Datasets:
davanstrien
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summary-test

Dataset card Data Studio Files
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Limour/perplexity
--- license: cc-by-nc-sa-4.0 language: - zh tags: - not-for-all-audiences --- https://www.kaggle.com/code/reginliu/perplexity | Model | Size | PPL | n_vocab | PPL_adjust | |-------|---------|---------|---------|---------| | [qwen1_5-14b-chat-IQ3_XS.gguf](https://huggingface.co/Limour/Qwen1.5-14B-Chat-GGUF/blob/main/qwen1_5-14b-chat-IQ3_XS.gguf) | 6.48 | 11.8084 +/- 0.121615 | 152064 | 11.8084 | | [causallm_14b.IQ3_XS.gguf](https://huggingface.co/Limour/CausalLM-14B-GGUF/blob/main/causallm_14b.IQ3_XS.gguf) | 6.48 | 13.3798 +/- 0.13641 | 152064 | 13.3798 | | [causallm_14b.IQ4_XS.gguf](https://huggingface.co/Limour/CausalLM-14B-GGUF/blob/main/causallm_14b.IQ4_XS.gguf) | 7.85 | 13.4127 +/- 0.13762 | 152064 | 13.4127 | | [causallm_14b.Q4_0.gguf](https://huggingface.co/TheBloke/CausalLM-14B-GGUF/blob/main/causallm_14b.Q4_0.gguf) | 8.18 | 13.6714 +/- 0.13964 | 152064 | 13.6714 | | [causallm_14b.IQ2_XXS.gguf](https://huggingface.co/Limour/CausalLM-14B-GGUF/blob/main/causallm_14b.IQ2_XXS.gguf) | 4.98 | 15.0160 +/- 0.15004 | 152064 | 15.0160 | | [Yi-9B-200K_iQ3xxs.gguf](https://huggingface.co/MarsupialAI/Yi-9B-200K_iMatrix_GGUF/blob/main/Yi-9B-200K_iQ3xxs.gguf) | 3.47 | 6.8157 +/- 0.05453 | 64000 | 16.1941 | | [Fi-9B-200K-Q8_0.gguf](https://huggingface.co/DisOOM/Fi-9B-GGUF/blob/main/Fi-9B-Q8_0.gguf) | 9.38 | 6.8402 +/- 0.05741 | 64000 | 16.2523 | | [causallm_7b.Q5_K_M.gguf](https://huggingface.co/TheBloke/CausalLM-7B-GGUF/blob/main/causallm_7b.Q5_K_M.gguf) | 5.53 | 16.5278 +/- 0.18005 | 152064 | 16.5278 | | [Qwen1.5-22B-Chat-Merge-Q4_0.gguf](https://huggingface.co/DisOOM/Qwen1.5-22B-Chat-Merge-GGUF/blob/main/Qwen1.5-22B-Chat-Merge-Q4_0.gguf) | 12.6 | 21.9669 +/- 0.28980 | 152064 | 21.9669 | | [Kunoichi-DPO-v2-7B-Q4_K_M-imatrix.gguf](https://hf-mirror.com/Lewdiculous/Kunoichi-DPO-v2-7B-GGUF-Imatrix/blob/main/Kunoichi-DPO-v2-7B-Q4_K_M-imatrix.gguf) | 4.37 | 6.7096 +/- 0.04519 | 32000 | 31.8840 | For a model that returns tokens completely at random, we have $$ P(token|context) = \frac{1}{n_{vocab}}, \quad PPL = \sqrt[N]{\left(\frac{1}{P}\right)^N} = n_{vocab} $$ therefore $$ PPL_{adjust} = \frac{PPL}{n_{vocab}} \times 152064 $$
japanese-asr/whisper_transcriptions.reazonspeech.all_49
--- dataset_info: config_name: all features: - name: name dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: transcription dtype: string - name: whisper_transcript sequence: int64 splits: - name: train num_bytes: 30365182032.0 num_examples: 267347 download_size: 30123643810 dataset_size: 30365182032.0 configs: - config_name: all data_files: - split: train path: all/train-* ---
irds/beir_dbpedia-entity_test
--- pretty_name: '`beir/dbpedia-entity/test`' viewer: false source_datasets: ['irds/beir_dbpedia-entity'] task_categories: - text-retrieval --- # Dataset Card for `beir/dbpedia-entity/test` The `beir/dbpedia-entity/test` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package. For more information about the dataset, see the [documentation](https://ir-datasets.com/beir#beir/dbpedia-entity/test). # Data This dataset provides: - `queries` (i.e., topics); count=400 - `qrels`: (relevance assessments); count=43,515 - For `docs`, use [`irds/beir_dbpedia-entity`](https://huggingface.co/datasets/irds/beir_dbpedia-entity) ## Usage ```python from datasets import load_dataset queries = load_dataset('irds/beir_dbpedia-entity_test', 'queries') for record in queries: record # {'query_id': ..., 'text': ...} qrels = load_dataset('irds/beir_dbpedia-entity_test', 'qrels') for record in qrels: record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...} ``` Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the data in 🤗 Dataset format. ## Citation Information ``` @article{Hasibi2017DBpediaEntityVA, title={DBpedia-Entity v2: A Test Collection for Entity Search}, author={Faegheh Hasibi and Fedor Nikolaev and Chenyan Xiong and K. Balog and S. E. Bratsberg and Alexander Kotov and J. Callan}, journal={Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval}, year={2017} } @article{Thakur2021Beir, title = "BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models", author = "Thakur, Nandan and Reimers, Nils and Rücklé, Andreas and Srivastava, Abhishek and Gurevych, Iryna", journal= "arXiv preprint arXiv:2104.08663", month = "4", year = "2021", url = "https://arxiv.org/abs/2104.08663", } ```
ozz/turkishReviews-ds-mini
--- dataset_info: features: - name: review dtype: string - name: review_length dtype: int64 splits: - name: train num_bytes: 134598991.2416305 num_examples: 362520 - name: validation num_bytes: 14955814.758369517 num_examples: 40281 download_size: 95987466 dataset_size: 149554806.0 --- # Dataset Card for "turkishReviews-ds-mini" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
AnabolAndi/Models_test
--- license: other ---
chansung/auto-paper-qa-test
--- dataset_info: features: - name: title dtype: string - name: summary dtype: string - name: abstract dtype: string - name: authors dtype: string - name: arxiv_id dtype: string - name: 0_question dtype: string - name: 0_answers:eli5 dtype: string - name: 0_answers:expert dtype: string - name: 0_additional_depth_q:follow up question dtype: string - name: 0_additional_depth_q:answers:eli5 dtype: string - name: 0_additional_depth_q:answers:expert dtype: string - name: 0_additional_breath_q:follow up question dtype: string - name: 0_additional_breath_q:answers:eli5 dtype: string - name: 0_additional_breath_q:answers:expert dtype: string - name: 1_question dtype: string - name: 1_answers:eli5 dtype: string - name: 1_answers:expert dtype: string - name: 1_additional_depth_q:follow up question dtype: string - name: 1_additional_depth_q:answers:eli5 dtype: string - name: 1_additional_depth_q:answers:expert dtype: string - name: 1_additional_breath_q:follow up question dtype: string - name: 1_additional_breath_q:answers:eli5 dtype: string - name: 1_additional_breath_q:answers:expert dtype: string - name: 2_question dtype: string - name: 2_answers:eli5 dtype: string - name: 2_answers:expert dtype: string - name: 2_additional_depth_q:follow up question dtype: string - name: 2_additional_depth_q:answers:eli5 dtype: string - name: 2_additional_depth_q:answers:expert dtype: string - name: 2_additional_breath_q:follow up question dtype: string - name: 2_additional_breath_q:answers:eli5 dtype: string - name: 2_additional_breath_q:answers:expert dtype: string - name: 3_question dtype: string - name: 3_answers:eli5 dtype: string - name: 3_answers:expert dtype: string - name: 3_additional_depth_q:follow up question dtype: string - name: 3_additional_depth_q:answers:eli5 dtype: string - name: 3_additional_depth_q:answers:expert dtype: string - name: 3_additional_breath_q:follow up question dtype: string - name: 3_additional_breath_q:answers:eli5 dtype: string - name: 3_additional_breath_q:answers:expert dtype: string - name: target_date dtype: timestamp[s] - name: 4_question dtype: string - name: 4_answers:eli5 dtype: string - name: 4_answers:expert dtype: string - name: 4_additional_depth_q:follow up question dtype: string - name: 4_additional_depth_q:answers:eli5 dtype: string - name: 4_additional_depth_q:answers:expert dtype: string - name: 4_additional_breath_q:follow up question dtype: string - name: 4_additional_breath_q:answers:eli5 dtype: string - name: 4_additional_breath_q:answers:expert dtype: string - name: 5_question dtype: string - name: 5_answers:eli5 dtype: string - name: 5_answers:expert dtype: string - name: 5_additional_depth_q:follow up question dtype: string - name: 5_additional_depth_q:answers:eli5 dtype: string - name: 5_additional_depth_q:answers:expert dtype: string - name: 5_additional_breath_q:follow up question dtype: string - name: 5_additional_breath_q:answers:eli5 dtype: string - name: 5_additional_breath_q:answers:expert dtype: string - name: 6_question dtype: string - name: 6_answers:eli5 dtype: string - name: 6_answers:expert dtype: string - name: 6_additional_depth_q:follow up question dtype: string - name: 6_additional_depth_q:answers:eli5 dtype: string - name: 6_additional_depth_q:answers:expert dtype: string - name: 6_additional_breath_q:follow up question dtype: string - name: 6_additional_breath_q:answers:eli5 dtype: string - name: 6_additional_breath_q:answers:expert dtype: string - name: 7_question dtype: string - name: 7_answers:eli5 dtype: string - name: 7_answers:expert dtype: string - name: 7_additional_depth_q:follow up question dtype: string - name: 7_additional_depth_q:answers:eli5 dtype: string - name: 7_additional_depth_q:answers:expert dtype: string - name: 7_additional_breath_q:follow up question dtype: string - name: 7_additional_breath_q:answers:eli5 dtype: string - name: 7_additional_breath_q:answers:expert dtype: string - name: 8_question dtype: string - name: 8_answers:eli5 dtype: string - name: 8_answers:expert dtype: string - name: 8_additional_depth_q:follow up question dtype: string - name: 8_additional_depth_q:answers:eli5 dtype: string - name: 8_additional_depth_q:answers:expert dtype: string - name: 8_additional_breath_q:follow up question dtype: string - name: 8_additional_breath_q:answers:eli5 dtype: string - name: 8_additional_breath_q:answers:expert dtype: string - name: 9_question dtype: string - name: 9_answers:eli5 dtype: string - name: 9_answers:expert dtype: string - name: 9_additional_depth_q:follow up question dtype: string - name: 9_additional_depth_q:answers:eli5 dtype: string - name: 9_additional_depth_q:answers:expert dtype: string - name: 9_additional_breath_q:follow up question dtype: string - name: 9_additional_breath_q:answers:eli5 dtype: string - name: 9_additional_breath_q:answers:expert dtype: string splits: - name: train num_bytes: 51368 num_examples: 3 download_size: 258271 dataset_size: 51368 configs: - config_name: default data_files: - split: train path: data/train-* ---
DeepFoldProtein/openfold_msa_contrastive_cards_000_processed_1024_ankh
--- dataset_info: features: - name: query_accession sequence: string - name: excludes sequence: sequence: string - name: query_sequence sequence: string - name: target_accessions sequence: sequence: string - name: target_sequences sequence: sequence: string - name: input_ids sequence: sequence: sequence: int64 - name: attention_mask sequence: sequence: sequence: int64 - name: special_tokens_mask sequence: sequence: sequence: int64 splits: - name: train num_bytes: 71626433715 num_examples: 64937 download_size: 2140946171 dataset_size: 71626433715 configs: - config_name: default data_files: - split: train path: data/train-* ---
danjacobellis/food101_cascade
--- dataset_info: features: - name: label dtype: class_label: names: '0': apple_pie '1': baby_back_ribs '2': baklava '3': beef_carpaccio '4': beef_tartare '5': beet_salad '6': beignets '7': bibimbap '8': bread_pudding '9': breakfast_burrito '10': bruschetta '11': caesar_salad '12': cannoli '13': caprese_salad '14': carrot_cake '15': ceviche '16': cheesecake '17': cheese_plate '18': chicken_curry '19': chicken_quesadilla '20': chicken_wings '21': chocolate_cake '22': chocolate_mousse '23': churros '24': clam_chowder '25': club_sandwich '26': crab_cakes '27': creme_brulee '28': croque_madame '29': cup_cakes '30': deviled_eggs '31': donuts '32': dumplings '33': edamame '34': eggs_benedict '35': escargots '36': falafel '37': filet_mignon '38': fish_and_chips '39': foie_gras '40': french_fries '41': french_onion_soup '42': french_toast '43': fried_calamari '44': fried_rice '45': frozen_yogurt '46': garlic_bread '47': gnocchi '48': greek_salad '49': grilled_cheese_sandwich '50': grilled_salmon '51': guacamole '52': gyoza '53': hamburger '54': hot_and_sour_soup '55': hot_dog '56': huevos_rancheros '57': hummus '58': ice_cream '59': lasagna '60': lobster_bisque '61': lobster_roll_sandwich '62': macaroni_and_cheese '63': macarons '64': miso_soup '65': mussels '66': nachos '67': omelette '68': onion_rings '69': oysters '70': pad_thai '71': paella '72': pancakes '73': panna_cotta '74': peking_duck '75': pho '76': pizza '77': pork_chop '78': poutine '79': prime_rib '80': pulled_pork_sandwich '81': ramen '82': ravioli '83': red_velvet_cake '84': risotto '85': samosa '86': sashimi '87': scallops '88': seaweed_salad '89': shrimp_and_grits '90': spaghetti_bolognese '91': spaghetti_carbonara '92': spring_rolls '93': steak '94': strawberry_shortcake '95': sushi '96': tacos '97': takoyaki '98': tiramisu '99': tuna_tartare '100': waffles - name: compressed_image dtype: binary splits: - name: train num_bytes: 176984876 num_examples: 75747 - name: validation num_bytes: 59015433 num_examples: 25250 download_size: 249884687 dataset_size: 236000309 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---
minimario/apps_partial_sorted_300_350
--- dataset_info: features: - name: problem dtype: string - name: code dtype: string - name: label dtype: int64 - name: full_sample dtype: string - name: where_from dtype: string splits: - name: train num_bytes: 25695567 num_examples: 20543 download_size: 923285 dataset_size: 25695567 --- # Dataset Card for "apps_partial_sorted_300_350" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
james-burton/OrientalMuseum_min4-white-mat
--- dataset_info: features: - name: obj_num dtype: string - name: file dtype: string - name: image dtype: image - name: root dtype: string - name: description dtype: string - name: object_name dtype: string - name: other_name dtype: string - name: label dtype: class_label: names: '0': Actinolite '1': Aluminium bronze alloy '2': Animal Mummy '3': Batik '4': Buffalo Horn '5': Chinese Red Rosewood '6': Colour on Paper '7': Flint/Chert '8': Gouache on Paper '9': Haematite/Red Ochre '10': Human Bone '11': Ink and Colour on Paper '12': Ink and Colours on Silk '13': Ink and Opaque Watercolour on Paper '14': Ink on Paper '15': Jade (Calcified) '16': Japanese paper '17': Microcline/Green Feldspar/Amazon-Stone '18': Nile Mud '19': Opaque Watercolour and Gilt on Paper '20': Opaque Watercolour on Paper '21': Opaque Watercolour or Gouache on Mica '22': Pith '23': Pith Paper '24': Plant Product '25': Resin/Plastic '26': Rhinoceros Horn '27': Shell (Ostrich Egg) '28': Smaragdite '29': Steatite '30': Steatite/Soap Stone '31': Watercolour on Rice Paper '32': acrylic '33': agate '34': alabaster '35': aluminum '36': amber '37': amethyst '38': antler '39': artificial stone '40': balsa '41': bamboo '42': basalt '43': bone '44': bowenite '45': boxwood '46': brass '47': brocade '48': bronze '49': burnt jade '50': canvas '51': cardboard '52': cards '53': carnelian '54': cast iron '55': celadon '56': cellulose acetate '57': ceramic '58': chalcedony '59': cherry '60': clay '61': cloth '62': coconut '63': copper '64': copper alloy '65': coral '66': cotton '67': crystal '68': diorite '69': dolerite '70': earthenware '71': ebony '72': emerald '73': enamel '74': faience '75': felt '76': flax '77': flint '78': gauze '79': glass '80': gold '81': granite '82': gray ware '83': hardwood '84': horn '85': incense '86': ink '87': iron '88': ivory '89': jade '90': jadeite '91': jasper '92': lacquer '93': lapis lazuli '94': lazurite '95': lead '96': lead alloy '97': leather '98': limestone '99': linen '100': malachite '101': marble '102': metal '103': mineral '104': mother of pearl '105': muslin '106': nephrite '107': nylon '108': obsidian '109': organic material '110': organza '111': paint '112': palm fiber '113': palm leaf '114': paper '115': papier mâché '116': papyrus '117': pewter '118': photographic paper '119': pine '120': plant fiber '121': plaster '122': plastic '123': plate '124': polyester '125': polystyrene '126': porcelain '127': pottery '128': quartzite '129': rattan '130': realgar '131': reed '132': rice paper '133': rock '134': rush '135': sandstone '136': satin '137': schist '138': seashell '139': serpentine '140': shagreen '141': shell '142': silk '143': siltstone '144': silver '145': silver alloy '146': skull '147': slate '148': soapstone '149': softwood '150': stalagmites '151': steel '152': stone '153': stoneware '154': straw '155': stucco '156': sycamore '157': synthetic fiber '158': teak '159': terracotta '160': textiles '161': tin '162': tortoise shell '163': tourmaline '164': travertine '165': tremolite '166': turquoise '167': velvet '168': wood '169': wool '170': wrought iron '171': zinc alloy - name: production.period dtype: string - name: production.place dtype: string - name: new_root dtype: string splits: - name: train num_bytes: 646369556.254 num_examples: 23083 - name: validation num_bytes: 182535306.672 num_examples: 5432 - name: test num_bytes: 166408429.856 num_examples: 5432 download_size: 951074067 dataset_size: 995313292.7819998 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
mask-distilled-onesec-cv12-each-chunk-uniq/chunk_19
--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1433739164.0 num_examples: 281567 download_size: 1460267942 dataset_size: 1433739164.0 --- # Dataset Card for "chunk_19" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
LambdaTests/VQAv2_sample_validation_benchmarks_partition_global_4_loca_4
--- dataset_info: features: - name: id dtype: int64 - name: response dtype: string splits: - name: train num_bytes: 15 num_examples: 1 download_size: 0 dataset_size: 15 --- # Dataset Card for "VQAv2_sample_validation_benchmarks_partition_global_4_loca_4" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
gg-ai/es-0103-stop-no-demoji-no-hasthag-l
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: val path: data/val-* dataset_info: features: - name: text dtype: string - name: clean_text dtype: string - name: sent dtype: int64 splits: - name: train num_bytes: 10604987 num_examples: 28854 - name: test num_bytes: 2174343 num_examples: 6131 - name: val num_bytes: 370030 num_examples: 1082 download_size: 8223549 dataset_size: 13149360 --- # Dataset Card for "es-0103-stop-no-demoji-no-hasthag-l" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_TheBloke__Kimiko-v2-13B-fp16
--- pretty_name: Evaluation run of TheBloke/Kimiko-v2-13B-fp16 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [TheBloke/Kimiko-v2-13B-fp16](https://huggingface.co/TheBloke/Kimiko-v2-13B-fp16)\ \ 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_TheBloke__Kimiko-v2-13B-fp16\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-22T17:23:39.395223](https://huggingface.co/datasets/open-llm-leaderboard/details_TheBloke__Kimiko-v2-13B-fp16/blob/main/results_2023-10-22T17-23-39.395223.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\": 0.0017827181208053692,\n\ \ \"em_stderr\": 0.00043200973460388544,\n \"f1\": 0.06393351510067083,\n\ \ \"f1_stderr\": 0.001389281752742565,\n \"acc\": 0.44652528493459387,\n\ \ \"acc_stderr\": 0.01048837556583878\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.0017827181208053692,\n \"em_stderr\": 0.00043200973460388544,\n\ \ \"f1\": 0.06393351510067083,\n \"f1_stderr\": 0.001389281752742565\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.12509476876421532,\n \ \ \"acc_stderr\": 0.009112601439849618\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7679558011049724,\n \"acc_stderr\": 0.01186414969182794\n\ \ }\n}\n```" repo_url: https://huggingface.co/TheBloke/Kimiko-v2-13B-fp16 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_31T10_23_07.841871 path: - '**/details_harness|arc:challenge|25_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-08-31T10:23:07.841871.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_22T17_23_39.395223 path: - '**/details_harness|drop|3_2023-10-22T17-23-39.395223.parquet' - split: latest path: - '**/details_harness|drop|3_2023-10-22T17-23-39.395223.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_22T17_23_39.395223 path: - '**/details_harness|gsm8k|5_2023-10-22T17-23-39.395223.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-10-22T17-23-39.395223.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hellaswag|10_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-31T10:23:07.841871.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-management|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-virology|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-31T10:23:07.841871.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_31T10_23_07.841871 path: - '**/details_harness|truthfulqa:mc|0_2023-08-31T10:23:07.841871.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-08-31T10:23:07.841871.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_22T17_23_39.395223 path: - '**/details_harness|winogrande|5_2023-10-22T17-23-39.395223.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-10-22T17-23-39.395223.parquet' - config_name: results data_files: - split: 2023_08_31T10_23_07.841871 path: - results_2023-08-31T10:23:07.841871.parquet - split: 2023_10_22T17_23_39.395223 path: - results_2023-10-22T17-23-39.395223.parquet - split: latest path: - results_2023-10-22T17-23-39.395223.parquet --- # Dataset Card for Evaluation run of TheBloke/Kimiko-v2-13B-fp16 ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/TheBloke/Kimiko-v2-13B-fp16 - **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 [TheBloke/Kimiko-v2-13B-fp16](https://huggingface.co/TheBloke/Kimiko-v2-13B-fp16) 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_TheBloke__Kimiko-v2-13B-fp16", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-22T17:23:39.395223](https://huggingface.co/datasets/open-llm-leaderboard/details_TheBloke__Kimiko-v2-13B-fp16/blob/main/results_2023-10-22T17-23-39.395223.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": 0.0017827181208053692, "em_stderr": 0.00043200973460388544, "f1": 0.06393351510067083, "f1_stderr": 0.001389281752742565, "acc": 0.44652528493459387, "acc_stderr": 0.01048837556583878 }, "harness|drop|3": { "em": 0.0017827181208053692, "em_stderr": 0.00043200973460388544, "f1": 0.06393351510067083, "f1_stderr": 0.001389281752742565 }, "harness|gsm8k|5": { "acc": 0.12509476876421532, "acc_stderr": 0.009112601439849618 }, "harness|winogrande|5": { "acc": 0.7679558011049724, "acc_stderr": 0.01186414969182794 } } ``` ### 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_lizhuang144__llama_mirror_13b_v1.0
--- pretty_name: Evaluation run of lizhuang144/llama_mirror_13b_v1.0 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [lizhuang144/llama_mirror_13b_v1.0](https://huggingface.co/lizhuang144/llama_mirror_13b_v1.0)\ \ 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_lizhuang144__llama_mirror_13b_v1.0\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-09-17T10:53:19.904763](https://huggingface.co/datasets/open-llm-leaderboard/details_lizhuang144__llama_mirror_13b_v1.0/blob/main/results_2023-09-17T10-53-19.904763.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\": 0.002726510067114094,\n\ \ \"em_stderr\": 0.0005340111700415926,\n \"f1\": 0.06866086409395994,\n\ \ \"f1_stderr\": 0.0014864813602608763,\n \"acc\": 0.42033799014225337,\n\ \ \"acc_stderr\": 0.00955801932501455\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.002726510067114094,\n \"em_stderr\": 0.0005340111700415926,\n\ \ \"f1\": 0.06866086409395994,\n \"f1_stderr\": 0.0014864813602608763\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.07429871114480667,\n \ \ \"acc_stderr\": 0.007223844172845574\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7663772691397001,\n \"acc_stderr\": 0.011892194477183524\n\ \ }\n}\n```" repo_url: https://huggingface.co/lizhuang144/llama_mirror_13b_v1.0 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_09T16_49_32.921683 path: - '**/details_harness|arc:challenge|25_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-08-09T16:49:32.921683.parquet' - config_name: harness_drop_3 data_files: - split: 2023_09_17T10_53_19.904763 path: - '**/details_harness|drop|3_2023-09-17T10-53-19.904763.parquet' - split: latest path: - '**/details_harness|drop|3_2023-09-17T10-53-19.904763.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_09_17T10_53_19.904763 path: - '**/details_harness|gsm8k|5_2023-09-17T10-53-19.904763.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-09-17T10-53-19.904763.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hellaswag|10_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-09T16:49:32.921683.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-management|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-virology|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T16:49:32.921683.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_09T16_49_32.921683 path: - '**/details_harness|truthfulqa:mc|0_2023-08-09T16:49:32.921683.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-08-09T16:49:32.921683.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_09_17T10_53_19.904763 path: - '**/details_harness|winogrande|5_2023-09-17T10-53-19.904763.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-09-17T10-53-19.904763.parquet' - config_name: results data_files: - split: 2023_08_09T16_49_32.921683 path: - results_2023-08-09T16:49:32.921683.parquet - split: 2023_09_17T10_53_19.904763 path: - results_2023-09-17T10-53-19.904763.parquet - split: latest path: - results_2023-09-17T10-53-19.904763.parquet --- # Dataset Card for Evaluation run of lizhuang144/llama_mirror_13b_v1.0 ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/lizhuang144/llama_mirror_13b_v1.0 - **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 [lizhuang144/llama_mirror_13b_v1.0](https://huggingface.co/lizhuang144/llama_mirror_13b_v1.0) 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_lizhuang144__llama_mirror_13b_v1.0", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-09-17T10:53:19.904763](https://huggingface.co/datasets/open-llm-leaderboard/details_lizhuang144__llama_mirror_13b_v1.0/blob/main/results_2023-09-17T10-53-19.904763.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": 0.002726510067114094, "em_stderr": 0.0005340111700415926, "f1": 0.06866086409395994, "f1_stderr": 0.0014864813602608763, "acc": 0.42033799014225337, "acc_stderr": 0.00955801932501455 }, "harness|drop|3": { "em": 0.002726510067114094, "em_stderr": 0.0005340111700415926, "f1": 0.06866086409395994, "f1_stderr": 0.0014864813602608763 }, "harness|gsm8k|5": { "acc": 0.07429871114480667, "acc_stderr": 0.007223844172845574 }, "harness|winogrande|5": { "acc": 0.7663772691397001, "acc_stderr": 0.011892194477183524 } } ``` ### 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]
Ckail/Needy_Girl_Overdose_P
--- license: apache-2.0 ---
liuyanchen1015/MULTI_VALUE_mnli_verbal_ing_suffix
--- dataset_info: features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: int64 - name: idx dtype: int64 - name: score dtype: int64 splits: - name: dev_matched num_bytes: 1961229 num_examples: 9527 - name: dev_mismatched num_bytes: 2066574 num_examples: 9535 - name: test_matched num_bytes: 1948471 num_examples: 9403 - name: test_mismatched num_bytes: 2069435 num_examples: 9573 - name: train num_bytes: 78004343 num_examples: 373005 download_size: 55482068 dataset_size: 86050052 --- # Dataset Card for "MULTI_VALUE_mnli_verbal_ing_suffix" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Julianasm/minhavozValmir
--- license: openrail ---
nattiey1/diverse-unit-QA
--- task_categories: - question-answering size_categories: - 100K<n<1M --- # Dataset Card for DUQA ## Table of Contents - [Dataset Description](#dataset-description) * [Abstract](#abstract) * [Languages](#languages) - [Dataset Structure](#dataset-structure) * [Data Instances](#data-instances) * [Data Fields](#data-fields) - [Data Statistics](#data-statistics) - [Dataset Creation](#dataset-creation) * [Curation Rationale](#curation-rationale) * [Source Data](#source-data) * [Annotations](#annotations) - [Considerations for Using the Data](#considerations-for-using-the-data) * [Discussion of Social Impact and Biases](#discussion-of-social-impact-and-biases) * [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) * [Dataset Curators](#dataset-curators) * [Licensing Information](#licensing-information) * [Citation Information](#citation-information) ## Dataset Description ### Abstract DUQA is a dataset for single-step unit conversion questions. It comes in three sizes, ”DUQA10k”, ”DUQA100k” and ”DUQA1M”, with 10,000, 100,000 and 1,000,000 entries respectively. Each size contains a mixture of basic and complex conversion questions, including simple conversion, multiple answer, max/min, argmax/argmin, and noisy/q-noisy questions. The complexity level varies based on the amount of information present in the sentence and the number of reasoning steps required to calculate a correct answer. ### Languages The text in the dataset is in English. ## Dataset Structure ### Data Instances A single instance in the dataset consists of a question related to a single-step unit conversion problem, along with its corresponding correct answer. ### Data Fields The dataset contains fields for the question, answer, and additional context about the question, along with multiple choices answers. ## Data Statistics The dataset comes in three sizes, with 10,000, 100,000 and 1,000,000 entries respectively. ## Dataset Creation ### Curation Rationale The dataset is curated to help machine learning models understand and perform single-step unit conversions. This ability is essential for many real-world applications, including but not limited to physical sciences, engineering, and data analysis tasks. ### Source Data The source data for the dataset is generated using a Python library provided with the dataset, which can create new datasets from a list of templates. ### Annotations The dataset does not contain any annotations. ## Considerations for Using the Data ### Discussion of Social Impact and Biases The dataset is neutral and does not contain any explicit biases or social implications as it deals primarily with mathematical conversion problems. ### Other Known Limitations The complexity of the questions is limited to single-step unit conversions. It does not cover multi-step or more complex unit conversion problems. ## Additional Information ### Dataset Curators The dataset was created by a team of researchers. More information might be needed to provide specific names or organizations. ### Licensing Information The licensing information for this dataset is not provided. Please consult the dataset provider for more details. ### Citation Information The citation information for this dataset is not provided. Please consult the dataset provider for more details.
ResplendentAI/NSFW_Format_Test
--- license: apache-2.0 task_categories: - text-generation language: - en tags: - not-for-all-audiences pretty_name: NSFW Format Test ---
liuyanchen1015/MULTI_VALUE_sst2_aint_be
--- dataset_info: features: - name: sentence dtype: string - name: label dtype: int64 - name: idx dtype: int64 - name: score dtype: int64 splits: - name: dev num_bytes: 5299 num_examples: 36 - name: test num_bytes: 11318 num_examples: 79 - name: train num_bytes: 148455 num_examples: 1330 download_size: 84818 dataset_size: 165072 --- # Dataset Card for "MULTI_VALUE_sst2_aint_be" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
yantitarina34/stable_diffusion
--- license: apache-2.0 ---
aignosi/langchaing-docs-chatgpt-plugin
--- license: apache-2.0 ---
greenpau/amz-press-release
--- license: cc-by-nc-4.0 task_categories: - text-generation language: - en pretty_name: Public Amazon Press Release Dataset size_categories: - 1K<n<10K configs: - config_name: default data_files: 'data.jsonl.zst' --- # amz-press-release Public Amazon Press Release Dataset ## Dataset Description This dataset contains data from Amazon News: http://amazon2022tf.q4web.com/news/default.aspx ## Dataset Structure Each line in the downloaded data file is a JSON dictionary containing the following data. ```json { "headline": "Amazon's Buy with Prime Increases Shopper Conversion by an Average of 25%", "url": "/news/news-details/2023/Amazons-Buy-with-Prime-Increases-Shopper-Conversion-by-an-Average-of-25/default.aspx", "seo_name": "Amazons-Buy-with-Prime-Increases-Shopper-Conversion-by-an-Average-of-25", "id": 4850, "date": "01/10/2023 08:00:00", "parsed_headline": "Amazon's Buy with Prime Increases Shopper Conversion by an Average of 25%", "parsed_date": "01/10/2023", "parsed_subheading_txt": "Previously available on an invite-only basis ...", "parsed_subheading_html": "<div><p><i>Previously available on an invite-only basis ... </i></p></div>", "parsed_body_txt": "SEATTLE--(BUSINESS WIRE)-- \nAmazon today announced that Buy with Prime ...", "parsed_body_html": "<p>SEATTLE--(BUSINESS WIRE)-- Amazon today announced that Buy with Prime ...</p>" } ``` ### Citation Information ```bibtex @misc{amz-press-release, author = {Paul Greenberg}, title = {Public Amazon Press Release Dataset}, year = {2023}, publisher = {Hugging Face}, journal = {Hugging Face repository}, howpublished = {\\url{https://huggingface.co/datasets/greenpau/amz-press-release}}, } ```
owanr/o1o2o3_xl_r2_coedit
--- dataset_info: features: - name: src dtype: string - name: tgt sequence: string splits: - name: train num_bytes: 18084526 num_examples: 35807 download_size: 7764285 dataset_size: 18084526 --- # Dataset Card for "o1o2o3_xl_r2_coedit" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
manishiitg/unalignment-toxic-dpo-v0.2
--- dataset_info: features: - name: prompt dtype: string - name: chosen dtype: string - name: rejected dtype: string - name: id dtype: string - name: system dtype: string splits: - name: train num_bytes: 3610985 num_examples: 1082 download_size: 1426016 dataset_size: 3610985 configs: - config_name: default data_files: - split: train path: data/train-* ---
hazardous/har
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': calling '1': clapping '2': cycling '3': dancing '4': drinking '5': eating '6': fighting '7': hugging '8': laughing '9': listening_to_music '10': running '11': sitting '12': sleeping '13': texting '14': using_laptop splits: - name: train num_bytes: 208908112.2 num_examples: 12600 download_size: 227817680 dataset_size: 208908112.2 --- # Dataset Card for "har" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Tippawan/en-th-full-abstract-pairs
--- dataset_info: features: - name: translation struct: - name: en dtype: string - name: th dtype: string splits: - name: train num_bytes: 13578996 num_examples: 4998 - name: validation num_bytes: 2518289 num_examples: 624 - name: test num_bytes: 2783734 num_examples: 624 download_size: 7114435 dataset_size: 18881019 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
hotchpotch/ms_marco_japanese
--- language: - ja license: other license_name: same-ms-marco license_link: https://huggingface.co/datasets/ms_marco dataset_info: config_name: v2.1-madlad400-3b features: - name: answers sequence: string - name: passages sequence: - name: is_selected dtype: int32 - name: passage_text dtype: string - name: url dtype: string - name: query dtype: string - name: query_id dtype: int32 - name: query_type dtype: string - name: wellFormedAnswers sequence: string splits: - name: validation num_bytes: 440690468 num_examples: 101093 - name: train num_bytes: 3590508080 num_examples: 808731 - name: test num_bytes: 430765349 num_examples: 101092 download_size: 2491144245 dataset_size: 4461963897 configs: - config_name: v2.1-madlad400-3b data_files: - split: validation path: v2.1-madlad400-3b/validation-* - split: train path: v2.1-madlad400-3b/train-* - split: test path: v2.1-madlad400-3b/test-* --- # ms_marco_japanese - [ms_marco](https://huggingface.co/datasets/ms_marco) の日本語翻訳データです。 - 翻訳には、[google/madlad400-3b-mt](https://huggingface.co/google/madlad400-3b-mt)を利用しています。 - HuggingFace で公開されている、ms_marco と同等の構造で保存しています。 - 翻訳品質はそれほど高くありません。繁体字などが含まれるデータもあります。Google Translate API を用いて翻訳された、マルチリンガルms_marcoデータセットである、[mMARCO](https://github.com/unicamp-dl/mMARCO)の方が品質が高いです。そのため、このデータセットを利用の際は、他の翻訳データセットとの比較をお勧めします。 - wellFormedAnswers カラムは翻訳していません - 翻訳にかかった時間は、高速化のため[santhosh/madlad400-3b-ct2](https://huggingface.co/santhosh/madlad400-3b-ct2)を利用し、対象のデータ約1000万文に対して RTX3090 で8日ほどでした。 ## 利用方法 ``` from datasets import load_dataset train_ds = load_dataset("hotchpotch/ms_marco_japanese", "v2.1-madlad400-3b", split="train") validation_ds = load_dataset("hotchpotch/ms_marco_japanese", "v2.1-madlad400-3b", split="validation") test_ds = load_dataset("hotchpotch/ms_marco_japanese", "v2.1-madlad400-3b", split="test" ``` ``` print(train_ds[0]) {'answers': ['マンハッタン計画の成功が直接的にもたらした影響は、原子力研究者や技術員達による素晴しい業績を覆い隠す唯一な雲であった。その成果と真実であるもの:何十万という無辜なる命々があきれていたことだろうか?'], 'passages': {'is_selected': [1, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'passage_text': ['科学者の間でコミュニケーションが行われることは、マンハッタン計画を成功させるために重要であった。原子力研究家や技術員たちによって達成された素晴らしい業績には雲だけがあふれているものだろうか?その実際的な意味と言えば何十万という無辜なる人々へ生命も犠牲になっていることですね!', 'マンハッタン計画とその原子爆弾は第二次世界大戦の終結に寄与し、平和的な目標をもって核エネルギーが利用されたことで歴史や科学界には影響力があった。', 'マンハッタン計画は原子爆弾の製造が可能かどうかなんて見るために始められた。このプロジェクトを成功させれば、世界には永遠な変化がありそこまで強力で人工的であることも知らしむことになっただろいますからね.', 'マンハッタン計画(Manhattan Project)は、第二次世界大戦中にアメリカ合衆国で行われた原子爆弾開発プロジェクトの名称。特別には1942年から翌日までレスリー・R. グローブズ将軍が指揮する米陸军工兵隊によって実施されたものをいうことが多かったのである 。', 'また、各巻のバージョンと補完的なウェブサイトもある。最初に作られたのは『マンハッタン計画: インタラクティヴ・ヒストリー』であり([http://www.cfo-doe/me70_history)歴史遺産資源局および国家核安全保障庁によるものだったが現在では全て廃止されています(https//en](http://www.cfo-doe/me70_history)%E6%AD%B4%E5%8F%B2%E9%81%BA%E7%94%A3%E8%B3%87%E6%BA%90%E5%B1%80%E3%81%8A%E3%82%88%E3%81%B3%E5%9B%BD%E5%AE%B6%E6%A0%B8%E5%AE%89%E5%85%A8%E4%BF%9D%E9%9A%9C%E5%BA%81%E3%81%AB%E3%82%88%E3%82%8B%E3%82%82%E3%81%AE%E3%81%A0%E3%81%A3%E3%81%9F%E3%81%8C%E7%8F%BE%E5%9C%A8%E3%81%A7%E3%81%AF%E5%85%A8%E3%81%A6%E5%BB%83%E6%AD%A2%E3%81%95%E3%82%8C%E3%81%A6%E3%81%84%E3%81%BE%E3%81%99(https//en))', '原子爆弾は、1945年7月にニューメキシコ州の砂漠で初めて実験的な核兵器として使用された。その後も多くが開発され続けたものだったのである(マンハッタン計画)。', 'また、原爆や第二次世界大戦の終結に関する非常によく豊富な文献を置き換える試みもない。本コレクションはマンハッタン計画について起源と発展が記録されることには努めていませんのである 。', 'マンハッタン計画(Manhattan Project)は、第二次世界大戦中に最初の核兵器を生産した研究開発事業である。イギリスとカナダによる支援下アメリカ合衆国が主導していたものだった 。1942年から1946年代までこのプロジェクトには米陸軍工廠少将レスリー・グローブス (Leslie Groves) (英語版 )(en:Lesley G.Grove, US Army Corp of Engineer), ロサンゼル斯原子力実験場所長ロバート·オペンハーマーらも参加しており,その間爆弾設計者として活躍していることでも知られていたのであり ,また彼等自身について言及する必要性があると考えている人物であることなどよりこれ以上詳細な情報ではないかという意見がありました', '1942年6月、アメリカ陸軍工兵隊はマンハッタン計画を開始した。原子爆弾の秘密名称であるが.', 'マンハッタン計画のB炉がハンフォードに建設される理由は、北アメリカ沿岸から太平洋へ流れ込む最大級河川であるコロンビア湖と近いことだった。'], 'url': ['[http://www.pitt.edu/~sdb14/atombomb.html](http://www.pitt.edu/~sdb14/atombomb.html)', '[http://www.osti.gov/accomplishments/manhattan_story.html](http://www.osti.gov/accomplishments/manhattan_story.html)', '[http://www.123helpme.com/impact-of-the-manhattan-project-preview.asp?id=177337](http://www.123helpme.com/impact-of-the-manhattan-project-preview.asp?id=177337)', '[http://www.answers.com/Q/How_did_the_Manhattan_Project_impact_on_society](http://www.answers.com/Q/How_did_the_Manhattan_Project_impact_on_society)', '[https://www.osti.gov/manhattan-project-history/publications/Manhattan_Project_2010.pdf](https://www.osti.gov/manhattan-project-history/publications/Manhattan_Project_2010.pdf)', '[http://www.ushistory.org/us/51f.asp](http://www.ushistory.org/us/51f.asp)', '[http://nsarchive.gwu.edu/NSAEBB/NSAEBB162](http://nsarchive.gwu.edu/NSAEBB/NSAEBB162)', '[https://en.wikipedia.org/wiki/Manhattan_Project](https://en.wikipedia.org/wiki/Manhattan_Project)', '[https://quizlet.com/41456230/a-bomb-flash-cards/](https://quizlet.com/41456230/a-bomb-flash-cards/)', '[https://www.atomicheritage.org/history/environmental-consequences](https://www.atomicheritage.org/history/environmental-consequences)']}, 'query': '(マンハッタン計画の成功が直接的にもたらした影響は何でしょうか。', 'query_id': 1185869, 'query_type': 'DESCRIPTION', 'wellFormedAnswers': []} ``` ## ライセンス - ms_marco と同等とします。
Plachta/GLIP-test-images
--- license: apache-2.0 ---
gagan3012/toxicRMv2
--- dataset_info: features: - name: prompt dtype: string - name: candidates list: - name: decoding_method dtype: string - name: model dtype: string - name: scores struct: - name: pairrm dtype: float64 - name: safety dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 50284677.0707871 num_examples: 57103 - name: test num_bytes: 508103.9292128988 num_examples: 577 download_size: 23537168 dataset_size: 50792781.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
GilsonRDF/Teste
--- dataset_info: features: - name: conversation dtype: string splits: - name: train num_bytes: 5450.4 num_examples: 24 - name: test num_bytes: 1362.6 num_examples: 6 download_size: 6033 dataset_size: 6813.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
David-Xu/astronomy-stack-dpo-text
--- dataset_info: features: - name: chosen dtype: string - name: rejected dtype: string - name: prompt dtype: string splits: - name: train num_bytes: 53775582 num_examples: 17942 - name: test num_bytes: 6055646 num_examples: 1993 download_size: 17732927 dataset_size: 59831228 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
ascolda/ru_en_Crystallography_and_Spectroscopy
--- task_categories: - translation language: - ru - en size_categories: - 10K<n<100K tags: - chemistry ---
yuanmei424/xxt_en
--- dataset_info: features: - name: edit_prompt dtype: string - name: input_image dtype: image - name: edited_image dtype: image splits: - name: train num_bytes: 5329195147.25 num_examples: 2283951 download_size: 526250170 dataset_size: 5329195147.25 --- # Dataset Card for "xxt_en" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
irds/wikiclir_tl
--- pretty_name: '`wikiclir/tl`' viewer: false source_datasets: [] task_categories: - text-retrieval --- # Dataset Card for `wikiclir/tl` The `wikiclir/tl` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package. For more information about the dataset, see the [documentation](https://ir-datasets.com/wikiclir#wikiclir/tl). # Data This dataset provides: - `docs` (documents, i.e., the corpus); count=79,008 - `queries` (i.e., topics); count=48,930 - `qrels`: (relevance assessments); count=72,359 ## Usage ```python from datasets import load_dataset docs = load_dataset('irds/wikiclir_tl', 'docs') for record in docs: record # {'doc_id': ..., 'title': ..., 'text': ...} queries = load_dataset('irds/wikiclir_tl', 'queries') for record in queries: record # {'query_id': ..., 'text': ...} qrels = load_dataset('irds/wikiclir_tl', 'qrels') for record in qrels: record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...} ``` Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the data in 🤗 Dataset format. ## Citation Information ``` @inproceedings{sasaki-etal-2018-cross, title = "Cross-Lingual Learning-to-Rank with Shared Representations", author = "Sasaki, Shota and Sun, Shuo and Schamoni, Shigehiko and Duh, Kevin and Inui, Kentaro", booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)", month = jun, year = "2018", address = "New Orleans, Louisiana", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/N18-2073", doi = "10.18653/v1/N18-2073", pages = "458--463" } ```
medric49/dolly-rag-gpt4-ins
--- dataset_info: features: - name: instruction dtype: string - name: context dtype: string - name: response dtype: string - name: category dtype: string splits: - name: train num_bytes: 7282892 num_examples: 4467 download_size: 4479160 dataset_size: 7282892 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "dolly-rag-gpt4-ins" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/3db56ea8
--- dataset_info: features: - name: result dtype: string - name: id dtype: int64 splits: - name: train num_bytes: 178 num_examples: 10 download_size: 1331 dataset_size: 178 --- # Dataset Card for "3db56ea8" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
liuyanchen1015/MULTI_VALUE_wnli_present_modals
--- 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: 3384 num_examples: 15 - name: test num_bytes: 10975 num_examples: 39 - name: train num_bytes: 20618 num_examples: 107 download_size: 20617 dataset_size: 34977 --- # Dataset Card for "MULTI_VALUE_wnli_present_modals" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
plncmm/wl-body-part
--- license: cc-by-nc-4.0 ---
nikraf/uniref128-256AA
--- dataset_info: features: - name: seqs dtype: string splits: - name: train num_bytes: 92114464 num_examples: 487832 download_size: 92373850 dataset_size: 92114464 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_jsfs11__SnorkelWestBeagle-DARETIES-7B
--- pretty_name: Evaluation run of jsfs11/SnorkelWestBeagle-DARETIES-7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [jsfs11/SnorkelWestBeagle-DARETIES-7B](https://huggingface.co/jsfs11/SnorkelWestBeagle-DARETIES-7B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_jsfs11__SnorkelWestBeagle-DARETIES-7B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-25T09:47:01.298299](https://huggingface.co/datasets/open-llm-leaderboard/details_jsfs11__SnorkelWestBeagle-DARETIES-7B/blob/main/results_2024-01-25T09-47-01.298299.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\": 0.6479799815457161,\n\ \ \"acc_stderr\": 0.032161535797548865,\n \"acc_norm\": 0.6485286656946667,\n\ \ \"acc_norm_stderr\": 0.03282087535821274,\n \"mc1\": 0.5630354957160343,\n\ \ \"mc1_stderr\": 0.017363844503195953,\n \"mc2\": 0.7005107732516146,\n\ \ \"mc2_stderr\": 0.014999534657573073\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6843003412969283,\n \"acc_stderr\": 0.01358257109581529,\n\ \ \"acc_norm\": 0.71160409556314,\n \"acc_norm_stderr\": 0.013238394422428173\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.711611232822147,\n\ \ \"acc_stderr\": 0.004520870679457037,\n \"acc_norm\": 0.8735311690898228,\n\ \ \"acc_norm_stderr\": 0.0033169770861701505\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252605,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252605\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6296296296296297,\n\ \ \"acc_stderr\": 0.041716541613545426,\n \"acc_norm\": 0.6296296296296297,\n\ \ \"acc_norm_stderr\": 0.041716541613545426\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6973684210526315,\n \"acc_stderr\": 0.03738520676119669,\n\ \ \"acc_norm\": 0.6973684210526315,\n \"acc_norm_stderr\": 0.03738520676119669\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.59,\n\ \ \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.59,\n \ \ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.720754716981132,\n \"acc_stderr\": 0.027611163402399715,\n\ \ \"acc_norm\": 0.720754716981132,\n \"acc_norm_stderr\": 0.027611163402399715\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7638888888888888,\n\ \ \"acc_stderr\": 0.03551446610810826,\n \"acc_norm\": 0.7638888888888888,\n\ \ \"acc_norm_stderr\": 0.03551446610810826\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.46,\n \"acc_stderr\": 0.05009082659620333,\n \ \ \"acc_norm\": 0.46,\n \"acc_norm_stderr\": 0.05009082659620333\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.53,\n \"acc_stderr\": 0.050161355804659205,\n \"acc_norm\": 0.53,\n\ \ \"acc_norm_stderr\": 0.050161355804659205\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768077,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768077\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6705202312138728,\n\ \ \"acc_stderr\": 0.03583901754736412,\n \"acc_norm\": 0.6705202312138728,\n\ \ \"acc_norm_stderr\": 0.03583901754736412\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.38235294117647056,\n \"acc_stderr\": 0.04835503696107223,\n\ \ \"acc_norm\": 0.38235294117647056,\n \"acc_norm_stderr\": 0.04835503696107223\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.8,\n \"acc_stderr\": 0.04020151261036845,\n \"acc_norm\": 0.8,\n\ \ \"acc_norm_stderr\": 0.04020151261036845\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5787234042553191,\n \"acc_stderr\": 0.03227834510146267,\n\ \ \"acc_norm\": 0.5787234042553191,\n \"acc_norm_stderr\": 0.03227834510146267\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.49122807017543857,\n\ \ \"acc_stderr\": 0.04702880432049615,\n \"acc_norm\": 0.49122807017543857,\n\ \ \"acc_norm_stderr\": 0.04702880432049615\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5586206896551724,\n \"acc_stderr\": 0.04137931034482757,\n\ \ \"acc_norm\": 0.5586206896551724,\n \"acc_norm_stderr\": 0.04137931034482757\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.3994708994708995,\n \"acc_stderr\": 0.02522545028406788,\n \"\ acc_norm\": 0.3994708994708995,\n \"acc_norm_stderr\": 0.02522545028406788\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\": 0.4,\n \"acc_stderr\": 0.04923659639173309,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04923659639173309\n },\n\ \ \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7709677419354839,\n\ \ \"acc_stderr\": 0.023904914311782655,\n \"acc_norm\": 0.7709677419354839,\n\ \ \"acc_norm_stderr\": 0.023904914311782655\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.4975369458128079,\n \"acc_stderr\": 0.03517945038691063,\n\ \ \"acc_norm\": 0.4975369458128079,\n \"acc_norm_stderr\": 0.03517945038691063\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\ : 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7818181818181819,\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\"\ : 0.7828282828282829,\n \"acc_stderr\": 0.029376616484945633,\n \"\ acc_norm\": 0.7828282828282829,\n \"acc_norm_stderr\": 0.029376616484945633\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.9015544041450777,\n \"acc_stderr\": 0.021500249576033477,\n\ \ \"acc_norm\": 0.9015544041450777,\n \"acc_norm_stderr\": 0.021500249576033477\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6641025641025641,\n \"acc_stderr\": 0.023946724741563973,\n\ \ \"acc_norm\": 0.6641025641025641,\n \"acc_norm_stderr\": 0.023946724741563973\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.37407407407407406,\n \"acc_stderr\": 0.02950286112895529,\n \ \ \"acc_norm\": 0.37407407407407406,\n \"acc_norm_stderr\": 0.02950286112895529\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.680672268907563,\n \"acc_stderr\": 0.030283995525884396,\n \ \ \"acc_norm\": 0.680672268907563,\n \"acc_norm_stderr\": 0.030283995525884396\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.3509933774834437,\n \"acc_stderr\": 0.03896981964257375,\n \"\ acc_norm\": 0.3509933774834437,\n \"acc_norm_stderr\": 0.03896981964257375\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8275229357798165,\n \"acc_stderr\": 0.016197807956848043,\n \"\ acc_norm\": 0.8275229357798165,\n \"acc_norm_stderr\": 0.016197807956848043\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\": 0.8235294117647058,\n\ \ \"acc_stderr\": 0.026756401538078966,\n \"acc_norm\": 0.8235294117647058,\n\ \ \"acc_norm_stderr\": 0.026756401538078966\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\ : {\n \"acc\": 0.8016877637130801,\n \"acc_stderr\": 0.02595502084162113,\n\ \ \"acc_norm\": 0.8016877637130801,\n \"acc_norm_stderr\": 0.02595502084162113\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.672645739910314,\n\ \ \"acc_stderr\": 0.03149384670994131,\n \"acc_norm\": 0.672645739910314,\n\ \ \"acc_norm_stderr\": 0.03149384670994131\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7480916030534351,\n \"acc_stderr\": 0.03807387116306085,\n\ \ \"acc_norm\": 0.7480916030534351,\n \"acc_norm_stderr\": 0.03807387116306085\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.7603305785123967,\n \"acc_stderr\": 0.03896878985070417,\n \"\ acc_norm\": 0.7603305785123967,\n \"acc_norm_stderr\": 0.03896878985070417\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7129629629629629,\n\ \ \"acc_stderr\": 0.043733130409147614,\n \"acc_norm\": 0.7129629629629629,\n\ \ \"acc_norm_stderr\": 0.043733130409147614\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.754601226993865,\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\": 0.5,\n\ \ \"acc_stderr\": 0.04745789978762494,\n \"acc_norm\": 0.5,\n \ \ \"acc_norm_stderr\": 0.04745789978762494\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7572815533980582,\n \"acc_stderr\": 0.04245022486384495,\n\ \ \"acc_norm\": 0.7572815533980582,\n \"acc_norm_stderr\": 0.04245022486384495\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8974358974358975,\n\ \ \"acc_stderr\": 0.01987565502786744,\n \"acc_norm\": 0.8974358974358975,\n\ \ \"acc_norm_stderr\": 0.01987565502786744\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\": 0.8237547892720306,\n\ \ \"acc_stderr\": 0.013625556907993464,\n \"acc_norm\": 0.8237547892720306,\n\ \ \"acc_norm_stderr\": 0.013625556907993464\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7023121387283237,\n \"acc_stderr\": 0.024617055388677006,\n\ \ \"acc_norm\": 0.7023121387283237,\n \"acc_norm_stderr\": 0.024617055388677006\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.44581005586592176,\n\ \ \"acc_stderr\": 0.01662399851333311,\n \"acc_norm\": 0.44581005586592176,\n\ \ \"acc_norm_stderr\": 0.01662399851333311\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7418300653594772,\n \"acc_stderr\": 0.025058503316958143,\n\ \ \"acc_norm\": 0.7418300653594772,\n \"acc_norm_stderr\": 0.025058503316958143\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7106109324758842,\n\ \ \"acc_stderr\": 0.025755865922632945,\n \"acc_norm\": 0.7106109324758842,\n\ \ \"acc_norm_stderr\": 0.025755865922632945\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7283950617283951,\n \"acc_stderr\": 0.024748624490537368,\n\ \ \"acc_norm\": 0.7283950617283951,\n \"acc_norm_stderr\": 0.024748624490537368\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.4716312056737589,\n \"acc_stderr\": 0.029779450957303062,\n \ \ \"acc_norm\": 0.4716312056737589,\n \"acc_norm_stderr\": 0.029779450957303062\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.46936114732724904,\n\ \ \"acc_stderr\": 0.012746237711716634,\n \"acc_norm\": 0.46936114732724904,\n\ \ \"acc_norm_stderr\": 0.012746237711716634\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6727941176470589,\n \"acc_stderr\": 0.028501452860396553,\n\ \ \"acc_norm\": 0.6727941176470589,\n \"acc_norm_stderr\": 0.028501452860396553\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6437908496732027,\n \"acc_stderr\": 0.0193733324207245,\n \ \ \"acc_norm\": 0.6437908496732027,\n \"acc_norm_stderr\": 0.0193733324207245\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7181818181818181,\n\ \ \"acc_stderr\": 0.043091187099464585,\n \"acc_norm\": 0.7181818181818181,\n\ \ \"acc_norm_stderr\": 0.043091187099464585\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.726530612244898,\n \"acc_stderr\": 0.028535560337128445,\n\ \ \"acc_norm\": 0.726530612244898,\n \"acc_norm_stderr\": 0.028535560337128445\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8656716417910447,\n\ \ \"acc_stderr\": 0.024112678240900808,\n \"acc_norm\": 0.8656716417910447,\n\ \ \"acc_norm_stderr\": 0.024112678240900808\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\": 0.5060240963855421,\n\ \ \"acc_stderr\": 0.03892212195333045,\n \"acc_norm\": 0.5060240963855421,\n\ \ \"acc_norm_stderr\": 0.03892212195333045\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8362573099415205,\n \"acc_stderr\": 0.028380919596145866,\n\ \ \"acc_norm\": 0.8362573099415205,\n \"acc_norm_stderr\": 0.028380919596145866\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.5630354957160343,\n\ \ \"mc1_stderr\": 0.017363844503195953,\n \"mc2\": 0.7005107732516146,\n\ \ \"mc2_stderr\": 0.014999534657573073\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8318863456985004,\n \"acc_stderr\": 0.010510336954166742\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6209249431387415,\n \ \ \"acc_stderr\": 0.01336363029508836\n }\n}\n```" repo_url: https://huggingface.co/jsfs11/SnorkelWestBeagle-DARETIES-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: 2024_01_25T09_47_01.298299 path: - '**/details_harness|arc:challenge|25_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-01-25T09-47-01.298299.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|gsm8k|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hellaswag|10_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-management|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-01-25T09-47-01.298299.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-management|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-virology|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-01-25T09-47-01.298299.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|truthfulqa:mc|0_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-01-25T09-47-01.298299.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_25T09_47_01.298299 path: - '**/details_harness|winogrande|5_2024-01-25T09-47-01.298299.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-01-25T09-47-01.298299.parquet' - config_name: results data_files: - split: 2024_01_25T09_47_01.298299 path: - results_2024-01-25T09-47-01.298299.parquet - split: latest path: - results_2024-01-25T09-47-01.298299.parquet --- # Dataset Card for Evaluation run of jsfs11/SnorkelWestBeagle-DARETIES-7B <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [jsfs11/SnorkelWestBeagle-DARETIES-7B](https://huggingface.co/jsfs11/SnorkelWestBeagle-DARETIES-7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_jsfs11__SnorkelWestBeagle-DARETIES-7B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-25T09:47:01.298299](https://huggingface.co/datasets/open-llm-leaderboard/details_jsfs11__SnorkelWestBeagle-DARETIES-7B/blob/main/results_2024-01-25T09-47-01.298299.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": 0.6479799815457161, "acc_stderr": 0.032161535797548865, "acc_norm": 0.6485286656946667, "acc_norm_stderr": 0.03282087535821274, "mc1": 0.5630354957160343, "mc1_stderr": 0.017363844503195953, "mc2": 0.7005107732516146, "mc2_stderr": 0.014999534657573073 }, "harness|arc:challenge|25": { "acc": 0.6843003412969283, "acc_stderr": 0.01358257109581529, "acc_norm": 0.71160409556314, "acc_norm_stderr": 0.013238394422428173 }, "harness|hellaswag|10": { "acc": 0.711611232822147, "acc_stderr": 0.004520870679457037, "acc_norm": 0.8735311690898228, "acc_norm_stderr": 0.0033169770861701505 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6296296296296297, "acc_stderr": 0.041716541613545426, "acc_norm": 0.6296296296296297, "acc_norm_stderr": 0.041716541613545426 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6973684210526315, "acc_stderr": 0.03738520676119669, "acc_norm": 0.6973684210526315, "acc_norm_stderr": 0.03738520676119669 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.59, "acc_stderr": 0.049431107042371025, "acc_norm": 0.59, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.720754716981132, "acc_stderr": 0.027611163402399715, "acc_norm": 0.720754716981132, "acc_norm_stderr": 0.027611163402399715 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7638888888888888, "acc_stderr": 0.03551446610810826, "acc_norm": 0.7638888888888888, "acc_norm_stderr": 0.03551446610810826 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.53, "acc_stderr": 0.050161355804659205, "acc_norm": 0.53, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.26, "acc_stderr": 0.04408440022768077, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768077 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107223, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107223 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.8, "acc_stderr": 0.04020151261036845, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036845 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5787234042553191, "acc_stderr": 0.03227834510146267, "acc_norm": 0.5787234042553191, "acc_norm_stderr": 0.03227834510146267 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.49122807017543857, "acc_stderr": 0.04702880432049615, "acc_norm": 0.49122807017543857, "acc_norm_stderr": 0.04702880432049615 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5586206896551724, "acc_stderr": 0.04137931034482757, "acc_norm": 0.5586206896551724, "acc_norm_stderr": 0.04137931034482757 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3994708994708995, "acc_stderr": 0.02522545028406788, "acc_norm": 0.3994708994708995, "acc_norm_stderr": 0.02522545028406788 }, "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": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7709677419354839, "acc_stderr": 0.023904914311782655, "acc_norm": 0.7709677419354839, "acc_norm_stderr": 0.023904914311782655 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4975369458128079, "acc_stderr": 0.03517945038691063, "acc_norm": 0.4975369458128079, "acc_norm_stderr": 0.03517945038691063 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7818181818181819, "acc_stderr": 0.03225078108306289, "acc_norm": 0.7818181818181819, "acc_norm_stderr": 0.03225078108306289 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7828282828282829, "acc_stderr": 0.029376616484945633, "acc_norm": 0.7828282828282829, "acc_norm_stderr": 0.029376616484945633 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9015544041450777, "acc_stderr": 0.021500249576033477, "acc_norm": 0.9015544041450777, "acc_norm_stderr": 0.021500249576033477 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6641025641025641, "acc_stderr": 0.023946724741563973, "acc_norm": 0.6641025641025641, "acc_norm_stderr": 0.023946724741563973 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.37407407407407406, "acc_stderr": 0.02950286112895529, "acc_norm": 0.37407407407407406, "acc_norm_stderr": 0.02950286112895529 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.680672268907563, "acc_stderr": 0.030283995525884396, "acc_norm": 0.680672268907563, "acc_norm_stderr": 0.030283995525884396 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.3509933774834437, "acc_stderr": 0.03896981964257375, "acc_norm": 0.3509933774834437, "acc_norm_stderr": 0.03896981964257375 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8275229357798165, "acc_stderr": 0.016197807956848043, "acc_norm": 0.8275229357798165, "acc_norm_stderr": 0.016197807956848043 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5277777777777778, "acc_stderr": 0.0340470532865388, "acc_norm": 0.5277777777777778, "acc_norm_stderr": 0.0340470532865388 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8235294117647058, "acc_stderr": 0.026756401538078966, "acc_norm": 0.8235294117647058, "acc_norm_stderr": 0.026756401538078966 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8016877637130801, "acc_stderr": 0.02595502084162113, "acc_norm": 0.8016877637130801, "acc_norm_stderr": 0.02595502084162113 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.672645739910314, "acc_stderr": 0.03149384670994131, "acc_norm": 0.672645739910314, "acc_norm_stderr": 0.03149384670994131 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7480916030534351, "acc_stderr": 0.03807387116306085, "acc_norm": 0.7480916030534351, "acc_norm_stderr": 0.03807387116306085 }, "harness|hendrycksTest-international_law|5": { "acc": 0.7603305785123967, "acc_stderr": 0.03896878985070417, "acc_norm": 0.7603305785123967, "acc_norm_stderr": 0.03896878985070417 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7129629629629629, "acc_stderr": 0.043733130409147614, "acc_norm": 0.7129629629629629, "acc_norm_stderr": 0.043733130409147614 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.754601226993865, "acc_stderr": 0.03380939813943354, "acc_norm": 0.754601226993865, "acc_norm_stderr": 0.03380939813943354 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.5, "acc_stderr": 0.04745789978762494, "acc_norm": 0.5, "acc_norm_stderr": 0.04745789978762494 }, "harness|hendrycksTest-management|5": { "acc": 0.7572815533980582, "acc_stderr": 0.04245022486384495, "acc_norm": 0.7572815533980582, "acc_norm_stderr": 0.04245022486384495 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8974358974358975, "acc_stderr": 0.01987565502786744, "acc_norm": 0.8974358974358975, "acc_norm_stderr": 0.01987565502786744 }, "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": 0.8237547892720306, "acc_stderr": 0.013625556907993464, "acc_norm": 0.8237547892720306, "acc_norm_stderr": 0.013625556907993464 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7023121387283237, "acc_stderr": 0.024617055388677006, "acc_norm": 0.7023121387283237, "acc_norm_stderr": 0.024617055388677006 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.44581005586592176, "acc_stderr": 0.01662399851333311, "acc_norm": 0.44581005586592176, "acc_norm_stderr": 0.01662399851333311 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7418300653594772, "acc_stderr": 0.025058503316958143, "acc_norm": 0.7418300653594772, "acc_norm_stderr": 0.025058503316958143 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7106109324758842, "acc_stderr": 0.025755865922632945, "acc_norm": 0.7106109324758842, "acc_norm_stderr": 0.025755865922632945 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7283950617283951, "acc_stderr": 0.024748624490537368, "acc_norm": 0.7283950617283951, "acc_norm_stderr": 0.024748624490537368 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4716312056737589, "acc_stderr": 0.029779450957303062, "acc_norm": 0.4716312056737589, "acc_norm_stderr": 0.029779450957303062 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.46936114732724904, "acc_stderr": 0.012746237711716634, "acc_norm": 0.46936114732724904, "acc_norm_stderr": 0.012746237711716634 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6727941176470589, "acc_stderr": 0.028501452860396553, "acc_norm": 0.6727941176470589, "acc_norm_stderr": 0.028501452860396553 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6437908496732027, "acc_stderr": 0.0193733324207245, "acc_norm": 0.6437908496732027, "acc_norm_stderr": 0.0193733324207245 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.7181818181818181, "acc_stderr": 0.043091187099464585, "acc_norm": 0.7181818181818181, "acc_norm_stderr": 0.043091187099464585 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.726530612244898, "acc_stderr": 0.028535560337128445, "acc_norm": 0.726530612244898, "acc_norm_stderr": 0.028535560337128445 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8656716417910447, "acc_stderr": 0.024112678240900808, "acc_norm": 0.8656716417910447, "acc_norm_stderr": 0.024112678240900808 }, "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": 0.5060240963855421, "acc_stderr": 0.03892212195333045, "acc_norm": 0.5060240963855421, "acc_norm_stderr": 0.03892212195333045 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8362573099415205, "acc_stderr": 0.028380919596145866, "acc_norm": 0.8362573099415205, "acc_norm_stderr": 0.028380919596145866 }, "harness|truthfulqa:mc|0": { "mc1": 0.5630354957160343, "mc1_stderr": 0.017363844503195953, "mc2": 0.7005107732516146, "mc2_stderr": 0.014999534657573073 }, "harness|winogrande|5": { "acc": 0.8318863456985004, "acc_stderr": 0.010510336954166742 }, "harness|gsm8k|5": { "acc": 0.6209249431387415, "acc_stderr": 0.01336363029508836 } } ``` ## 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 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manu/english-60b
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: text dtype: string - name: id dtype: string - name: dataset_id dtype: string splits: - name: train num_bytes: 259969046699 num_examples: 58986336 - name: test num_bytes: 43278365 num_examples: 10000 download_size: 151705709032 dataset_size: 260012325064 --- # Dataset Card for "english_20b" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
SportsShot/SportsShot
--- license: cc-by-nc-4.0 ---
Falah/random_prompts
--- dataset_info: features: - name: prompts dtype: string splits: - name: train num_bytes: 27245594 num_examples: 100000 download_size: 4512640 dataset_size: 27245594 --- # Dataset Card for "random_prompts" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CyberHarem/sakurakouji_kinako_lovelivesuperstar
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of sakurakouji_kinako/桜小路きな子/사쿠라코지키나코 (Love Live! Superstar!!) This is the dataset of sakurakouji_kinako/桜小路きな子/사쿠라코지키나코 (Love Live! Superstar!!), containing 179 images and their tags. The core tags of this character are `bangs, brown_hair, long_hair, green_eyes, twintails, low_twintails, braid, blunt_bangs, ribbon, 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 | 179 | 238.88 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakurakouji_kinako_lovelivesuperstar/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 179 | 117.68 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakurakouji_kinako_lovelivesuperstar/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 415 | 258.04 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakurakouji_kinako_lovelivesuperstar/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 179 | 201.46 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakurakouji_kinako_lovelivesuperstar/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 415 | 400.25 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakurakouji_kinako_lovelivesuperstar/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/sakurakouji_kinako_lovelivesuperstar', 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 | 13 | ![](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, blue_jacket, grey_dress, long_sleeves, looking_at_viewer, neck_ribbon, solo, yuigaoka_school_uniform, smile, black_pantyhose, open_mouth, red_ribbon, blush, pinafore_dress, brown_footwear, full_body, loafers, collared_shirt, white_background | | 1 | 7 | ![](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) | 1girl, blue_jacket, blush, grey_dress, long_sleeves, looking_at_viewer, open_jacket, solo, yuigaoka_school_uniform, neck_ribbon, pinafore_dress, red_ribbon, white_background, black_pantyhose, petals, smile, white_shirt, closed_mouth, collared_shirt, french_braid, hair_ribbon, simple_background, upper_body | | 2 | 7 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | 1girl, beret, looking_at_viewer, solo, blue_headwear, short_sleeves, smile, birthday, dress, jacket, blush, collarbone, open_mouth, pink_gloves, white_background | | 3 | 11 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | 1girl, solo, fingerless_gloves, looking_at_viewer, smile, white_gloves, sleeveless, blush, open_mouth, arm_up, armpits, bow, clothes_around_waist, skirt, confetti, medium_breasts, green_ribbon | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | blue_jacket | grey_dress | long_sleeves | looking_at_viewer | neck_ribbon | solo | yuigaoka_school_uniform | smile | black_pantyhose | open_mouth | red_ribbon | blush | pinafore_dress | brown_footwear | full_body | loafers | collared_shirt | white_background | open_jacket | petals | white_shirt | closed_mouth | french_braid | hair_ribbon | simple_background | upper_body | beret | blue_headwear | short_sleeves | birthday | dress | jacket | collarbone | pink_gloves | fingerless_gloves | white_gloves | sleeveless | arm_up | armpits | bow | clothes_around_waist | skirt | confetti | medium_breasts | green_ribbon | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------|:-------------|:---------------|:--------------------|:--------------|:-------|:--------------------------|:--------|:------------------|:-------------|:-------------|:--------|:-----------------|:-----------------|:------------|:----------|:-----------------|:-------------------|:--------------|:---------|:--------------|:---------------|:---------------|:--------------|:--------------------|:-------------|:--------|:----------------|:----------------|:-----------|:--------|:---------|:-------------|:--------------|:--------------------|:---------------|:-------------|:---------|:----------|:------|:-----------------------|:--------|:-----------|:-----------------|:---------------| | 0 | 13 | ![](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 | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 7 | ![](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 | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | 2 | 7 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | X | | | | X | | X | | X | | X | | X | | | | | | X | | | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | 3 | 11 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | X | | | | X | | X | | X | | X | | X | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X |
CyberHarem/aihara_yukino_idolmastercinderellagirls
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of aihara_yukino/相原雪乃 (THE iDOLM@STER: Cinderella Girls) This is the dataset of aihara_yukino/相原雪乃 (THE iDOLM@STER: Cinderella Girls), containing 28 images and their tags. The core tags of this character are `brown_hair, long_hair, braid, brown_eyes, single_braid, very_long_hair, breasts, hat, bow`, 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 | 28 | 20.80 MiB | [Download](https://huggingface.co/datasets/CyberHarem/aihara_yukino_idolmastercinderellagirls/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 28 | 17.74 MiB | [Download](https://huggingface.co/datasets/CyberHarem/aihara_yukino_idolmastercinderellagirls/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 49 | 27.62 MiB | [Download](https://huggingface.co/datasets/CyberHarem/aihara_yukino_idolmastercinderellagirls/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 28 | 20.06 MiB | [Download](https://huggingface.co/datasets/CyberHarem/aihara_yukino_idolmastercinderellagirls/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 49 | 30.64 MiB | [Download](https://huggingface.co/datasets/CyberHarem/aihara_yukino_idolmastercinderellagirls/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/aihara_yukino_idolmastercinderellagirls', 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 | 5 | ![](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, smile, solo, dress, large_breasts, looking_at_viewer, necklace, cleavage, gloves, hair_bow, sitting, teacup | | 1 | 10 | ![](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) | 1girl, smile, solo, card_(medium), character_name, flower_(symbol), open_mouth, dress, gloves, hair_ornament, pink_background | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | smile | solo | dress | large_breasts | looking_at_viewer | necklace | cleavage | gloves | hair_bow | sitting | teacup | card_(medium) | character_name | flower_(symbol) | open_mouth | hair_ornament | pink_background | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------|:-------|:--------|:----------------|:--------------------|:-----------|:-----------|:---------|:-----------|:----------|:---------|:----------------|:-----------------|:------------------|:-------------|:----------------|:------------------| | 0 | 5 | ![](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 | | | | | | | | 1 | 10 | ![](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 |
daqc/wikihow_es
--- dataset_info: features: - name: title dtype: string - name: section_name dtype: string - name: summary dtype: string - name: document dtype: string - name: english_section_name dtype: string - name: english_url dtype: string - name: url dtype: string splits: - name: train num_bytes: 323465146 num_examples: 113160 download_size: 173101313 dataset_size: 323465146 configs: - config_name: default data_files: - split: train path: data/train-* ---
codesagar/malicious-llm-prompts
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* dataset_info: features: - name: prompt dtype: string - name: malicious dtype: bool - name: reasoning dtype: string - name: attack_type dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 2859138 num_examples: 3570 - name: validation num_bytes: 641063 num_examples: 763 - name: test num_bytes: 677615 num_examples: 765 download_size: 2405757 dataset_size: 4177816 --- # Dataset Card for "malicious-llm-prompts" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Giacinta/heehe
--- license: apache-2.0 task_categories: - text-classification language: - en pretty_name: ll size_categories: - 1K<n<10K ---
CyberHarem/archetto_arknights
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of archetto/アルケット/空弦 (Arknights) This is the dataset of archetto/アルケット/空弦 (Arknights), containing 212 images and their tags. The core tags of this character are `animal_ears, long_hair, blue_eyes, red_eyes, heterochromia, blonde_hair, breasts, tail, very_long_hair, brown_hair`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages | Name | Images | Size | Download | Type | Description | |:-----------------|---------:|:-----------|:--------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------| | raw | 212 | 434.73 MiB | [Download](https://huggingface.co/datasets/CyberHarem/archetto_arknights/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 1200 | 212 | 360.30 MiB | [Download](https://huggingface.co/datasets/CyberHarem/archetto_arknights/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 567 | 723.05 MiB | [Download](https://huggingface.co/datasets/CyberHarem/archetto_arknights/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/archetto_arknights', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | 0 | 11 | ![](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, black_dress, looking_at_viewer, red_cape, solo, black_gloves, epaulettes, simple_background, tiara, white_background, medium_breasts, blush, cowboy_shot, open_mouth, partially_fingerless_gloves, :d, upper_body | | 1 | 20 | ![](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) | 1girl, red_cape, solo, holding_bow_(weapon), arrow_(projectile), black_dress, black_gloves, looking_at_viewer, epaulettes, knee_boots, simple_background, white_background, full_body, medium_breasts, partially_fingerless_gloves, white_footwear, cross-laced_footwear, frilled_dress, tiara, thigh_strap, infection_monitor_(arknights) | | 2 | 49 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | 1girl, official_alternate_costume, solo, shirt, short_sleeves, looking_at_viewer, hair_bow, white_skirt, white_gloves, midriff, blush, open_mouth, navel, red_bowtie, crop_top, fingerless_gloves, miniskirt, cowboy_shot, infection_monitor_(arknights), parted_bangs, :d, white_background, epaulettes, holding, lion_tail, blue_jacket, microphone, two_side_up | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | black_dress | looking_at_viewer | red_cape | solo | black_gloves | epaulettes | simple_background | tiara | white_background | medium_breasts | blush | cowboy_shot | open_mouth | partially_fingerless_gloves | :d | upper_body | holding_bow_(weapon) | arrow_(projectile) | knee_boots | full_body | white_footwear | cross-laced_footwear | frilled_dress | thigh_strap | infection_monitor_(arknights) | official_alternate_costume | shirt | short_sleeves | hair_bow | white_skirt | white_gloves | midriff | navel | red_bowtie | crop_top | fingerless_gloves | miniskirt | parted_bangs | holding | lion_tail | blue_jacket | microphone | two_side_up | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------|:--------------------|:-----------|:-------|:---------------|:-------------|:--------------------|:--------|:-------------------|:-----------------|:--------|:--------------|:-------------|:------------------------------|:-----|:-------------|:-----------------------|:---------------------|:-------------|:------------|:-----------------|:-----------------------|:----------------|:--------------|:--------------------------------|:-----------------------------|:--------|:----------------|:-----------|:--------------|:---------------|:----------|:--------|:-------------|:-----------|:--------------------|:------------|:---------------|:----------|:------------|:--------------|:-------------|:--------------| | 0 | 11 | ![](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 | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 20 | ![](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 | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | 2 | 49 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | X | | X | | X | | X | | | X | | X | X | X | | X | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
open-llm-leaderboard/details_KoboldAI__fairseq-dense-1.3B
--- pretty_name: Evaluation run of KoboldAI/fairseq-dense-1.3B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [KoboldAI/fairseq-dense-1.3B](https://huggingface.co/KoboldAI/fairseq-dense-1.3B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 3 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_KoboldAI__fairseq-dense-1.3B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-19T04:22:19.785222](https://huggingface.co/datasets/open-llm-leaderboard/details_KoboldAI__fairseq-dense-1.3B/blob/main/results_2023-10-19T04-22-19.785222.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\": 0.024119127516778523,\n\ \ \"em_stderr\": 0.0015711543458424907,\n \"f1\": 0.10603817114093886,\n\ \ \"f1_stderr\": 0.002447898366394225,\n \"acc\": 0.2951854775059195,\n\ \ \"acc_stderr\": 0.006910524554827735\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.024119127516778523,\n \"em_stderr\": 0.0015711543458424907,\n\ \ \"f1\": 0.10603817114093886,\n \"f1_stderr\": 0.002447898366394225\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.590370955011839,\n\ \ \"acc_stderr\": 0.01382104910965547\n }\n}\n```" repo_url: https://huggingface.co/KoboldAI/fairseq-dense-1.3B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_drop_3 data_files: - split: 2023_10_19T04_22_19.785222 path: - '**/details_harness|drop|3_2023-10-19T04-22-19.785222.parquet' - split: latest path: - '**/details_harness|drop|3_2023-10-19T04-22-19.785222.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_19T04_22_19.785222 path: - '**/details_harness|gsm8k|5_2023-10-19T04-22-19.785222.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-10-19T04-22-19.785222.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_19T04_22_19.785222 path: - '**/details_harness|winogrande|5_2023-10-19T04-22-19.785222.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-10-19T04-22-19.785222.parquet' - config_name: results data_files: - split: 2023_10_19T04_22_19.785222 path: - results_2023-10-19T04-22-19.785222.parquet - split: latest path: - results_2023-10-19T04-22-19.785222.parquet --- # Dataset Card for Evaluation run of KoboldAI/fairseq-dense-1.3B ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/KoboldAI/fairseq-dense-1.3B - **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 [KoboldAI/fairseq-dense-1.3B](https://huggingface.co/KoboldAI/fairseq-dense-1.3B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 3 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_KoboldAI__fairseq-dense-1.3B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-19T04:22:19.785222](https://huggingface.co/datasets/open-llm-leaderboard/details_KoboldAI__fairseq-dense-1.3B/blob/main/results_2023-10-19T04-22-19.785222.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": 0.024119127516778523, "em_stderr": 0.0015711543458424907, "f1": 0.10603817114093886, "f1_stderr": 0.002447898366394225, "acc": 0.2951854775059195, "acc_stderr": 0.006910524554827735 }, "harness|drop|3": { "em": 0.024119127516778523, "em_stderr": 0.0015711543458424907, "f1": 0.10603817114093886, "f1_stderr": 0.002447898366394225 }, "harness|gsm8k|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness|winogrande|5": { "acc": 0.590370955011839, "acc_stderr": 0.01382104910965547 } } ``` ### 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_codellama__CodeLlama-7b-Instruct-hf
--- pretty_name: Evaluation run of codellama/CodeLlama-7b-Instruct-hf dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 3 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_codellama__CodeLlama-7b-Instruct-hf\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-14T16:13:27.845445](https://huggingface.co/datasets/open-llm-leaderboard/details_codellama__CodeLlama-7b-Instruct-hf/blob/main/results_2023-10-14T16-13-27.845445.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\": 0.0008389261744966443,\n\ \ \"em_stderr\": 0.00029649629898012493,\n \"f1\": 0.05166841442953039,\n\ \ \"f1_stderr\": 0.0012678878311342997,\n \"acc\": 0.36261266786861684,\n\ \ \"acc_stderr\": 0.010449619353516184\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.0008389261744966443,\n \"em_stderr\": 0.00029649629898012493,\n\ \ \"f1\": 0.05166841442953039,\n \"f1_stderr\": 0.0012678878311342997\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.07960576194086429,\n \ \ \"acc_stderr\": 0.00745592433867628\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.6456195737963694,\n \"acc_stderr\": 0.013443314368356088\n\ \ }\n}\n```" repo_url: https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|arc:challenge|25_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|arc:challenge|25_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-08-26T03:58:42.829453.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_14T16_13_27.845445 path: - '**/details_harness|drop|3_2023-10-14T16-13-27.845445.parquet' - split: latest path: - '**/details_harness|drop|3_2023-10-14T16-13-27.845445.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_14T16_13_27.845445 path: - '**/details_harness|gsm8k|5_2023-10-14T16-13-27.845445.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-10-14T16-13-27.845445.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hellaswag|10_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hellaswag|10_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-25T17:04:00.078187.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-26T03:58:42.829453.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-management|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-management|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-virology|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-virology|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-26T03:58:42.829453.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_25T17_04_00.078187 path: - '**/details_harness|truthfulqa:mc|0_2023-08-25T17:04:00.078187.parquet' - split: 2023_08_26T03_58_42.829453 path: - '**/details_harness|truthfulqa:mc|0_2023-08-26T03:58:42.829453.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-08-26T03:58:42.829453.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_14T16_13_27.845445 path: - '**/details_harness|winogrande|5_2023-10-14T16-13-27.845445.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-10-14T16-13-27.845445.parquet' - config_name: results data_files: - split: 2023_08_25T17_04_00.078187 path: - results_2023-08-25T17:04:00.078187.parquet - split: 2023_08_26T03_58_42.829453 path: - results_2023-08-26T03:58:42.829453.parquet - split: 2023_10_14T16_13_27.845445 path: - results_2023-10-14T16-13-27.845445.parquet - split: latest path: - results_2023-10-14T16-13-27.845445.parquet --- # Dataset Card for Evaluation run of codellama/CodeLlama-7b-Instruct-hf ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf - **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 [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 3 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_codellama__CodeLlama-7b-Instruct-hf", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-14T16:13:27.845445](https://huggingface.co/datasets/open-llm-leaderboard/details_codellama__CodeLlama-7b-Instruct-hf/blob/main/results_2023-10-14T16-13-27.845445.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": 0.0008389261744966443, "em_stderr": 0.00029649629898012493, "f1": 0.05166841442953039, "f1_stderr": 0.0012678878311342997, "acc": 0.36261266786861684, "acc_stderr": 0.010449619353516184 }, "harness|drop|3": { "em": 0.0008389261744966443, "em_stderr": 0.00029649629898012493, "f1": 0.05166841442953039, "f1_stderr": 0.0012678878311342997 }, "harness|gsm8k|5": { "acc": 0.07960576194086429, "acc_stderr": 0.00745592433867628 }, "harness|winogrande|5": { "acc": 0.6456195737963694, "acc_stderr": 0.013443314368356088 } } ``` ### 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]
fantasyfish/laion-art
--- dataset_info: features: - name: image dtype: image - name: text dtype: string - name: aesthetic dtype: float64 splits: - name: train num_bytes: 11640624315.8 num_examples: 20072 - name: test num_bytes: 538961083.0 num_examples: 855 download_size: 12347056207 dataset_size: 12179585398.8 --- # Dataset Card for "laion-art" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
daniilak/Russia_Real_Estate_2018_2021
--- license: cc --- ### Context The dataset consists of lists of unique objects of popular portals for the sale of real estate in Russia. More than 540 thousand objects. The dataset contains 540000 real estate objects in Russia. ### Content The Russian real estate market has a relatively short history. In the Soviet era, all properties were state-owned; people only had the right to use them with apartments allocated based on one's place of work. As a result, options for moving were fairly limited. However, after the fall of the Soviet Union, the Russian real estate market emerged and Muscovites could privatize and subsequently sell and buy properties for the first time. Today, Russian real estate is booming. It offers many exciting opportunities and high returns for lifestyle and investment. The real estate market has been in a growth phase for several years, which means that you can still find properties at very attractive prices, but with good chances of increasing their value in the future. ### Dataset The dataset has 13 fields. - date - date of publication of the announcement; - time - the time when the ad was published; - geo_lat - Latitude - geo_lon - Longitude - region - Region of Russia. There are 85 subjects in the country in total. - building_type - Facade type. 0 - Other. 1 - Panel. 2 - Monolithic. 3 - Brick. 4 - Blocky. 5 - Wooden - object_type - Apartment type. 1 - Secondary real estate market; 2 - New building; - level - Apartment floor - levels - Number of storeys - rooms - the number of living rooms. If the value is "-1", then it means "studio apartment" - area - the total area of ​​the apartment - kitchen_area - Kitchen area - price - Price. in rubles ### Attention. The dataset may contain erroneous data due to input errors on services, as well as outliers, and so on. ### :) Using this dataset, we offer Kagglers algorithms that use a wide range of functions to predict real estate prices. Competitors will rely on a vast dataset that includes housing data and macroeconomic models. An accurate forecasting model provides more confidence to its clients in a volatile economy.
Isamu136/custom_diffusion_eval_dataset
--- dataset_info: features: - name: image dtype: image - name: prompt dtype: string - name: ibot_b_16_embedding sequence: float32 - name: moco_vitb_imagenet_embeddings_without_last_layer sequence: float32 - name: clip_vision_l14 sequence: float32 - name: clip_l14 sequence: float32 splits: - name: train num_bytes: 200864257.0 num_examples: 64 download_size: 201259767 dataset_size: 200864257.0 --- # Dataset Card for "custom_diffusion_eval_dataset" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
rohithmr12/med-data
--- license: mit ---
yezhengli9/wmt20-ru-en
--- dataset_info: features: - name: id (string) dtype: string - name: translation (translation) dtype: string splits: - name: train num_bytes: 694166 num_examples: 991 download_size: 267391 dataset_size: 694166 --- # Dataset Card for "wmt20-ru-en" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CyberHarem/maryberry_lapisrelights
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Maryberry (Lapis Re:LiGHTs) This is the dataset of Maryberry (Lapis Re:LiGHTs), containing 58 images and their tags. The core tags of this character are `bangs, purple_eyes, hair_between_eyes, short_hair, blue_hair, long_hair`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages | Name | Images | Size | Download | Type | Description | |:-----------------|---------:|:----------|:-------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------| | raw | 58 | 32.72 MiB | [Download](https://huggingface.co/datasets/CyberHarem/maryberry_lapisrelights/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 58 | 27.74 MiB | [Download](https://huggingface.co/datasets/CyberHarem/maryberry_lapisrelights/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 104 | 46.51 MiB | [Download](https://huggingface.co/datasets/CyberHarem/maryberry_lapisrelights/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 58 | 32.69 MiB | [Download](https://huggingface.co/datasets/CyberHarem/maryberry_lapisrelights/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 104 | 52.42 MiB | [Download](https://huggingface.co/datasets/CyberHarem/maryberry_lapisrelights/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/maryberry_lapisrelights', 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 | 11 | ![](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, solo, blush, closed_mouth, holding, indoors, skirt, aqua_hair, smile, chair, puffy_short_sleeves, school_uniform, upper_body | | 1 | 16 | ![](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) | 1girl, solo, sleeveless, dress, hat, looking_at_viewer, white_headwear, aqua_hair, open_mouth, ribbon, smile, white_thighhighs, sailor_collar | | 2 | 9 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | 2girls, closed_mouth, bare_shoulders, blush, sleeveless, solo_focus, shirt, smile, black_gloves, blurry, dress, holding_hands, looking_at_viewer | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | blush | closed_mouth | holding | indoors | skirt | aqua_hair | smile | chair | puffy_short_sleeves | school_uniform | upper_body | sleeveless | dress | hat | looking_at_viewer | white_headwear | open_mouth | ribbon | white_thighhighs | sailor_collar | 2girls | bare_shoulders | solo_focus | shirt | black_gloves | blurry | holding_hands | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:--------|:---------------|:----------|:----------|:--------|:------------|:--------|:--------|:----------------------|:-----------------|:-------------|:-------------|:--------|:------|:--------------------|:-----------------|:-------------|:---------|:-------------------|:----------------|:---------|:-----------------|:-------------|:--------|:---------------|:---------|:----------------| | 0 | 11 | ![](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 | | | | | | | | | | | | | | | | | | 1 | 16 | ![](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 | | | | | | | | | 2 | 9 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | | | X | X | | | | | X | | | | | X | X | | X | | | | | | X | X | X | X | X | X | X |
awettig/Pile-HackerNews-0.5B-6K-opt
--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 6359132637 num_examples: 81380 - name: test num_bytes: 64945692 num_examples: 813 download_size: 1710629426 dataset_size: 6424078329 --- # Dataset Card for "Pile-HackerNews-0.5B-6K-opt" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
VasquesXavier/Ressentiment
--- dataset_info: features: - name: question dtype: string - name: answer dtype: string splits: - name: train num_bytes: 69808 num_examples: 3 download_size: 45123 dataset_size: 69808 --- # Dataset Card for "Ressentiment" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
pipi00pipi/bibi_he
--- license: openrail ---
Multimodal-Fatima/StanfordCars_test
--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': am general hummer suv 2000 '1': acura rl sedan 2012 '2': acura tl sedan 2012 '3': acura tl type-s 2008 '4': acura tsx sedan 2012 '5': acura integra type r 2001 '6': acura zdx hatchback 2012 '7': aston martin v8 vantage convertible 2012 '8': aston martin v8 vantage coupe 2012 '9': aston martin virage convertible 2012 '10': aston martin virage coupe 2012 '11': audi rs 4 convertible 2008 '12': audi a5 coupe 2012 '13': audi tts coupe 2012 '14': audi r8 coupe 2012 '15': audi v8 sedan 1994 '16': audi 100 sedan 1994 '17': audi 100 wagon 1994 '18': audi tt hatchback 2011 '19': audi s6 sedan 2011 '20': audi s5 convertible 2012 '21': audi s5 coupe 2012 '22': audi s4 sedan 2012 '23': audi s4 sedan 2007 '24': audi tt rs coupe 2012 '25': bmw activehybrid 5 sedan 2012 '26': bmw 1 series convertible 2012 '27': bmw 1 series coupe 2012 '28': bmw 3 series sedan 2012 '29': bmw 3 series wagon 2012 '30': bmw 6 series convertible 2007 '31': bmw x5 suv 2007 '32': bmw x6 suv 2012 '33': bmw m3 coupe 2012 '34': bmw m5 sedan 2010 '35': bmw m6 convertible 2010 '36': bmw x3 suv 2012 '37': bmw z4 convertible 2012 '38': bentley continental supersports conv. convertible 2012 '39': bentley arnage sedan 2009 '40': bentley mulsanne sedan 2011 '41': bentley continental gt coupe 2012 '42': bentley continental gt coupe 2007 '43': bentley continental flying spur sedan 2007 '44': bugatti veyron 16.4 convertible 2009 '45': bugatti veyron 16.4 coupe 2009 '46': buick regal gs 2012 '47': buick rainier suv 2007 '48': buick verano sedan 2012 '49': buick enclave suv 2012 '50': cadillac cts-v sedan 2012 '51': cadillac srx suv 2012 '52': cadillac escalade ext crew cab 2007 '53': chevrolet silverado 1500 hybrid crew cab 2012 '54': chevrolet corvette convertible 2012 '55': chevrolet corvette zr1 2012 '56': chevrolet corvette ron fellows edition z06 2007 '57': chevrolet traverse suv 2012 '58': chevrolet camaro convertible 2012 '59': chevrolet hhr ss 2010 '60': chevrolet impala sedan 2007 '61': chevrolet tahoe hybrid suv 2012 '62': chevrolet sonic sedan 2012 '63': chevrolet express cargo van 2007 '64': chevrolet avalanche crew cab 2012 '65': chevrolet cobalt ss 2010 '66': chevrolet malibu hybrid sedan 2010 '67': chevrolet trailblazer ss 2009 '68': chevrolet silverado 2500hd regular cab 2012 '69': chevrolet silverado 1500 classic extended cab 2007 '70': chevrolet express van 2007 '71': chevrolet monte carlo coupe 2007 '72': chevrolet malibu sedan 2007 '73': chevrolet silverado 1500 extended cab 2012 '74': chevrolet silverado 1500 regular cab 2012 '75': chrysler aspen suv 2009 '76': chrysler sebring convertible 2010 '77': chrysler town and country minivan 2012 '78': chrysler 300 srt-8 2010 '79': chrysler crossfire convertible 2008 '80': chrysler pt cruiser convertible 2008 '81': daewoo nubira wagon 2002 '82': dodge caliber wagon 2012 '83': dodge caliber wagon 2007 '84': dodge caravan minivan 1997 '85': dodge ram pickup 3500 crew cab 2010 '86': dodge ram pickup 3500 quad cab 2009 '87': dodge sprinter cargo van 2009 '88': dodge journey suv 2012 '89': dodge dakota crew cab 2010 '90': dodge dakota club cab 2007 '91': dodge magnum wagon 2008 '92': dodge challenger srt8 2011 '93': dodge durango suv 2012 '94': dodge durango suv 2007 '95': dodge charger sedan 2012 '96': dodge charger srt-8 2009 '97': eagle talon hatchback 1998 '98': fiat 500 abarth 2012 '99': fiat 500 convertible 2012 '100': ferrari ff coupe 2012 '101': ferrari california convertible 2012 '102': ferrari 458 italia convertible 2012 '103': ferrari 458 italia coupe 2012 '104': fisker karma sedan 2012 '105': ford f-450 super duty crew cab 2012 '106': ford mustang convertible 2007 '107': ford freestar minivan 2007 '108': ford expedition el suv 2009 '109': ford edge suv 2012 '110': ford ranger supercab 2011 '111': ford gt coupe 2006 '112': ford f-150 regular cab 2012 '113': ford f-150 regular cab 2007 '114': ford focus sedan 2007 '115': ford e-series wagon van 2012 '116': ford fiesta sedan 2012 '117': gmc terrain suv 2012 '118': gmc savana van 2012 '119': gmc yukon hybrid suv 2012 '120': gmc acadia suv 2012 '121': gmc canyon extended cab 2012 '122': geo metro convertible 1993 '123': hummer h3t crew cab 2010 '124': hummer h2 sut crew cab 2009 '125': honda odyssey minivan 2012 '126': honda odyssey minivan 2007 '127': honda accord coupe 2012 '128': honda accord sedan 2012 '129': hyundai veloster hatchback 2012 '130': hyundai santa fe suv 2012 '131': hyundai tucson suv 2012 '132': hyundai veracruz suv 2012 '133': hyundai sonata hybrid sedan 2012 '134': hyundai elantra sedan 2007 '135': hyundai accent sedan 2012 '136': hyundai genesis sedan 2012 '137': hyundai sonata sedan 2012 '138': hyundai elantra touring hatchback 2012 '139': hyundai azera sedan 2012 '140': infiniti g coupe ipl 2012 '141': infiniti qx56 suv 2011 '142': isuzu ascender suv 2008 '143': jaguar xk xkr 2012 '144': jeep patriot suv 2012 '145': jeep wrangler suv 2012 '146': jeep liberty suv 2012 '147': jeep grand cherokee suv 2012 '148': jeep compass suv 2012 '149': lamborghini reventon coupe 2008 '150': lamborghini aventador coupe 2012 '151': lamborghini gallardo lp 570-4 superleggera 2012 '152': lamborghini diablo coupe 2001 '153': land rover range rover suv 2012 '154': land rover lr2 suv 2012 '155': lincoln town car sedan 2011 '156': mini cooper roadster convertible 2012 '157': maybach landaulet convertible 2012 '158': mazda tribute suv 2011 '159': mclaren mp4-12c coupe 2012 '160': mercedes-benz 300-class convertible 1993 '161': mercedes-benz c-class sedan 2012 '162': mercedes-benz sl-class coupe 2009 '163': mercedes-benz e-class sedan 2012 '164': mercedes-benz s-class sedan 2012 '165': mercedes-benz sprinter van 2012 '166': mitsubishi lancer sedan 2012 '167': nissan leaf hatchback 2012 '168': nissan nv passenger van 2012 '169': nissan juke hatchback 2012 '170': nissan 240sx coupe 1998 '171': plymouth neon coupe 1999 '172': porsche panamera sedan 2012 '173': ram c/v cargo van minivan 2012 '174': rolls-royce phantom drophead coupe convertible 2012 '175': rolls-royce ghost sedan 2012 '176': rolls-royce phantom sedan 2012 '177': scion xd hatchback 2012 '178': spyker c8 convertible 2009 '179': spyker c8 coupe 2009 '180': suzuki aerio sedan 2007 '181': suzuki kizashi sedan 2012 '182': suzuki sx4 hatchback 2012 '183': suzuki sx4 sedan 2012 '184': tesla model s sedan 2012 '185': toyota sequoia suv 2012 '186': toyota camry sedan 2012 '187': toyota corolla sedan 2012 '188': toyota 4runner suv 2012 '189': volkswagen golf hatchback 2012 '190': volkswagen golf hatchback 1991 '191': volkswagen beetle hatchback 2012 '192': volvo c30 hatchback 2012 '193': volvo 240 sedan 1993 '194': volvo xc90 suv 2007 '195': smart fortwo convertible 2012 - name: id dtype: int64 - name: clip_tags_ViT_L_14 sequence: string - name: LLM_Description_opt175b_downstream_tasks_ViT_L_14 sequence: string - name: LLM_Description_gpt3_downstream_tasks_ViT_L_14 sequence: string - name: LLM_Description_gpt3_downstream_tasks_visual_genome_ViT_L_14 sequence: string - name: blip_caption_beam_5 dtype: string - name: Attributes_ViT_L_14_text_davinci_003_full sequence: string - name: Attributes_ViT_L_14_text_davinci_003_stanfordcars sequence: string - name: clip_tags_ViT_L_14_with_openai_classes sequence: string - name: clip_tags_ViT_L_14_wo_openai_classes sequence: string - name: clip_tags_ViT_L_14_simple_specific dtype: string - name: clip_tags_ViT_L_14_ensemble_specific dtype: string - name: clip_tags_ViT_B_16_simple_specific dtype: string - name: clip_tags_ViT_B_16_ensemble_specific dtype: string - name: clip_tags_ViT_B_32_simple_specific dtype: string - name: clip_tags_ViT_B_32_ensemble_specific dtype: string - name: Attributes_ViT_B_16_descriptors_text_davinci_003_full sequence: string - name: Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full sequence: string - name: clip_tags_LAION_ViT_H_14_2B_simple_specific dtype: string - name: clip_tags_LAION_ViT_H_14_2B_ensemble_specific dtype: string - name: Attributes_ViT_L_14_descriptors_text_davinci_003_full sequence: string splits: - name: test num_bytes: 1016320238.0 num_examples: 8041 download_size: 989991348 dataset_size: 1016320238.0 --- # Dataset Card for "StanfordCars_test" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
kpriyanshu256/MultiTabQA-multitable_pretraining-Salesforce-codet5-base_train-latex-39000
--- dataset_info: features: - name: input_ids sequence: sequence: int32 - name: attention_mask sequence: sequence: int8 - name: labels sequence: sequence: int64 splits: - name: train num_bytes: 13336000 num_examples: 1000 download_size: 1053437 dataset_size: 13336000 configs: - config_name: default data_files: - split: train path: data/train-* ---
liuyanchen1015/MULTI_VALUE_cola_zero_plural
--- dataset_info: features: - name: sentence dtype: string - name: label dtype: int64 - name: idx dtype: int64 - name: value_score dtype: int64 splits: - name: dev num_bytes: 14427 num_examples: 194 - name: test num_bytes: 14640 num_examples: 192 - name: train num_bytes: 114261 num_examples: 1495 download_size: 73109 dataset_size: 143328 --- # Dataset Card for "MULTI_VALUE_cola_zero_plural" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Mitsuki-Sakamoto/alpaca_farm-deberta-re-pref-64-_fil_self_160m_bo2_100_kl_0.1_prm_70m_thr_0.3_seed_3
--- dataset_info: config_name: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1 features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: preference dtype: int64 - name: output_1 dtype: string - name: output_2 dtype: string - name: reward_model_prompt_format dtype: string - name: gen_prompt_format dtype: string - name: gen_kwargs struct: - name: do_sample dtype: bool - name: max_new_tokens dtype: int64 - name: pad_token_id dtype: int64 - name: top_k dtype: int64 - name: top_p dtype: float64 - name: reward_1 dtype: float64 - name: reward_2 dtype: float64 - name: n_samples dtype: int64 - name: reject_select dtype: string - name: prompt dtype: string - name: chosen dtype: string - name: rejected dtype: string - name: index dtype: int64 - name: filtered_epoch dtype: int64 - name: gen_reward dtype: float64 - name: gen_response dtype: string splits: - name: epoch_0 num_bytes: 43586042 num_examples: 18929 - name: epoch_1 num_bytes: 44099890 num_examples: 18929 - name: epoch_2 num_bytes: 44209292 num_examples: 18929 - name: epoch_3 num_bytes: 44251605 num_examples: 18929 - name: epoch_4 num_bytes: 44274741 num_examples: 18929 - name: epoch_5 num_bytes: 44289273 num_examples: 18929 - name: epoch_6 num_bytes: 44296482 num_examples: 18929 - name: epoch_7 num_bytes: 44303398 num_examples: 18929 - name: epoch_8 num_bytes: 44306950 num_examples: 18929 - name: epoch_9 num_bytes: 44308769 num_examples: 18929 - name: epoch_10 num_bytes: 44311035 num_examples: 18929 - name: epoch_11 num_bytes: 44310924 num_examples: 18929 - name: epoch_12 num_bytes: 44312195 num_examples: 18929 - name: epoch_13 num_bytes: 44313444 num_examples: 18929 - name: epoch_14 num_bytes: 44313855 num_examples: 18929 - name: epoch_15 num_bytes: 44313210 num_examples: 18929 - name: epoch_16 num_bytes: 44314927 num_examples: 18929 - name: epoch_17 num_bytes: 44315070 num_examples: 18929 - name: epoch_18 num_bytes: 44315919 num_examples: 18929 - name: epoch_19 num_bytes: 44315408 num_examples: 18929 - name: epoch_20 num_bytes: 44315491 num_examples: 18929 - name: epoch_21 num_bytes: 44316046 num_examples: 18929 - name: epoch_22 num_bytes: 44315262 num_examples: 18929 - name: epoch_23 num_bytes: 44315781 num_examples: 18929 - name: epoch_24 num_bytes: 44316326 num_examples: 18929 - name: epoch_25 num_bytes: 44315765 num_examples: 18929 - name: epoch_26 num_bytes: 44316179 num_examples: 18929 - name: epoch_27 num_bytes: 44316692 num_examples: 18929 - name: epoch_28 num_bytes: 44316878 num_examples: 18929 - name: epoch_29 num_bytes: 44317006 num_examples: 18929 download_size: 699305585 dataset_size: 1328223855 configs: - config_name: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1 data_files: - split: epoch_0 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_0-* - split: epoch_1 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_1-* - split: epoch_2 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_2-* - split: epoch_3 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_3-* - split: epoch_4 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_4-* - split: epoch_5 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_5-* - split: epoch_6 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_6-* - split: epoch_7 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_7-* - split: epoch_8 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_8-* - split: epoch_9 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_9-* - split: epoch_10 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_10-* - split: epoch_11 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_11-* - split: epoch_12 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_12-* - split: epoch_13 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_13-* - split: epoch_14 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_14-* - split: epoch_15 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_15-* - split: epoch_16 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_16-* - split: epoch_17 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_17-* - split: epoch_18 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_18-* - split: epoch_19 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_19-* - split: epoch_20 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_20-* - split: epoch_21 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_21-* - split: epoch_22 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_22-* - split: epoch_23 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_23-* - split: epoch_24 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_24-* - split: epoch_25 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_25-* - split: epoch_26 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_26-* - split: epoch_27 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_27-* - split: epoch_28 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_28-* - split: epoch_29 path: alpaca_instructions-pythia_160m_alpaca_farm_instructions_sft_constant_pa_seed_1/epoch_29-* ---
oreva/squad_30_percent_pruned_by_ppl_gpt2-medium
--- configs: - config_name: default data_files: - split: top_ppl path: data/top_ppl-* - split: bottom_ppl path: data/bottom_ppl-* dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers struct: - name: answer_start sequence: int32 - name: text sequence: string - name: prompt dtype: string - name: ppl_gpt2-medium dtype: float64 splits: - name: top_ppl num_bytes: 42784619 num_examples: 23126 - name: bottom_ppl num_bytes: 38869155 num_examples: 23126 download_size: 49882177 dataset_size: 81653774 --- # Dataset Card for "squad_30_percent_pruned_by_ppl_gpt2-medium" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ywan111/macbook-dataset
--- license: apache-2.0 dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 82755.0 num_examples: 1 download_size: 83469 dataset_size: 82755.0 ---
bodonodon/colabunny
--- license: afl-3.0 ---
ytzi/the-stack-dedup-python-scored
--- dataset_info: config_name: python features: - name: hexsha dtype: string - name: size dtype: int64 - name: ext dtype: string - name: lang dtype: string - name: max_stars_repo_path dtype: string - name: max_stars_repo_name dtype: string - name: max_stars_repo_head_hexsha dtype: string - name: max_stars_repo_licenses sequence: string - name: max_stars_count dtype: int64 - name: max_stars_repo_stars_event_min_datetime dtype: string - name: max_stars_repo_stars_event_max_datetime dtype: string - name: max_issues_repo_path dtype: string - name: max_issues_repo_name dtype: string - name: max_issues_repo_head_hexsha dtype: string - name: max_issues_repo_licenses sequence: string - name: max_issues_count dtype: int64 - name: max_issues_repo_issues_event_min_datetime dtype: string - name: max_issues_repo_issues_event_max_datetime dtype: string - name: max_forks_repo_path dtype: string - name: max_forks_repo_name dtype: string - name: max_forks_repo_head_hexsha dtype: string - name: max_forks_repo_licenses sequence: string - name: max_forks_count dtype: int64 - name: max_forks_repo_forks_event_min_datetime dtype: string - name: max_forks_repo_forks_event_max_datetime dtype: string - name: content dtype: string - name: avg_line_length dtype: float64 - name: max_line_length dtype: int64 - name: alphanum_fraction dtype: float64 - name: count_classes dtype: int64 - name: score_classes dtype: float64 - name: count_generators dtype: int64 - name: score_generators dtype: float64 - name: count_decorators dtype: int64 - name: score_decorators dtype: float64 - name: count_async_functions dtype: int64 - name: score_async_functions dtype: float64 - name: count_documentation dtype: int64 - name: score_documentation dtype: float64 splits: - name: train num_bytes: 72919338116 num_examples: 12962249 download_size: 28959409073 dataset_size: 72919338116 configs: - config_name: python data_files: - split: train path: python/train-* ---
ASIDS/alpaca-cleaned-ru
--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string - name: iteration dtype: uint32 splits: - name: train num_bytes: 74829755.0 num_examples: 51760 download_size: 36596664 dataset_size: 74829755.0 license: cc-by-4.0 language: - ru multilinguality: - monolingual tags: - instruction-finetuning pretty_name: alpaca-cleaned-ru task_categories: - text-generation size_categories: - 10K<n<100K source_datasets: - yahma/alpaca-cleaned language_creators: - translated --- # alpaca-cleaned-ru converter for autotrain from [d0rj/alpaca-cleaned-ru](https://huggingface.co/datasets/d0rj/alpaca-cleaned-ru) Translated version of [yahma/alpaca-cleaned](https://huggingface.co/datasets/yahma/alpaca-cleaned) into Russian. ## Dataset Description - **Repository:** https://github.com/gururise/AlpacaDataCleaned - **Repository:** https://huggingface.co/datasets/d0rj/alpaca-cleaned-ru
ShankarSaumil/ArakooAI_Task_Flan-v2
--- dataset_info: features: - name: inputs dtype: string - name: targets dtype: string - name: task_source dtype: string - name: task_name dtype: string - name: template_type dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 351820999.11881727 num_examples: 212520 - name: validation num_bytes: 476643.24302443425 num_examples: 257 download_size: 847814029 dataset_size: 352297642.3618417 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---
Saulons3/cocina_final
--- license: apache-2.0 dataset_info: features: - name: column0 dtype: string - name: column1 dtype: string splits: - name: train num_bytes: 40574 num_examples: 121 download_size: 21456 dataset_size: 40574 configs: - config_name: default data_files: - split: train path: data/train-* ---
Eduardovco/edu2
--- license: openrail ---
tianleliphoebe/DreamEditBench
--- license: cc-by-4.0 task_categories: - image-to-image - text-to-image language: - en size_categories: - n<1K --- ## DreamEditBench for Subject Replacement task and Subject Addition task. ## Dataset Description - **Homepage:** https://dreameditbenchteam.github.io - **Repository:** https://github.com/DreamEditBenchTeam/DreamEdit <!-- **Paper:** https://arxiv.org/abs/2306.12624 --> The goal of subject replacement is to replace a subject from a source image with a customized subject. In contrast, the aim of the subject addition task is to add a customized subject to a desired position in the source image. To standardize the evaluation of the two proposed tasks, we curate a new benchmark, i.e. DreamEditBench, consisting of 22 subjects in alignment with DreamBooth with 20 images for each subject correspondingly. For the subject replacement task, we collect 10 images for each type, which include same-typed source subjects in diverse environments. The images are retrieved from the internet with the search query “a photo of [Class name]”, and the source subject should be the main subject in the image which dominates a major part of the photo. For the subject addition task, we collect 10 reasonable backgrounds for each type of subject. In the meantime, we manually designate the specific location the target subject should be placed with a bounding box in the background. To collect the specific backgrounds for each subject, we first brainstorm and list the possible common environments of the subjects, then we search the listed keywords from the internet to retrieve and pick the backgrounds ## Data Structure There are 22 subject folders in each task folder respectively. In each subject folder, there are 10 source images. For Subject Addition task, there is an additional bbox.json file recording the manually labeled bounding box for each background. The replacement_subset.csv and addition_subset.csv record the easy/hard subset division for each task correspondingly. ## Citation Information If you find this dataset useful, please consider citing our paper: ``` @misc{li2023dreamedit, title={DreamEdit: Subject-driven Image Editing}, author={Tianle Li and Max Ku and Cong Wei and Wenhu Chen}, year={2023}, eprint={2306.12624}, archivePrefix={arXiv}, primaryClass={cs.CV} } ```
Veector2312/osmar1
--- license: openrail ---
Seanxh/twitter_dataset_1713132324
--- 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: 21488 num_examples: 53 download_size: 13718 dataset_size: 21488 configs: - config_name: default data_files: - split: train path: data/train-* ---
DZN111/test
--- license: openrail ---
distilled-from-one-sec-cv12/chunk_217
--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1133607480 num_examples: 220890 download_size: 1159089868 dataset_size: 1133607480 --- # Dataset Card for "chunk_217" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
leemeng/ShareGPT90K_ja_1392
--- license: cc0-1.0 dataset_info: features: - name: id dtype: string - name: conversations list: - name: from dtype: string - name: value dtype: string splits: - name: train num_bytes: 24698698 num_examples: 1392 download_size: 8804954 dataset_size: 24698698 ---
davanstrien/cosmopedia_chat
--- dataset_info: features: - name: prompt dtype: string - name: text_token_length dtype: int64 - name: text dtype: string - name: seed_data dtype: string - name: format dtype: string - name: audience dtype: string - name: title dtype: string - name: generated_text dtype: string splits: - name: train num_bytes: 5362254 num_examples: 1188 download_size: 1902915 dataset_size: 5362254 configs: - config_name: default data_files: - split: train path: data/train-* task_categories: - text-generation language: - en tags: - synthetic pretty_name: Cosmopedia Chat size_categories: - 1K<n<10K --- # Dataset Card for Cosmopedia Chat <p align="center"> <img src="https://cdn-uploads.huggingface.co/production/uploads/60107b385ac3e86b3ea4fc34/6mMBW7gBurVT6kYpjX9L8.png" alt="Your Image" width="500"> </p> ## Dataset Details ### Dataset Description Docs are WIP! Rough steps to produce this data. - Start with [HuggingFaceTB/cosmopedia](https://huggingface.co/datasets/HuggingFaceTB/cosmopedia) dataset - Select `khanacademy` config - filter by text length - remove some examples with certain text i.e. responses starting with "sure" - Extract a title from the original prompt in the dataset - Pass titlte + text to [NousResearch/Genstruct-7B](https://huggingface.co/NousResearch/Genstruct-7B) to create user/chat pairs from this title + text context - Profit?? TODO: - More curation of what data is included to start. Some of the Cosmpoedia data is not very "stand alone" - Try and remove topics that are unlikely to be useful for chat data - Remove bad generations - Parse generations into users/assistant chat format.
justinian336/salvadoran-news-edh
--- dataset_info: features: - name: image_src dtype: string - name: title dtype: string - name: content dtype: string - name: category dtype: class_label: names: '0': opinion '1': noticias '2': videos '3': entretenimiento '4': vida '5': deportes/zona-mundialista '6': opinion/caricaturas '7': fotogalerias '8': null '9': deportes - name: link dtype: string splits: - name: train num_bytes: 196407515 num_examples: 55345 download_size: 111585522 dataset_size: 196407515 --- # Dataset Card for "salvadoran-news-edh" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
irds/mmarco_v2_es_dev
--- pretty_name: '`mmarco/v2/es/dev`' viewer: false source_datasets: ['irds/mmarco_v2_es'] task_categories: - text-retrieval --- # Dataset Card for `mmarco/v2/es/dev` The `mmarco/v2/es/dev` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package. For more information about the dataset, see the [documentation](https://ir-datasets.com/mmarco#mmarco/v2/es/dev). # Data This dataset provides: - `queries` (i.e., topics); count=101,093 - `qrels`: (relevance assessments); count=59,273 - For `docs`, use [`irds/mmarco_v2_es`](https://huggingface.co/datasets/irds/mmarco_v2_es) ## Usage ```python from datasets import load_dataset queries = load_dataset('irds/mmarco_v2_es_dev', 'queries') for record in queries: record # {'query_id': ..., 'text': ...} qrels = load_dataset('irds/mmarco_v2_es_dev', 'qrels') for record in qrels: record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...} ``` Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the data in 🤗 Dataset format. ## Citation Information ``` @article{Bonifacio2021MMarco, title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset}, author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira}, year={2021}, journal={arXiv:2108.13897} } ```
open-llm-leaderboard/details_TW3Partners__testmerge-7b
--- pretty_name: Evaluation run of TW3Partners/testmerge-7b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [TW3Partners/testmerge-7b](https://huggingface.co/TW3Partners/testmerge-7b) on\ \ the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_TW3Partners__testmerge-7b\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-04-15T11:52:55.740432](https://huggingface.co/datasets/open-llm-leaderboard/details_TW3Partners__testmerge-7b/blob/main/results_2024-04-15T11-52-55.740432.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\": 0.6471497788929994,\n\ \ \"acc_stderr\": 0.03215584016671172,\n \"acc_norm\": 0.6466881410376628,\n\ \ \"acc_norm_stderr\": 0.032826608517522254,\n \"mc1\": 0.6217870257037944,\n\ \ \"mc1_stderr\": 0.016976335907546863,\n \"mc2\": 0.7466999166295964,\n\ \ \"mc2_stderr\": 0.014498007351803632\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.7226962457337884,\n \"acc_stderr\": 0.013082095839059374,\n\ \ \"acc_norm\": 0.7414675767918089,\n \"acc_norm_stderr\": 0.012794553754288692\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7349133638717387,\n\ \ \"acc_stderr\": 0.0044047727357659884,\n \"acc_norm\": 0.8937462656841266,\n\ \ \"acc_norm_stderr\": 0.0030753230104084216\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.6222222222222222,\n\ \ \"acc_stderr\": 0.04188307537595853,\n \"acc_norm\": 0.6222222222222222,\n\ \ \"acc_norm_stderr\": 0.04188307537595853\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6644736842105263,\n \"acc_stderr\": 0.038424985593952694,\n\ \ \"acc_norm\": 0.6644736842105263,\n \"acc_norm_stderr\": 0.038424985593952694\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.63,\n\ \ \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\": 0.63,\n \ \ \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.690566037735849,\n \"acc_stderr\": 0.028450154794118637,\n\ \ \"acc_norm\": 0.690566037735849,\n \"acc_norm_stderr\": 0.028450154794118637\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7708333333333334,\n\ \ \"acc_stderr\": 0.03514697467862388,\n \"acc_norm\": 0.7708333333333334,\n\ \ \"acc_norm_stderr\": 0.03514697467862388\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.52,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.52,\n \"acc_norm_stderr\": 0.050211673156867795\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\": 0.28,\n \"acc_stderr\": 0.04512608598542127,\n \ \ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542127\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.630057803468208,\n\ \ \"acc_stderr\": 0.0368122963339432,\n \"acc_norm\": 0.630057803468208,\n\ \ \"acc_norm_stderr\": 0.0368122963339432\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3627450980392157,\n \"acc_stderr\": 0.047840607041056527,\n\ \ \"acc_norm\": 0.3627450980392157,\n \"acc_norm_stderr\": 0.047840607041056527\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.74,\n \"acc_stderr\": 0.04408440022768078,\n \"acc_norm\": 0.74,\n\ \ \"acc_norm_stderr\": 0.04408440022768078\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5617021276595745,\n \"acc_stderr\": 0.03243618636108102,\n\ \ \"acc_norm\": 0.5617021276595745,\n \"acc_norm_stderr\": 0.03243618636108102\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.49122807017543857,\n\ \ \"acc_stderr\": 0.04702880432049615,\n \"acc_norm\": 0.49122807017543857,\n\ \ \"acc_norm_stderr\": 0.04702880432049615\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5448275862068965,\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\"\ : 0.40476190476190477,\n \"acc_stderr\": 0.025279850397404904,\n \"\ acc_norm\": 0.40476190476190477,\n \"acc_norm_stderr\": 0.025279850397404904\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4523809523809524,\n\ \ \"acc_stderr\": 0.044518079590553275,\n \"acc_norm\": 0.4523809523809524,\n\ \ \"acc_norm_stderr\": 0.044518079590553275\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621505,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621505\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7967741935483871,\n\ \ \"acc_stderr\": 0.022891687984554952,\n \"acc_norm\": 0.7967741935483871,\n\ \ \"acc_norm_stderr\": 0.022891687984554952\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.5172413793103449,\n \"acc_stderr\": 0.035158955511656986,\n\ \ \"acc_norm\": 0.5172413793103449,\n \"acc_norm_stderr\": 0.035158955511656986\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.72,\n \"acc_stderr\": 0.04512608598542127,\n \"acc_norm\"\ : 0.72,\n \"acc_norm_stderr\": 0.04512608598542127\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7515151515151515,\n \"acc_stderr\": 0.03374402644139402,\n\ \ \"acc_norm\": 0.7515151515151515,\n \"acc_norm_stderr\": 0.03374402644139402\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.803030303030303,\n \"acc_stderr\": 0.028335609732463362,\n \"\ acc_norm\": 0.803030303030303,\n \"acc_norm_stderr\": 0.028335609732463362\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8963730569948186,\n \"acc_stderr\": 0.02199531196364424,\n\ \ \"acc_norm\": 0.8963730569948186,\n \"acc_norm_stderr\": 0.02199531196364424\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6564102564102564,\n \"acc_stderr\": 0.024078696580635477,\n\ \ \"acc_norm\": 0.6564102564102564,\n \"acc_norm_stderr\": 0.024078696580635477\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.3111111111111111,\n \"acc_stderr\": 0.028226446749683512,\n \ \ \"acc_norm\": 0.3111111111111111,\n \"acc_norm_stderr\": 0.028226446749683512\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\"\ : 0.36423841059602646,\n \"acc_stderr\": 0.03929111781242742,\n \"\ acc_norm\": 0.36423841059602646,\n \"acc_norm_stderr\": 0.03929111781242742\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\"\ : 0.8235294117647058,\n \"acc_stderr\": 0.026756401538078966,\n \"\ acc_norm\": 0.8235294117647058,\n \"acc_norm_stderr\": 0.026756401538078966\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8016877637130801,\n \"acc_stderr\": 0.02595502084162113,\n \ \ \"acc_norm\": 0.8016877637130801,\n \"acc_norm_stderr\": 0.02595502084162113\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6860986547085202,\n\ \ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.6860986547085202,\n\ \ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.8015267175572519,\n \"acc_stderr\": 0.034981493854624714,\n\ \ \"acc_norm\": 0.8015267175572519,\n \"acc_norm_stderr\": 0.034981493854624714\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.768595041322314,\n \"acc_stderr\": 0.038498560987940904,\n \"\ acc_norm\": 0.768595041322314,\n \"acc_norm_stderr\": 0.038498560987940904\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7962962962962963,\n\ \ \"acc_stderr\": 0.03893542518824847,\n \"acc_norm\": 0.7962962962962963,\n\ \ \"acc_norm_stderr\": 0.03893542518824847\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.754601226993865,\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\": 0.42857142857142855,\n\ \ \"acc_stderr\": 0.04697113923010212,\n \"acc_norm\": 0.42857142857142855,\n\ \ \"acc_norm_stderr\": 0.04697113923010212\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7864077669902912,\n \"acc_stderr\": 0.040580420156460344,\n\ \ \"acc_norm\": 0.7864077669902912,\n \"acc_norm_stderr\": 0.040580420156460344\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8803418803418803,\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\": 0.68,\n \"acc_stderr\": 0.04688261722621504,\n \ \ \"acc_norm\": 0.68,\n \"acc_norm_stderr\": 0.04688261722621504\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8237547892720306,\n\ \ \"acc_stderr\": 0.013625556907993464,\n \"acc_norm\": 0.8237547892720306,\n\ \ \"acc_norm_stderr\": 0.013625556907993464\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\": 0.4324022346368715,\n\ \ \"acc_stderr\": 0.01656897123354861,\n \"acc_norm\": 0.4324022346368715,\n\ \ \"acc_norm_stderr\": 0.01656897123354861\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7287581699346405,\n \"acc_stderr\": 0.025457756696667874,\n\ \ \"acc_norm\": 0.7287581699346405,\n \"acc_norm_stderr\": 0.025457756696667874\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7106109324758842,\n\ \ \"acc_stderr\": 0.025755865922632945,\n \"acc_norm\": 0.7106109324758842,\n\ \ \"acc_norm_stderr\": 0.025755865922632945\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7407407407407407,\n \"acc_stderr\": 0.024383665531035454,\n\ \ \"acc_norm\": 0.7407407407407407,\n \"acc_norm_stderr\": 0.024383665531035454\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.5035460992907801,\n \"acc_stderr\": 0.02982674915328092,\n \ \ \"acc_norm\": 0.5035460992907801,\n \"acc_norm_stderr\": 0.02982674915328092\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.46284224250325945,\n\ \ \"acc_stderr\": 0.012734923579532069,\n \"acc_norm\": 0.46284224250325945,\n\ \ \"acc_norm_stderr\": 0.012734923579532069\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6764705882352942,\n \"acc_stderr\": 0.028418208619406755,\n\ \ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.028418208619406755\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6666666666666666,\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\": 0.6545454545454545,\n\ \ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\ \ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7183673469387755,\n \"acc_stderr\": 0.028795185574291293,\n\ \ \"acc_norm\": 0.7183673469387755,\n \"acc_norm_stderr\": 0.028795185574291293\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8308457711442786,\n\ \ \"acc_stderr\": 0.02650859065623327,\n \"acc_norm\": 0.8308457711442786,\n\ \ \"acc_norm_stderr\": 0.02650859065623327\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.03588702812826371,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.03588702812826371\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5662650602409639,\n\ \ \"acc_stderr\": 0.03858158940685516,\n \"acc_norm\": 0.5662650602409639,\n\ \ \"acc_norm_stderr\": 0.03858158940685516\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8245614035087719,\n \"acc_stderr\": 0.029170885500727665,\n\ \ \"acc_norm\": 0.8245614035087719,\n \"acc_norm_stderr\": 0.029170885500727665\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.6217870257037944,\n\ \ \"mc1_stderr\": 0.016976335907546863,\n \"mc2\": 0.7466999166295964,\n\ \ \"mc2_stderr\": 0.014498007351803632\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8531965272296764,\n \"acc_stderr\": 0.009946627440250676\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6459438968915845,\n \ \ \"acc_stderr\": 0.01317272838522258\n }\n}\n```" repo_url: https://huggingface.co/TW3Partners/testmerge-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: 2024_04_15T11_52_55.740432 path: - '**/details_harness|arc:challenge|25_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-04-15T11-52-55.740432.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|gsm8k|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hellaswag|10_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-management|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-management|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-04-15T11-52-55.740432.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-international_law|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-management|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-marketing|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-sociology|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-virology|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-04-15T11-52-55.740432.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|truthfulqa:mc|0_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-04-15T11-52-55.740432.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_04_15T11_52_55.740432 path: - '**/details_harness|winogrande|5_2024-04-15T11-52-55.740432.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-04-15T11-52-55.740432.parquet' - config_name: results data_files: - split: 2024_04_15T11_52_55.740432 path: - results_2024-04-15T11-52-55.740432.parquet - split: latest path: - results_2024-04-15T11-52-55.740432.parquet --- # Dataset Card for Evaluation run of TW3Partners/testmerge-7b <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [TW3Partners/testmerge-7b](https://huggingface.co/TW3Partners/testmerge-7b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_TW3Partners__testmerge-7b", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-04-15T11:52:55.740432](https://huggingface.co/datasets/open-llm-leaderboard/details_TW3Partners__testmerge-7b/blob/main/results_2024-04-15T11-52-55.740432.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": 0.6471497788929994, "acc_stderr": 0.03215584016671172, "acc_norm": 0.6466881410376628, "acc_norm_stderr": 0.032826608517522254, "mc1": 0.6217870257037944, "mc1_stderr": 0.016976335907546863, "mc2": 0.7466999166295964, "mc2_stderr": 0.014498007351803632 }, "harness|arc:challenge|25": { "acc": 0.7226962457337884, "acc_stderr": 0.013082095839059374, "acc_norm": 0.7414675767918089, "acc_norm_stderr": 0.012794553754288692 }, "harness|hellaswag|10": { "acc": 0.7349133638717387, "acc_stderr": 0.0044047727357659884, "acc_norm": 0.8937462656841266, "acc_norm_stderr": 0.0030753230104084216 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6222222222222222, "acc_stderr": 0.04188307537595853, "acc_norm": 0.6222222222222222, "acc_norm_stderr": 0.04188307537595853 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6644736842105263, "acc_stderr": 0.038424985593952694, "acc_norm": 0.6644736842105263, "acc_norm_stderr": 0.038424985593952694 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.63, "acc_stderr": 0.04852365870939099, "acc_norm": 0.63, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.690566037735849, "acc_stderr": 0.028450154794118637, "acc_norm": 0.690566037735849, "acc_norm_stderr": 0.028450154794118637 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7708333333333334, "acc_stderr": 0.03514697467862388, "acc_norm": 0.7708333333333334, "acc_norm_stderr": 0.03514697467862388 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "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": 0.28, "acc_stderr": 0.04512608598542127, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542127 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.630057803468208, "acc_stderr": 0.0368122963339432, "acc_norm": 0.630057803468208, "acc_norm_stderr": 0.0368122963339432 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3627450980392157, "acc_stderr": 0.047840607041056527, "acc_norm": 0.3627450980392157, "acc_norm_stderr": 0.047840607041056527 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.74, "acc_stderr": 0.04408440022768078, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768078 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5617021276595745, "acc_stderr": 0.03243618636108102, "acc_norm": 0.5617021276595745, "acc_norm_stderr": 0.03243618636108102 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.49122807017543857, "acc_stderr": 0.04702880432049615, "acc_norm": 0.49122807017543857, "acc_norm_stderr": 0.04702880432049615 }, "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": 0.40476190476190477, "acc_stderr": 0.025279850397404904, "acc_norm": 0.40476190476190477, "acc_norm_stderr": 0.025279850397404904 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4523809523809524, "acc_stderr": 0.044518079590553275, "acc_norm": 0.4523809523809524, "acc_norm_stderr": 0.044518079590553275 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.32, "acc_stderr": 0.04688261722621505, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7967741935483871, "acc_stderr": 0.022891687984554952, "acc_norm": 0.7967741935483871, "acc_norm_stderr": 0.022891687984554952 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5172413793103449, "acc_stderr": 0.035158955511656986, "acc_norm": 0.5172413793103449, "acc_norm_stderr": 0.035158955511656986 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.72, "acc_stderr": 0.04512608598542127, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542127 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7515151515151515, "acc_stderr": 0.03374402644139402, "acc_norm": 0.7515151515151515, "acc_norm_stderr": 0.03374402644139402 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.803030303030303, "acc_stderr": 0.028335609732463362, "acc_norm": 0.803030303030303, "acc_norm_stderr": 0.028335609732463362 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8963730569948186, "acc_stderr": 0.02199531196364424, "acc_norm": 0.8963730569948186, "acc_norm_stderr": 0.02199531196364424 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6564102564102564, "acc_stderr": 0.024078696580635477, "acc_norm": 0.6564102564102564, "acc_norm_stderr": 0.024078696580635477 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3111111111111111, "acc_stderr": 0.028226446749683512, "acc_norm": 0.3111111111111111, "acc_norm_stderr": 0.028226446749683512 }, "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": 0.36423841059602646, "acc_stderr": 0.03929111781242742, "acc_norm": 0.36423841059602646, "acc_norm_stderr": 0.03929111781242742 }, "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": 0.8235294117647058, "acc_stderr": 0.026756401538078966, "acc_norm": 0.8235294117647058, "acc_norm_stderr": 0.026756401538078966 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8016877637130801, "acc_stderr": 0.02595502084162113, "acc_norm": 0.8016877637130801, "acc_norm_stderr": 0.02595502084162113 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6860986547085202, "acc_stderr": 0.031146796482972465, "acc_norm": 0.6860986547085202, "acc_norm_stderr": 0.031146796482972465 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.8015267175572519, "acc_stderr": 0.034981493854624714, "acc_norm": 0.8015267175572519, "acc_norm_stderr": 0.034981493854624714 }, "harness|hendrycksTest-international_law|5": { "acc": 0.768595041322314, "acc_stderr": 0.038498560987940904, "acc_norm": 0.768595041322314, "acc_norm_stderr": 0.038498560987940904 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7962962962962963, "acc_stderr": 0.03893542518824847, "acc_norm": 0.7962962962962963, "acc_norm_stderr": 0.03893542518824847 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.754601226993865, "acc_stderr": 0.03380939813943354, "acc_norm": 0.754601226993865, "acc_norm_stderr": 0.03380939813943354 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.42857142857142855, "acc_stderr": 0.04697113923010212, "acc_norm": 0.42857142857142855, "acc_norm_stderr": 0.04697113923010212 }, "harness|hendrycksTest-management|5": { "acc": 0.7864077669902912, "acc_stderr": 0.040580420156460344, "acc_norm": 0.7864077669902912, "acc_norm_stderr": 0.040580420156460344 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8803418803418803, "acc_stderr": 0.021262719400406957, "acc_norm": 0.8803418803418803, "acc_norm_stderr": 0.021262719400406957 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.68, "acc_stderr": 0.04688261722621504, "acc_norm": 0.68, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8237547892720306, "acc_stderr": 0.013625556907993464, "acc_norm": 0.8237547892720306, "acc_norm_stderr": 0.013625556907993464 }, "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": 0.4324022346368715, "acc_stderr": 0.01656897123354861, "acc_norm": 0.4324022346368715, "acc_norm_stderr": 0.01656897123354861 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7287581699346405, "acc_stderr": 0.025457756696667874, "acc_norm": 0.7287581699346405, "acc_norm_stderr": 0.025457756696667874 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7106109324758842, "acc_stderr": 0.025755865922632945, "acc_norm": 0.7106109324758842, "acc_norm_stderr": 0.025755865922632945 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7407407407407407, "acc_stderr": 0.024383665531035454, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.024383665531035454 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.5035460992907801, "acc_stderr": 0.02982674915328092, "acc_norm": 0.5035460992907801, "acc_norm_stderr": 0.02982674915328092 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.46284224250325945, "acc_stderr": 0.012734923579532069, "acc_norm": 0.46284224250325945, "acc_norm_stderr": 0.012734923579532069 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6764705882352942, "acc_stderr": 0.028418208619406755, "acc_norm": 0.6764705882352942, "acc_norm_stderr": 0.028418208619406755 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6666666666666666, "acc_stderr": 0.019070985589687495, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.019070985589687495 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6545454545454545, "acc_stderr": 0.04554619617541054, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.04554619617541054 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7183673469387755, "acc_stderr": 0.028795185574291293, "acc_norm": 0.7183673469387755, "acc_norm_stderr": 0.028795185574291293 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8308457711442786, "acc_stderr": 0.02650859065623327, "acc_norm": 0.8308457711442786, "acc_norm_stderr": 0.02650859065623327 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.85, "acc_stderr": 0.03588702812826371, "acc_norm": 0.85, "acc_norm_stderr": 0.03588702812826371 }, "harness|hendrycksTest-virology|5": { "acc": 0.5662650602409639, "acc_stderr": 0.03858158940685516, "acc_norm": 0.5662650602409639, "acc_norm_stderr": 0.03858158940685516 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8245614035087719, "acc_stderr": 0.029170885500727665, "acc_norm": 0.8245614035087719, "acc_norm_stderr": 0.029170885500727665 }, "harness|truthfulqa:mc|0": { "mc1": 0.6217870257037944, "mc1_stderr": 0.016976335907546863, "mc2": 0.7466999166295964, "mc2_stderr": 0.014498007351803632 }, "harness|winogrande|5": { "acc": 0.8531965272296764, "acc_stderr": 0.009946627440250676 }, "harness|gsm8k|5": { "acc": 0.6459438968915845, "acc_stderr": 0.01317272838522258 } } ``` ## 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]
MrM0dZ/Samples
--- license: openrail ---
Nexdata/48_Categories_307776_Images_of_Scene_Classification_Data
--- license: cc-by-nc-nd-4.0 --- ## Description 48 Categories - 307,776 Images of Scene Classification Data. The data diversity includes multiple scenes, different photographic angles. The dataset can be used for tasks such as scene classification. For more details, please refer to the link: https://www.nexdata.ai/dataset/1143?source=Huggingface ## Data size 48 categories, including 15 sub-categories, a total of 307,776 images ## Data diversity multiple scenes, different photographic angles ## Collecting time day, night ## Data format .jpg, .png, .jpeg ## Accuracy the accuracy of classification of image is more than 95% # Licensing Information Commercial License
adityarra07/train_24000
--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 - name: transcription dtype: string - name: id dtype: string splits: - name: train num_bytes: 3108325777.5861845 num_examples: 23322 - name: test num_bytes: 26655739.452758636 num_examples: 200 download_size: 3090623993 dataset_size: 3134981517.0389433 --- # Dataset Card for "train_24000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
kevinautomation/llme2_sft_dataset_rlaif_2
--- dataset_info: features: - name: prompt dtype: string - name: response dtype: string - name: text dtype: string splits: - name: train num_bytes: 6159 num_examples: 5 download_size: 11485 dataset_size: 6159 configs: - config_name: default data_files: - split: train path: data/train-* ---
dream
--- annotations_creators: - expert-generated language_creators: - expert-generated language: - en license: - unknown multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - question-answering task_ids: - multiple-choice-qa paperswithcode_id: dream pretty_name: DREAM dataset_info: features: - name: id dtype: int32 - name: dialogue_id dtype: string - name: dialogue sequence: string - name: question dtype: string - name: choice sequence: string - name: answer dtype: string config_name: plain_text splits: - name: train num_bytes: 4775235 num_examples: 6116 - name: validation num_bytes: 1539272 num_examples: 2040 - name: test num_bytes: 1556379 num_examples: 2041 download_size: 5558190 dataset_size: 7870886 --- # Dataset Card for DREAM ## 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:** [Add homepage URL here if available (unless it's a GitHub repository)]() - **Repository:** [If the dataset is hosted on github or has a github homepage, add URL here]() - **Paper:** [If the dataset was introduced by a paper or there was a paper written describing the dataset, add URL here (landing page for Arxiv paper preferred)]() - **Leaderboard:** [If the dataset supports an active leaderboard, add link here]() - **Point of Contact:** [If known, name and email of at least one person the reader can contact for questions about the dataset.]() ### 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 [More Information Needed] #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations [More Information Needed] #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset.
tolgadev/turkish_73k_instruct_extended
--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 46016105 num_examples: 73124 download_size: 23400866 dataset_size: 46016105 configs: - config_name: default data_files: - split: train path: data/train-* license: apache-2.0 task_categories: - text-generation - text2text-generation language: - tr size_categories: - 10K<n<100K --- ## turkish_73k_instruct_extended This repository describes a dataset compiled from Turkish instruction-based sources, structured using the LLama Instruct format. Feel free to use this dataset for training and fine-tuning Turkish large language models (LLMs). ⭐ ## Merged Datasets | DatasetName | Link | Licence | numRows | | ---- | ---- | ---- | ---- | | [merve/turkish_instructions](https://huggingface.co/datasets/merve/turkish_instructions) | https://huggingface.co/datasets/merve/turkish_instructions | apache-2.0 | 51.6k | | [tolgadev/ruyatabirleri_instruct](https://huggingface.co/datasets/tolgadev/ruyatabirleri_instruct) | https://huggingface.co/datasets/tolgadev/ruyatabirleri_instruct | apache-2.0 | 8.9k | | [mertbozkurt/llama2-TR-recipe](https://huggingface.co/datasets/mertbozkurt/llama2-TR-recipe) | https://huggingface.co/datasets/mertbozkurt/llama2-TR-recipe | mit | 10.5k | | [CausalLM/GPT-4-Self-Instruct-Turkish](https://huggingface.co/datasets/CausalLM/GPT-4-Self-Instruct-Turkish) | https://huggingface.co/datasets/CausalLM/GPT-4-Self-Instruct-Turkish | cc-by-4.0 | 3.08k | | [emre/stanford-alpaca-cleaned-turkish-translated](https://huggingface.co/datasets/emre/stanford-alpaca-cleaned-turkish-translated) | https://huggingface.co/datasets/emre/stanford-alpaca-cleaned-turkish-translated | afl-3.0 | -| ### Citation Please ensure to cite all the repositories listed above when using this dataset or code in this repo. ``` @misc{turkish_73k_instruct_extended author = {Kurtuluş, Tolga}, title = {turkish_73k_instruct_extended}, year = {2024}, publisher = {HuggingFace.co}, journal = {HuggingFace dataset repository}, howpublished = {\url{https://huggingface.co/datasets/tolgadev/turkish_73k_instruct_extended}}, } ```
awettig/Pile-ArXiv-0.5B-8K-opt
--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 6500715780 num_examples: 61035 - name: test num_bytes: 64969880 num_examples: 610 download_size: 1583362590 dataset_size: 6565685660 --- # Dataset Card for "Pile-ArXiv-0.5B-8K-opt" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Syed-Hasan-8503/tiny-codes-pretraining
--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 3580824575 num_examples: 1632309 download_size: 1680133396 dataset_size: 3580824575 configs: - config_name: default data_files: - split: train path: data/train-* ---
Kamyar-zeinalipour/AR_CW
--- dataset_info: features: - name: clue dtype: string - name: answer dtype: string splits: - name: train num_bytes: 2063175 num_examples: 57706 download_size: 1126121 dataset_size: 2063175 --- # Dataset Card for "AR_CW" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
giuseppemartino/i-SAID_custom_or_1
--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: image dtype: image - name: label dtype: image splits: - name: train num_bytes: 6362576122.0 num_examples: 840 - name: validation num_bytes: 905977299.0 num_examples: 99 download_size: 7262651438 dataset_size: 7268553421.0 --- # Dataset Card for "i-SAID_custom_or_1" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
saibo/bookcorpus_compact_256_test_meta
--- dataset_info: features: - name: text dtype: string - name: concept_with_offset dtype: string - name: cid_arrangement sequence: int32 - name: schema_lengths sequence: int64 - name: topic_entity_mask sequence: int64 - name: text_lengths sequence: int64 splits: - name: train num_bytes: 214680900 num_examples: 6160 download_size: 47705450 dataset_size: 214680900 --- # Dataset Card for "bookcorpus_compact_256_test_meta" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
pks3kor/medical_qa
--- configs: - config_name: default data_files: - split: train path: data.csv --- # Dataset Card for Dataset Name <!-- Provide a quick summary of the dataset. --> ## 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]
autoevaluate/autoeval-staging-eval-project-d60b4e7e-7574888
--- type: predictions tags: - autotrain - evaluation datasets: - xtreme eval_info: task: entity_extraction model: OneFly/xlm-roberta-base-finetuned-panx-de metrics: [] dataset_name: xtreme dataset_config: PAN-X.de dataset_split: test col_mapping: tokens: tokens tags: ner_tags --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Token Classification * Model: OneFly/xlm-roberta-base-finetuned-panx-de * Dataset: xtreme To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model.
jhhon80/jhhon
--- license: openrail ---
dura-garage/nep-spell-50k
--- license: mit ---
sheik21/lucas-vocals
--- license: openrail ---