-22T03-38-21.830640.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-management|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-22T03-38-21.830640.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|truthfulqa:mc|0_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-22T03-38-21.830640.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_22T03_38_21.830640 path: - '**/details_harness|winogrande|5_2024-03-22T03-38-21.830640.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-22T03-38-21.830640.parquet' - config_name: results data_files: - split: 2024_03_22T03_38_21.830640 path: - results_2024-03-22T03-38-21.830640.parquet - split: latest path: - results_2024-03-22T03-38-21.830640.parquet --- # Dataset Card for Evaluation run of mychen76/openmixtral-6x7b-v2 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [mychen76/openmixtral-6x7b-v2](https://huggingface.co/mychen76/openmixtral-6x7b-v2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_mychen76__openmixtral-6x7b-v2", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-22T03:38:21.830640](https://huggingface.co/datasets/open-llm-leaderboard/details_mychen76__openmixtral-6x7b-v2/blob/main/results_2024-03-22T03-38-21.830640.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": 0.6549214653780983, "acc_stderr": 0.03192694712071088, "acc_norm": 0.6553162947426028, "acc_norm_stderr": 0.03257645266665692, "mc1": 0.47368421052631576, "mc1_stderr": 0.017479241161975526, "mc2": 0.651312479462047, "mc2_stderr": 0.015362786449252212 }, "harness|arc:challenge|25": { "acc": 0.6604095563139932, "acc_stderr": 0.013839039762820167, "acc_norm": 0.6851535836177475, "acc_norm_stderr": 0.013572657703084948 }, "harness|hellaswag|10": { "acc": 0.6938856801433977, "acc_stderr": 0.00459935892090954, "acc_norm": 0.8674566819358693, "acc_norm_stderr": 0.003383875172670026 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "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": 0.7171052631578947, "acc_stderr": 0.03665349695640767, "acc_norm": 0.7171052631578947, "acc_norm_stderr": 0.03665349695640767 }, "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": 0.027834912527544067, "acc_norm": 0.7132075471698113, "acc_norm_stderr": 0.027834912527544067 }, "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": 0.49, "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": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "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": 0.4215686274509804, "acc_stderr": 0.049135952012744975, "acc_norm": 0.4215686274509804, "acc_norm_stderr": 0.049135952012744975 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.76, "acc_stderr": 0.04292346959909282, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909282 }, "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": 0.5, "acc_stderr": 0.047036043419179864, "acc_norm": 0.5, "acc_norm_stderr": 0.047036043419179864 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5724137931034483, "acc_stderr": 0.04122737111370333, "acc_norm": 0.5724137931034483, "acc_norm_stderr": 0.04122737111370333 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.41005291005291006, "acc_stderr": 0.025331202438944437, "acc_norm": 0.41005291005291006, "acc_norm_stderr": 0.025331202438944437 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.48412698412698413, "acc_stderr": 0.04469881854072606, "acc_norm": 0.48412698412698413, "acc_norm_stderr": 0.04469881854072606 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7903225806451613, "acc_stderr": 0.023157879349083525, "acc_norm": 0.7903225806451613, "acc_norm_stderr": 0.023157879349083525 }, 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"harness|truthfulqa:mc|0": { "mc1": 0.47368421052631576, "mc1_stderr": 0.017479241161975526, "mc2": 0.651312479462047, "mc2_stderr": 0.015362786449252212 }, "harness|winogrande|5": { "acc": 0.7987371744277821, "acc_stderr": 0.01126851997157768 }, "harness|gsm8k|5": { "acc": 0.686125852918878, "acc_stderr": 0.012782681251053205 } } ``` ## 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]
larrylawl/opus
--- annotations_creators: - expert-generated - found language_creators: - found - expert-generated license: [] multilinguality: - translation pretty_name: opus size_categories: [] source_datasets: [] tags: - parallel-corpus task_categories: - translation task_ids: [] --- # Dataset Card for [opus] ## 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 **Disclaimer.** Loading of dataset is slow, thus it may not be feasible when loading at scale. I'd suggest to use the other OPUS datasets on Huggingface which loads a specific corpus. Loads [OPUS](https://opus.nlpl.eu/) as HuggingFace dataset. OPUS is an open parallel corpus covering 700+ languages and 1100+ datasets. Given a `src` and `tgt` language, this repository can load *all* available parallel corpus. To my knowledge, other OPUS datasets on Huggingface loads a specific corpus **Requirements**. ``` pip install pandas # pip install my fork of `opustools` git clone https://github.com/larrylawl/OpusTools.git pip install -e OpusTools/opustools_pkg ``` **Example Usage**. ``` # args follows `opustools`: https://pypi.org/project/opustools/ src="en" tgt="id" download_dir="data" # dir to save downloaded files corpus="bible-uedin" # corpus name. Leave as `None` to download all available corpus for the src-tgt pair. dataset = load_dataset("larrylawl/opus", src=src, tgt=tgt, download_dir=download_dir, corpus=corpus) ) ``` **Disclaimer**. This repository is still in active development. Do make a PR if there're any issues! ### Dataset Summary [More Information Needed] ### Supported Tasks and Leaderboards [More Information Needed] ### Languages Available languages can be viewed on the [OPUS API](https://opus.nlpl.eu/opusapi/?languages=True) ## Dataset Structure ### Data Instances ``` {'src': 'In the beginning God created the heavens and the earth .', 'tgt': 'Pada mulanya , waktu Allah mulai menciptakan alam semesta'} ``` ### Data Fields ``` features = { "src": datasets.Value("string"), "tgt": datasets.Value("string"), } ``` ### Data Splits Merged all data into train split. ## 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 [@larrylawl](https://larrylawl.github.io/) for adding this dataset.
autoevaluate/autoeval-eval-glue-mrpc-9038ab-1509054846
--- type: predictions tags: - autotrain - evaluation datasets: - glue eval_info: task: natural_language_inference model: JeremiahZ/bert-base-uncased-mrpc metrics: [] dataset_name: glue dataset_config: mrpc dataset_split: validation col_mapping: text1: sentence1 text2: sentence2 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: Natural Language Inference * Model: JeremiahZ/bert-base-uncased-mrpc * Dataset: glue * Config: mrpc * Split: validation To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@JeremiahZ](https://huggingface.co/JeremiahZ) for evaluating this model.
TinyPixel/lima_1
--- dataset_info: features: - name: human dtype: string - name: gpt dtype: string splits: - name: train num_bytes: 2887450 num_examples: 1030 download_size: 1701721 dataset_size: 2887450 --- # Dataset Card for "lima_1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
result-kand2-sdxl-wuerst-karlo/b6112e1b
--- dataset_info: features: - name: result dtype: string - name: id dtype: int64 splits: - name: train num_bytes: 166 num_examples: 10 download_size: 1318 dataset_size: 166 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "b6112e1b" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
dmayhem93/agieval-lsat-ar
--- dataset_info: features: - name: query dtype: string - name: choices sequence: string - name: gold sequence: int64 splits: - name: test num_bytes: 273902 num_examples: 230 download_size: 66495 dataset_size: 273902 --- # Dataset Card for "agieval-lsat-ar" Dataset taken from https://github.com/microsoft/AGIEval and processed as in that repo. Raw datset: https://github.com/zhongwanjun/AR-LSAT MIT License Copyright (c) 2022 Wanjun Zhong Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. @misc{zhong2023agieval, title={AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models}, author={Wanjun Zhong and Ruixiang Cui and Yiduo Guo and Yaobo Liang and Shuai Lu and Yanlin Wang and Amin Saied and Weizhu Chen and Nan Duan}, year={2023}, eprint={2304.06364}, archivePrefix={arXiv}, primaryClass={cs.CL} } @misc{zhong2021arlsat, title={AR-LSAT: Investigating Analytical Reasoning of Text}, author={Wanjun Zhong and Siyuan Wang and Duyu Tang and Zenan Xu and Daya Guo and Jiahai Wang and Jian Yin and Ming Zhou and Nan Duan}, year={2021}, eprint={2104.06598}, archivePrefix={arXiv}, primaryClass={cs.CL} } @article{wang2022lsat, title={From lsat: The progress and challenges of complex reasoning}, author={Wang, Siyuan and Liu, Zhongkun and Zhong, Wanjun and Zhou, Ming and Wei, Zhongyu and Chen, Zhumin and Duan, Nan}, journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing}, year={2022}, publisher={IEEE} }
dkshjn/chatdoctor-200k-stripped-embedded
--- dataset_info: features: - name: input dtype: string - name: instruction dtype: string - name: output dtype: string splits: - name: s1 num_bytes: 82572870.22843863 num_examples: 82964 - name: s2 num_bytes: 82571874.94289035 num_examples: 82963 - name: s3 num_bytes: 82571874.94289035 num_examples: 82963 - name: s4 num_bytes: 82571874.94289035 num_examples: 82963 - name: s5 num_bytes: 82571874.94289035 num_examples: 82963 download_size: 231809582 dataset_size: 412860370.0 configs: - config_name: default data_files: - split: s1 path: data/s1-* - split: s2 path: data/s2-* - split: s3 path: data/s3-* - split: s4 path: data/s4-* - split: s5 path: data/s5-* ---
Seanxh/twitter_dataset_1713204712
--- 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: 134471 num_examples: 315 download_size: 51234 dataset_size: 134471 configs: - config_name: default data_files: - split: train path: data/train-* ---
Nexdata/Russian_Spontaneous_Speech_Data
--- task_categories: - automatic-speech-recognition language: - ru --- # Dataset Card for Nexdata/Russian_Spontaneous_Speech_Data ## Description 503 Hours - Russian Spontaneous Speech Data, the content covering multiple topics. All the speech audio was manually transcribed into text content; speaker identity, gender, and other attribution are also annotated. This dataset can be used for voiceprint recognition model training, corpus construction for machine translation, and algorithm research introduction For more details, please refer to the link: https://www.nexdata.ai/datasets/1271?source=Huggingface # Specifications ## Format 16kHz, 16bit, mono channel; ## Content category including education, interview, sports, etc ## Language Russian; ## Annotation annotation for the transcription text, speaker identification, gender; ## Application scenarios speech recognition, video caption generation and video content review; ## Accuracy at a word Accuracy Rate (WAR) of being no less than 98%. # Licensing Information Commercial License
sruly/StepBackSearch
--- license: apache-2.0 ---