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datasetId stringlengths 2 117	card stringlengths 19 1.01M
nikitam/ACES	--- language: - multilingual license: - cc-by-nc-sa-4.0 multilinguality: - multilingual source_datasets: - FLORES-101, FLORES-200, PAWS-X, XNLI, XTREME, WinoMT, Wino-X, MuCOW, EuroParl ConDisco, ParcorFull task_categories: - translation pretty_name: ACES configs: - config_name: ACES data_files: challenge_set.jsonl - config_name: Span-ACES data_files: span_aces.jsonl --- # Dataset Card for ACES and Span-ACES ## 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) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Discussion of Biases](#discussion-of-biases) - [Usage](#usage) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contact](#contact) ## Dataset Description - Repository: [ACES dataset repository](https://github.com/EdinburghNLP/ACES) - Paper: [arXiv](https://arxiv.org/abs/2401.16313) ### Dataset Summary ACES consists of 36,476 examples covering 146 language pairs and representing challenges from 68 phenomena for evaluating machine translation metrics. We focus on translation accuracy errors and base the phenomena covered in our challenge set on the Multidimensional Quality Metrics (MQM) ontology. The phenomena range from simple perturbations at the word/character level to more complex errors based on discourse and real-world knowledge. 29.01.2024: We also release Span-ACES, which is an extension to the ACES dataset. The errors in incorrect-translation are explicitly marked in a <v>span</v> format. ### Supported Tasks and Leaderboards -Machine translation evaluation of metrics -Potentially useful for contrastive machine translation evaluation ### Languages The dataset covers 146 language pairs as follows: af-en, af-fa, ar-en, ar-fr, ar-hi, be-en, bg-en, bg-lt, ca-en, ca-es, cs-en, da-en, de-en, de-es, de-fr, de-ja, de-ko, de-ru, de-zh, el-en, en-af, en-ar, en-be, en-bg, en-ca, en-cs, en-da, en-de, en-el, en-es, en-et, en-fa, en-fi, en-fr, en-gl, en-he, en-hi, en-hr, en-hu, en-hy, en-id, en-it, en-ja, en-ko, en-lt, en-lv, en-mr, en-nl, en-no, en-pl, en-pt, en-ro, en-ru, en-sk, en-sl, en-sr, en-sv, en-ta, en-tr, en-uk, en-ur, en-vi, en-zh, es-ca, es-de, es-en, es-fr, es-ja, es-ko, es-zh, et-en, fa-af, fa-en, fi-en, fr-de, fr-en, fr-es, fr-ja, fr-ko, fr-mr, fr-ru, fr-zh, ga-en, gl-en, he-en, he-sv, hi-ar, hi-en, hr-en, hr-lv, hu-en, hy-en, hy-vi, id-en, it-en, ja-de, ja-en, ja-es, ja-fr, ja-ko, ja-zh, ko-de, ko-en, ko-es, ko-fr, ko-ja, ko-zh, lt-bg, lt-en, lv-en, lv-hr, mr-en, nl-en, no-en, pl-en, pl-mr, pl-sk, pt-en, pt-sr, ro-en, ru-de, ru-en, ru-es, ru-fr, sk-en, sk-pl, sl-en, sr-en, sr-pt, sv-en, sv-he, sw-en, ta-en, th-en, tr-en, uk-en, ur-en, vi-en, vi-hy, wo-en, zh-de, zh-en, zh-es, zh-fr, zh-ja, zh-ko ## Dataset Structure ### Data Instances Each data instance contains the following features: _source_, _good-translation_, _incorrect-translation_, _reference_, _phenomena_, _langpair_ See the [ACES corpus viewer](https://huggingface.co/datasets/nikitam/ACES/viewer/nikitam--ACES/train) to explore more examples. An example from the ACES challenge set looks like the following: ``` {'source': "Proper nutritional practices alone cannot generate elite performances, but they can significantly affect athletes' overall wellness.", 'good-translation': 'Las prácticas nutricionales adecuadas por sí solas no pueden generar rendimiento de élite, pero pueden afectar significativamente el bienestar general de los atletas.', 'incorrect-translation': 'Las prácticas nutricionales adecuadas por sí solas no pueden generar rendimiento de élite, pero pueden afectar significativamente el bienestar general de los jóvenes atletas.', 'reference': 'No es posible que las prácticas nutricionales adecuadas, por sí solas, generen un rendimiento de elite, pero puede influir en gran medida el bienestar general de los atletas .', 'phenomena': 'addition', 'langpair': 'en-es'} ``` An example from the Span-ACES challenge set looks like the following: ``` {'source': "Proper nutritional practices alone cannot generate elite performances, but they can significantly affect athletes' overall wellness.", 'good-translation': 'Las prácticas nutricionales adecuadas por sí solas no pueden generar rendimiento de élite, pero pueden afectar significativamente el bienestar general de los atletas.', 'incorrect-translation': 'Las prácticas nutricionales adecuadas por sí solas no pueden generar rendimiento de élite, pero pueden afectar significativamente el bienestar general de los jóvenes atletas.', 'reference': 'No es posible que las prácticas nutricionales adecuadas, por sí solas, generen un rendimiento de elite, pero puede influir en gran medida el bienestar general de los atletas .', 'phenomena': 'addition', 'langpair': 'en-es', "incorrect-translation-annotated":"Las prácticas nutricionales adecuadas por sí solas no pueden generar rendimiento de élite, pero pueden afectar significativamente el bienestar general de los <v>jóvenes</v> atletas.","annotation-method":"annotate_word"} ``` ### Data Fields - 'source': a string containing the text that needs to be translated - 'good-translation': possible translation of the source sentence - 'incorrect-translation': translation of the source sentence that contains an error or phenomenon of interest - 'reference': the gold standard translation - 'phenomena': the type of error or phenomena being studied in the example - 'langpair': the source language and the target language pair of the example - 'incorrect-translation-annotated': incorrect translation with annotated spans containing the phenomena - 'annotation-method': field describing how the annotation Note that the _good-translation_ may not be free of errors but it is a better translation than the _incorrect-translation_ ### Data Splits The ACES dataset has 1 split: _train_ which contains the challenge set. There are 36476 examples. Note, the examples in Span-ACES are identical to ACES with the two additional columns. The examples are also stored under a different _train_ split ## Dataset Creation ### Curation Rationale With the advent of neural networks and especially Transformer-based architectures, machine translation outputs have become more and more fluent. Fluency errors are also judged less severely than accuracy errors by human evaluators \citep{freitag-etal-2021-experts} which reflects the fact that accuracy errors can have dangerous consequences in certain contexts, for example in the medical and legal domains. For these reasons, we decided to build a challenge set focused on accuracy errors. Another aspect we focus on is including a broad range of language pairs in ACES. Whenever possible we create examples for all language pairs covered in a source dataset when we use automatic approaches. For phenomena where we create examples manually, we also aim to cover at least two language pairs per phenomenon but are of course limited to the languages spoken by the authors. We aim to offer a collection of challenge sets covering both easy and hard phenomena. While it may be of interest to the community to continuously test on harder examples to check where machine translation evaluation metrics still break, we believe that easy challenge sets are just as important to ensure that metrics do not suddenly become worse at identifying error types that were previously considered ``solved''. Therefore, we take a holistic view when creating ACES and do not filter out individual examples or exclude challenge sets based on baseline metric performance or other factors. ### Source Data #### Initial Data Collection and Normalization Please see Sections 4 and 5 of the paper. #### Who are the source language producers? The dataset contains sentences found in FLORES-101, FLORES-200, PAWS-X, XNLI, XTREME, WinoMT, Wino-X, MuCOW, EuroParl ConDisco, ParcorFull datasets. Please refer to the respective papers for further details. ### Personal and Sensitive Information The external datasets may contain sensitive information. Refer to the respective datasets for further details. ## Considerations for Using the Data ### Usage ACES has been primarily designed to evaluate machine translation metrics on the accuracy errors. We expect the metric to score _good-translation_ consistently higher than _incorrect-translation_. We report the performance of metric based on Kendall-tau like correlation. It measures the number of times a metric scores the good translation above the incorrect translation (concordant) and equal to or lower than the incorrect translation (discordant). ### Discussion of Biases Some examples within the challenge set exhibit biases, however, this is necessary in order to expose the limitations of existing metrics. ### Other Known Limitations The ACES challenge set exhibits a number of biases. Firstly, there is greater coverage in terms of phenomena and the number of examples for the en-de and en-fr language pairs. This is in part due to the manual effort required to construct examples for some phenomena, in particular, those belonging to the discourse-level and real-world knowledge categories. Further, our choice of language pairs is also limited to the ones available in XLM-R. Secondly, ACES contains more examples for those phenomena for which examples could be generated automatically, compared to those that required manual construction/filtering. Thirdly, some of the automatically generated examples require external libraries which are only available for a few languages (e.g. Multilingual Wordnet). Fourthly, the focus of the challenge set is on accuracy errors. We leave the development of challenge sets for fluency errors to future work. As a result of using existing datasets as the basis for many of the examples, errors present in these datasets may be propagated through into ACES. Whilst we acknowledge that this is undesirable, in our methods for constructing the incorrect translation we aim to ensure that the quality of the incorrect translation is always worse than the corresponding good translation. The results and analyses presented in the paper exclude those metrics submitted to the WMT 2022 metrics shared task that provides only system-level outputs. We focus on metrics that provide segment-level outputs as this enables us to provide a broad overview of metric performance on different phenomenon categories and to conduct fine-grained analyses of performance on individual phenomena. For some of the fine-grained analyses, we apply additional constraints based on the language pairs covered by the metrics, or whether the metrics take the source as input, to address specific questions of interest. As a result of applying some of these additional constraints, our investigations tend to focus more on high and medium-resource languages than on low-resource languages. We hope to address this shortcoming in future work. ## Additional Information ### Licensing Information The ACES dataset is Creative Commons Attribution Non-Commercial Share Alike 4.0 (cc-by-nc-sa-4.0) ### Citation Information ``` @inproceedings{amrhein-etal-2022-aces, title = "{ACES}: Translation Accuracy Challenge Sets for Evaluating Machine Translation Metrics", author = "Amrhein, Chantal and Moghe, Nikita and Guillou, Liane", booktitle = "Proceedings of the Seventh Conference on Machine Translation (WMT)", month = dec, year = "2022", address = "Abu Dhabi, United Arab Emirates (Hybrid)", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2022.wmt-1.44", pages = "479--513", } ``` If using Span-ACES, ``` @misc{moghe2024machine, title={Machine Translation Meta Evaluation through Translation Accuracy Challenge Sets}, author={Nikita Moghe and Arnisa Fazla and Chantal Amrhein and Tom Kocmi and Mark Steedman and Alexandra Birch and Rico Sennrich and Liane Guillou}, year={2024}, eprint={2401.16313}, archivePrefix={arXiv}, primaryClass={cs.CL} } ``` ### Contact [Chantal Amrhein](mailto:amrhein@cl.uzh.ch) and [Nikita Moghe](mailto:nikita.moghe@ed.ac.uk) and [Liane Guillou](mailto:lguillou@ed.ac.uk) Dataset card based on [Allociné](https://huggingface.co/datasets/allocine)
tollefj/sts14-sts-NOB	--- license: cc-by-4.0 --- # Translated STS dataset to Norwegian Bokmål Machine translated using the No language left behind model series, specifically the 1.3B variant: https://huggingface.co/facebook/nllb-200-distilled-1.3B
HydraLM/partitioned_v2_standardized_08	--- dataset_info: features: - name: message dtype: string - name: message_type dtype: string - name: message_id dtype: int64 - name: conversation_id dtype: int64 - name: dataset_id dtype: string - name: unique_conversation_id dtype: string splits: - name: train num_bytes: 63484239.644193426 num_examples: 124197 download_size: 10735759 dataset_size: 63484239.644193426 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "partitioned_v2_standardized_08" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
nam194/codesum_java_512_128_function	--- dataset_info: features: - name: hexsha dtype: string - name: repo dtype: string - name: path dtype: string - name: license sequence: string - name: language dtype: string - name: identifier dtype: string - name: return_type dtype: string - name: original_string dtype: string - name: original_docstring dtype: string - name: docstring dtype: string - name: docstring_tokens sequence: string - name: code dtype: string - name: code_tokens sequence: string - name: short_docstring dtype: string - name: short_docstring_tokens sequence: string - name: comment sequence: string - name: parameters list: - name: param dtype: string - name: type dtype: string - name: docstring_params struct: - name: returns list: - name: docstring dtype: string - name: docstring_tokens sequence: string - name: type dtype: string - name: raises list: - name: docstring dtype: string - name: docstring_tokens sequence: string - name: type dtype: string - name: params list: - name: identifier dtype: string - name: type dtype: string - name: docstring dtype: string - name: docstring_tokens sequence: string - name: default dtype: string - name: is_optional dtype: bool - name: outlier_params list: - name: identifier dtype: string - name: type dtype: string - name: docstring dtype: string - name: docstring_tokens sequence: string - name: default dtype: string - name: is_optional dtype: bool - name: others list: - name: identifier dtype: string - name: docstring dtype: string - name: docstring_tokens sequence: string - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 49797821738 num_examples: 6629193 download_size: 9683784722 dataset_size: 49797821738 configs: - config_name: default data_files: - split: train path: data/train-* ---
Margaret-mmh/mini-MedQuad	--- dataset_info: features: - name: Question dtype: string - name: Answer dtype: string splits: - name: train num_bytes: 4089845 num_examples: 1000 download_size: 1830455 dataset_size: 4089845 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o	--- pretty_name: Evaluation run of CHIH-HUNG/llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [CHIH-HUNG/llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o](https://huggingface.co/CHIH-HUNG/llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o)\ \ 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_CHIH-HUNG__llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-25T01:55:24.069120](https://huggingface.co/datasets/open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o/blob/main/results_2023-10-25T01-55-24.069120.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\": 0.3683934563758389,\n\ \ \"em_stderr\": 0.004939908621291744,\n \"f1\": 0.40490771812080534,\n\ \ \"f1_stderr\": 0.004849475843152754,\n \"acc\": 0.45406011226844856,\n\ \ \"acc_stderr\": 0.010767859275955907\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.3683934563758389,\n \"em_stderr\": 0.004939908621291744,\n\ \ \"f1\": 0.40490771812080534,\n \"f1_stderr\": 0.004849475843152754\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.1425322213798332,\n \ \ \"acc_stderr\": 0.009629588445673827\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7655880031570639,\n \"acc_stderr\": 0.011906130106237986\n\ \ }\n}\n```" repo_url: https://huggingface.co/CHIH-HUNG/llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|arc:challenge\|25_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-01T14-32-44.417888.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_25T01_55_24.069120 path: - '/details_harness\|drop\|3_2023-10-25T01-55-24.069120.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-25T01-55-24.069120.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_25T01_55_24.069120 path: - '/details_harness\|gsm8k\|5_2023-10-25T01-55-24.069120.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-25T01-55-24.069120.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hellaswag\|10_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T14-32-44.417888.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-01T14-32-44.417888.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_01T14_32_44.417888 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-01T14-32-44.417888.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-01T14-32-44.417888.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_25T01_55_24.069120 path: - '/details_harness\|winogrande\|5_2023-10-25T01-55-24.069120.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-25T01-55-24.069120.parquet' - config_name: results data_files: - split: 2023_10_01T14_32_44.417888 path: - results_2023-10-01T14-32-44.417888.parquet - split: 2023_10_25T01_55_24.069120 path: - results_2023-10-25T01-55-24.069120.parquet - split: latest path: - results_2023-10-25T01-55-24.069120.parquet --- # Dataset Card for Evaluation run of CHIH-HUNG/llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o ## Dataset Description - Homepage: - Repository: https://huggingface.co/CHIH-HUNG/llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o - 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 [CHIH-HUNG/llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o](https://huggingface.co/CHIH-HUNG/llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o) 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_CHIH-HUNG__llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-25T01:55:24.069120](https://huggingface.co/datasets/open-llm-leaderboard/details_CHIH-HUNG__llama-2-13b-FINETUNE3_3.3w-r8-q_k_v_o/blob/main/results_2023-10-25T01-55-24.069120.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": 0.3683934563758389, "em_stderr": 0.004939908621291744, "f1": 0.40490771812080534, "f1_stderr": 0.004849475843152754, "acc": 0.45406011226844856, "acc_stderr": 0.010767859275955907 }, "harness\|drop\|3": { "em": 0.3683934563758389, "em_stderr": 0.004939908621291744, "f1": 0.40490771812080534, "f1_stderr": 0.004849475843152754 }, "harness\|gsm8k\|5": { "acc": 0.1425322213798332, "acc_stderr": 0.009629588445673827 }, "harness\|winogrande\|5": { "acc": 0.7655880031570639, "acc_stderr": 0.011906130106237986 } } ``` ### 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_UCLA-AGI__zephyr-7b-sft-full-SPIN-iter3	--- pretty_name: Evaluation run of UCLA-AGI/zephyr-7b-sft-full-SPIN-iter3 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [UCLA-AGI/zephyr-7b-sft-full-SPIN-iter3](https://huggingface.co/UCLA-AGI/zephyr-7b-sft-full-SPIN-iter3)\ \ 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_UCLA-AGI__zephyr-7b-sft-full-SPIN-iter3\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-20T04:40:32.614362](https://huggingface.co/datasets/open-llm-leaderboard/details_UCLA-AGI__zephyr-7b-sft-full-SPIN-iter3/blob/main/results_2024-01-20T04-40-32.614362.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\": 0.6144035496773548,\n\ \ \"acc_stderr\": 0.032858739117399755,\n \"acc_norm\": 0.6200519616024565,\n\ \ \"acc_norm_stderr\": 0.03352475225298005,\n \"mc1\": 0.4222766217870257,\n\ \ \"mc1_stderr\": 0.017290733254248174,\n \"mc2\": 0.5789464689775264,\n\ \ \"mc2_stderr\": 0.015807009741465705\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6305460750853242,\n \"acc_stderr\": 0.014104578366491887,\n\ \ \"acc_norm\": 0.6612627986348123,\n \"acc_norm_stderr\": 0.01383056892797433\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.676458872734515,\n\ \ \"acc_stderr\": 0.0046687106891924,\n \"acc_norm\": 0.8584943238398726,\n\ \ \"acc_norm_stderr\": 0.0034783009945146973\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.5851851851851851,\n\ \ \"acc_stderr\": 0.04256193767901408,\n \"acc_norm\": 0.5851851851851851,\n\ \ \"acc_norm_stderr\": 0.04256193767901408\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6447368421052632,\n \"acc_stderr\": 0.03894734487013317,\n\ \ \"acc_norm\": 0.6447368421052632,\n \"acc_norm_stderr\": 0.03894734487013317\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.57,\n\ \ \"acc_stderr\": 0.049756985195624284,\n \"acc_norm\": 0.57,\n \ \ \"acc_norm_stderr\": 0.049756985195624284\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6754716981132075,\n \"acc_stderr\": 0.028815615713432115,\n\ \ \"acc_norm\": 0.6754716981132075,\n \"acc_norm_stderr\": 0.028815615713432115\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.6944444444444444,\n\ \ \"acc_stderr\": 0.03852084696008534,\n \"acc_norm\": 0.6944444444444444,\n\ \ \"acc_norm_stderr\": 0.03852084696008534\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.45,\n \"acc_stderr\": 0.05,\n \"acc_norm\"\ : 0.45,\n \"acc_norm_stderr\": 0.05\n },\n \"harness\|hendrycksTest-college_computer_science\|5\"\ : {\n \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness\|hendrycksTest-college_mathematics\|5\": {\n \"acc\"\ : 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \"acc_norm\": 0.34,\n\ \ \"acc_norm_stderr\": 0.04760952285695235\n },\n \"harness\|hendrycksTest-college_medicine\|5\"\ : {\n \"acc\": 0.6184971098265896,\n \"acc_stderr\": 0.03703851193099521,\n\ \ \"acc_norm\": 0.6184971098265896,\n \"acc_norm_stderr\": 0.03703851193099521\n\ \ },\n \"harness\|hendrycksTest-college_physics\|5\": {\n \"acc\": 0.4117647058823529,\n\ \ \"acc_stderr\": 0.04897104952726366,\n \"acc_norm\": 0.4117647058823529,\n\ \ \"acc_norm_stderr\": 0.04897104952726366\n },\n \"harness\|hendrycksTest-computer_security\|5\"\ : {\n \"acc\": 0.71,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.71,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness\|hendrycksTest-conceptual_physics\|5\": {\n \"acc\":\ \ 0.5446808510638298,\n \"acc_stderr\": 0.03255525359340355,\n \"\ acc_norm\": 0.5446808510638298,\n \"acc_norm_stderr\": 0.03255525359340355\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.43859649122807015,\n\ \ \"acc_stderr\": 0.04668000738510455,\n \"acc_norm\": 0.43859649122807015,\n\ \ \"acc_norm_stderr\": 0.04668000738510455\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\": 0.38095238095238093,\n\ \ \"acc_stderr\": 0.04343525428949098,\n \"acc_norm\": 0.38095238095238093,\n\ \ \"acc_norm_stderr\": 0.04343525428949098\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.048783173121456316,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.048783173121456316\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.7322580645161291,\n \"acc_stderr\": 0.02518900666021238,\n \"\ acc_norm\": 0.7322580645161291,\n \"acc_norm_stderr\": 0.02518900666021238\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.49261083743842365,\n \"acc_stderr\": 0.035176035403610084,\n \"\ acc_norm\": 0.49261083743842365,\n \"acc_norm_stderr\": 0.035176035403610084\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \"acc_norm\"\ : 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7696969696969697,\n \"acc_stderr\": 0.0328766675860349,\n\ \ \"acc_norm\": 0.7696969696969697,\n \"acc_norm_stderr\": 0.0328766675860349\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7727272727272727,\n \"acc_stderr\": 0.02985751567338642,\n \"\ acc_norm\": 0.7727272727272727,\n \"acc_norm_stderr\": 0.02985751567338642\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8652849740932642,\n \"acc_stderr\": 0.024639789097709447,\n\ \ \"acc_norm\": 0.8652849740932642,\n \"acc_norm_stderr\": 0.024639789097709447\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6102564102564103,\n \"acc_stderr\": 0.024726967886647074,\n\ \ \"acc_norm\": 0.6102564102564103,\n \"acc_norm_stderr\": 0.024726967886647074\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3333333333333333,\n \"acc_stderr\": 0.028742040903948485,\n \ \ \"acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.028742040903948485\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6554621848739496,\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\"\ : 0.2980132450331126,\n \"acc_stderr\": 0.037345356767871984,\n \"\ acc_norm\": 0.2980132450331126,\n \"acc_norm_stderr\": 0.037345356767871984\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.7944954128440367,\n \"acc_stderr\": 0.01732435232501601,\n \"\ acc_norm\": 0.7944954128440367,\n \"acc_norm_stderr\": 0.01732435232501601\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.4305555555555556,\n \"acc_stderr\": 0.03376922151252336,\n \"\ acc_norm\": 0.4305555555555556,\n \"acc_norm_stderr\": 0.03376922151252336\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.7941176470588235,\n \"acc_stderr\": 0.028379449451588663,\n \"\ acc_norm\": 0.7941176470588235,\n \"acc_norm_stderr\": 0.028379449451588663\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7679324894514767,\n \"acc_stderr\": 0.027479744550808514,\n \ \ \"acc_norm\": 0.7679324894514767,\n \"acc_norm_stderr\": 0.027479744550808514\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.672645739910314,\n\ \ \"acc_stderr\": 0.031493846709941306,\n \"acc_norm\": 0.672645739910314,\n\ \ \"acc_norm_stderr\": 0.031493846709941306\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7404580152671756,\n \"acc_stderr\": 0.03844876139785271,\n\ \ \"acc_norm\": 0.7404580152671756,\n \"acc_norm_stderr\": 0.03844876139785271\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.768595041322314,\n \"acc_stderr\": 0.03849856098794088,\n \"acc_norm\"\ : 0.768595041322314,\n \"acc_norm_stderr\": 0.03849856098794088\n },\n\ \ \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7407407407407407,\n\ \ \"acc_stderr\": 0.04236511258094633,\n \"acc_norm\": 0.7407407407407407,\n\ \ \"acc_norm_stderr\": 0.04236511258094633\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7484662576687117,\n \"acc_stderr\": 0.03408997886857529,\n\ \ \"acc_norm\": 0.7484662576687117,\n \"acc_norm_stderr\": 0.03408997886857529\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.45535714285714285,\n\ \ \"acc_stderr\": 0.04726835553719099,\n \"acc_norm\": 0.45535714285714285,\n\ \ \"acc_norm_stderr\": 0.04726835553719099\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7864077669902912,\n \"acc_stderr\": 0.04058042015646034,\n\ \ \"acc_norm\": 0.7864077669902912,\n \"acc_norm_stderr\": 0.04058042015646034\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8461538461538461,\n\ \ \"acc_stderr\": 0.023636873317489284,\n \"acc_norm\": 0.8461538461538461,\n\ \ \"acc_norm_stderr\": 0.023636873317489284\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.72,\n \"acc_stderr\": 0.04512608598542128,\n \ \ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.04512608598542128\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8084291187739464,\n\ \ \"acc_stderr\": 0.014072859310451949,\n \"acc_norm\": 0.8084291187739464,\n\ \ \"acc_norm_stderr\": 0.014072859310451949\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6965317919075145,\n \"acc_stderr\": 0.024752411960917212,\n\ \ \"acc_norm\": 0.6965317919075145,\n \"acc_norm_stderr\": 0.024752411960917212\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.3664804469273743,\n\ \ \"acc_stderr\": 0.016115235504865464,\n \"acc_norm\": 0.3664804469273743,\n\ \ \"acc_norm_stderr\": 0.016115235504865464\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.6895424836601307,\n \"acc_stderr\": 0.026493033225145898,\n\ \ \"acc_norm\": 0.6895424836601307,\n \"acc_norm_stderr\": 0.026493033225145898\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6816720257234726,\n\ \ \"acc_stderr\": 0.026457225067811025,\n \"acc_norm\": 0.6816720257234726,\n\ \ \"acc_norm_stderr\": 0.026457225067811025\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.6512345679012346,\n \"acc_stderr\": 0.02651759772446501,\n\ \ \"acc_norm\": 0.6512345679012346,\n \"acc_norm_stderr\": 0.02651759772446501\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.4716312056737589,\n \"acc_stderr\": 0.029779450957303055,\n \ \ \"acc_norm\": 0.4716312056737589,\n \"acc_norm_stderr\": 0.029779450957303055\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.44589308996088656,\n\ \ \"acc_stderr\": 0.012695244711379778,\n \"acc_norm\": 0.44589308996088656,\n\ \ \"acc_norm_stderr\": 0.012695244711379778\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\": 0.619281045751634,\n \"acc_stderr\": 0.0196438015579248,\n \ \ \"acc_norm\": 0.619281045751634,\n \"acc_norm_stderr\": 0.0196438015579248\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\": 0.6653061224489796,\n \"acc_stderr\": 0.030209235226242307,\n\ \ \"acc_norm\": 0.6653061224489796,\n \"acc_norm_stderr\": 0.030209235226242307\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8159203980099502,\n\ \ \"acc_stderr\": 0.027403859410786845,\n \"acc_norm\": 0.8159203980099502,\n\ \ \"acc_norm_stderr\": 0.027403859410786845\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.84,\n \"acc_stderr\": 0.03684529491774708,\n \ \ \"acc_norm\": 0.84,\n \"acc_norm_stderr\": 0.03684529491774708\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5421686746987951,\n\ \ \"acc_stderr\": 0.0387862677100236,\n \"acc_norm\": 0.5421686746987951,\n\ \ \"acc_norm_stderr\": 0.0387862677100236\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.029547741687640038,\n\ \ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.029547741687640038\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.4222766217870257,\n\ \ \"mc1_stderr\": 0.017290733254248174,\n \"mc2\": 0.5789464689775264,\n\ \ \"mc2_stderr\": 0.015807009741465705\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7663772691397001,\n \"acc_stderr\": 0.011892194477183525\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.3419257012888552,\n \ \ \"acc_stderr\": 0.0130660896251828\n }\n}\n```" repo_url: https://huggingface.co/UCLA-AGI/zephyr-7b-sft-full-SPIN-iter3 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_20T04_40_32.614362 path: - '/details_harness\|arc:challenge\|25_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-01-20T04-40-32.614362.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|gsm8k\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hellaswag\|10_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-20T04-40-32.614362.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-management\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-20T04-40-32.614362.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|truthfulqa:mc\|0_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-01-20T04-40-32.614362.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_20T04_40_32.614362 path: - '/details_harness\|winogrande\|5_2024-01-20T04-40-32.614362.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-01-20T04-40-32.614362.parquet' - config_name: results data_files: - split: 2024_01_20T04_40_32.614362 path: - results_2024-01-20T04-40-32.614362.parquet - split: latest path: - results_2024-01-20T04-40-32.614362.parquet --- # Dataset Card for Evaluation run of UCLA-AGI/zephyr-7b-sft-full-SPIN-iter3 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [UCLA-AGI/zephyr-7b-sft-full-SPIN-iter3](https://huggingface.co/UCLA-AGI/zephyr-7b-sft-full-SPIN-iter3) 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_UCLA-AGI__zephyr-7b-sft-full-SPIN-iter3", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-20T04:40:32.614362](https://huggingface.co/datasets/open-llm-leaderboard/details_UCLA-AGI__zephyr-7b-sft-full-SPIN-iter3/blob/main/results_2024-01-20T04-40-32.614362.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": 0.6144035496773548, "acc_stderr": 0.032858739117399755, "acc_norm": 0.6200519616024565, "acc_norm_stderr": 0.03352475225298005, "mc1": 0.4222766217870257, "mc1_stderr": 0.017290733254248174, "mc2": 0.5789464689775264, "mc2_stderr": 0.015807009741465705 }, "harness\|arc:challenge\|25": { "acc": 0.6305460750853242, "acc_stderr": 0.014104578366491887, "acc_norm": 0.6612627986348123, "acc_norm_stderr": 0.01383056892797433 }, "harness\|hellaswag\|10": { "acc": 0.676458872734515, "acc_stderr": 0.0046687106891924, "acc_norm": 0.8584943238398726, "acc_norm_stderr": 0.0034783009945146973 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.5851851851851851, "acc_stderr": 0.04256193767901408, "acc_norm": 0.5851851851851851, "acc_norm_stderr": 0.04256193767901408 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6447368421052632, "acc_stderr": 0.03894734487013317, "acc_norm": 0.6447368421052632, "acc_norm_stderr": 0.03894734487013317 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.57, "acc_stderr": 0.049756985195624284, "acc_norm": 0.57, "acc_norm_stderr": 0.049756985195624284 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6754716981132075, "acc_stderr": 0.028815615713432115, "acc_norm": 0.6754716981132075, "acc_norm_stderr": 0.028815615713432115 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.6944444444444444, "acc_stderr": 0.03852084696008534, "acc_norm": 0.6944444444444444, "acc_norm_stderr": 0.03852084696008534 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6184971098265896, "acc_stderr": 0.03703851193099521, "acc_norm": 0.6184971098265896, "acc_norm_stderr": 0.03703851193099521 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.4117647058823529, "acc_stderr": 0.04897104952726366, "acc_norm": 0.4117647058823529, "acc_norm_stderr": 0.04897104952726366 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5446808510638298, "acc_stderr": 0.03255525359340355, "acc_norm": 0.5446808510638298, "acc_norm_stderr": 0.03255525359340355 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.43859649122807015, "acc_stderr": 0.04668000738510455, "acc_norm": 0.43859649122807015, "acc_norm_stderr": 0.04668000738510455 }, "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": 0.38095238095238093, "acc_stderr": 0.04343525428949098, "acc_norm": 0.38095238095238093, "acc_norm_stderr": 0.04343525428949098 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7322580645161291, "acc_stderr": 0.02518900666021238, "acc_norm": 0.7322580645161291, "acc_norm_stderr": 0.02518900666021238 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.49261083743842365, "acc_stderr": 0.035176035403610084, "acc_norm": 0.49261083743842365, "acc_norm_stderr": 0.035176035403610084 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7696969696969697, "acc_stderr": 0.0328766675860349, "acc_norm": 0.7696969696969697, "acc_norm_stderr": 0.0328766675860349 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7727272727272727, "acc_stderr": 0.02985751567338642, "acc_norm": 0.7727272727272727, "acc_norm_stderr": 0.02985751567338642 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8652849740932642, "acc_stderr": 0.024639789097709447, "acc_norm": 0.8652849740932642, "acc_norm_stderr": 0.024639789097709447 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6102564102564103, "acc_stderr": 0.024726967886647074, "acc_norm": 0.6102564102564103, "acc_norm_stderr": 0.024726967886647074 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.028742040903948485, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.028742040903948485 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6554621848739496, "acc_stderr": 0.030868682604121622, "acc_norm": 0.6554621848739496, "acc_norm_stderr": 0.030868682604121622 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.2980132450331126, "acc_stderr": 0.037345356767871984, "acc_norm": 0.2980132450331126, "acc_norm_stderr": 0.037345356767871984 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.7944954128440367, "acc_stderr": 0.01732435232501601, "acc_norm": 0.7944954128440367, "acc_norm_stderr": 0.01732435232501601 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4305555555555556, "acc_stderr": 0.03376922151252336, "acc_norm": 0.4305555555555556, "acc_norm_stderr": 0.03376922151252336 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7941176470588235, "acc_stderr": 0.028379449451588663, "acc_norm": 0.7941176470588235, "acc_norm_stderr": 0.028379449451588663 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7679324894514767, "acc_stderr": 0.027479744550808514, "acc_norm": 0.7679324894514767, "acc_norm_stderr": 0.027479744550808514 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.672645739910314, "acc_stderr": 0.031493846709941306, "acc_norm": 0.672645739910314, "acc_norm_stderr": 0.031493846709941306 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7404580152671756, "acc_stderr": 0.03844876139785271, "acc_norm": 0.7404580152671756, "acc_norm_stderr": 0.03844876139785271 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.768595041322314, "acc_stderr": 0.03849856098794088, "acc_norm": 0.768595041322314, "acc_norm_stderr": 0.03849856098794088 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7407407407407407, "acc_stderr": 0.04236511258094633, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.04236511258094633 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7484662576687117, "acc_stderr": 0.03408997886857529, "acc_norm": 0.7484662576687117, "acc_norm_stderr": 0.03408997886857529 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.45535714285714285, "acc_stderr": 0.04726835553719099, "acc_norm": 0.45535714285714285, "acc_norm_stderr": 0.04726835553719099 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7864077669902912, "acc_stderr": 0.04058042015646034, "acc_norm": 0.7864077669902912, "acc_norm_stderr": 0.04058042015646034 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8461538461538461, "acc_stderr": 0.023636873317489284, "acc_norm": 0.8461538461538461, "acc_norm_stderr": 0.023636873317489284 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8084291187739464, "acc_stderr": 0.014072859310451949, "acc_norm": 0.8084291187739464, "acc_norm_stderr": 0.014072859310451949 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6965317919075145, "acc_stderr": 0.024752411960917212, "acc_norm": 0.6965317919075145, "acc_norm_stderr": 0.024752411960917212 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.3664804469273743, "acc_stderr": 0.016115235504865464, "acc_norm": 0.3664804469273743, "acc_norm_stderr": 0.016115235504865464 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.6895424836601307, "acc_stderr": 0.026493033225145898, "acc_norm": 0.6895424836601307, "acc_norm_stderr": 0.026493033225145898 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6816720257234726, "acc_stderr": 0.026457225067811025, "acc_norm": 0.6816720257234726, "acc_norm_stderr": 0.026457225067811025 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.6512345679012346, "acc_stderr": 0.02651759772446501, "acc_norm": 0.6512345679012346, "acc_norm_stderr": 0.02651759772446501 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4716312056737589, "acc_stderr": 0.029779450957303055, "acc_norm": 0.4716312056737589, "acc_norm_stderr": 0.029779450957303055 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.44589308996088656, "acc_stderr": 0.012695244711379778, "acc_norm": 0.44589308996088656, "acc_norm_stderr": 0.012695244711379778 }, "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": 0.619281045751634, "acc_stderr": 0.0196438015579248, "acc_norm": 0.619281045751634, "acc_norm_stderr": 0.0196438015579248 }, "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": 0.6653061224489796, "acc_stderr": 0.030209235226242307, "acc_norm": 0.6653061224489796, "acc_norm_stderr": 0.030209235226242307 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8159203980099502, "acc_stderr": 0.027403859410786845, "acc_norm": 0.8159203980099502, "acc_norm_stderr": 0.027403859410786845 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.84, "acc_stderr": 0.03684529491774708, "acc_norm": 0.84, "acc_norm_stderr": 0.03684529491774708 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5421686746987951, "acc_stderr": 0.0387862677100236, "acc_norm": 0.5421686746987951, "acc_norm_stderr": 0.0387862677100236 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8187134502923976, "acc_stderr": 0.029547741687640038, "acc_norm": 0.8187134502923976, "acc_norm_stderr": 0.029547741687640038 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.4222766217870257, "mc1_stderr": 0.017290733254248174, "mc2": 0.5789464689775264, "mc2_stderr": 0.015807009741465705 }, "harness\|winogrande\|5": { "acc": 0.7663772691397001, "acc_stderr": 0.011892194477183525 }, "harness\|gsm8k\|5": { "acc": 0.3419257012888552, "acc_stderr": 0.0130660896251828 } } ``` ## 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]
pankajemplay/llama-intent-1K	--- dataset_info: features: - name: User Query dtype: string - name: Intent dtype: string - name: id type dtype: string - name: id value dtype: string - name: id slot filled dtype: bool - name: Task dtype: string - name: task slot filled dtype: bool - name: Bot Response dtype: string - name: text dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 633182 num_examples: 1308 download_size: 189305 dataset_size: 633182 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "llama-intent-1K" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
suyuanliu/Winnf0VOT	--- dataset_info: features: - name: audio dtype: audio splits: - name: train num_bytes: 100267569.0 num_examples: 1800 download_size: 93892942 dataset_size: 100267569.0 --- # Dataset Card for "Winnf0VOT" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CristianaLazar/librispeech5k_train	--- dataset_info: features: - name: file dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: text dtype: string - name: speaker_id dtype: int64 - name: chapter_id dtype: int64 - name: id dtype: string - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train.360 num_bytes: 6796635145.0 num_examples: 5000 download_size: 3988908181 dataset_size: 6796635145.0 --- # Dataset Card for "librispeech5k_train" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
tyzhu/squad_id_train_10_eval_10	--- dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers sequence: - name: text dtype: string - name: answer_start dtype: int32 - name: context_id dtype: string - name: inputs dtype: string - name: targets dtype: string splits: - name: train num_bytes: 237881 num_examples: 150 - name: validation num_bytes: 59860 num_examples: 48 download_size: 72567 dataset_size: 297741 --- # Dataset Card for "squad_id_train_10_eval_10" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
jarod0411/zinc10M_linker_v2	--- dataset_info: features: - name: smiles dtype: string - name: p1 dtype: string - name: p2 dtype: string splits: - name: train num_bytes: 2481183347.0 num_examples: 24088962 - name: validation num_bytes: 275347726.0 num_examples: 2673196 download_size: 807049756 dataset_size: 2756531073.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---
LinQingYang/my_dataset	--- license: mit ---
RafaelBlue/Ranozera3	--- license: openrail ---
Multimodal-Fatima/Hatefulmemes_test_facebook_opt_6.7b_Hatefulmemes_ns_1000	--- dataset_info: features: - name: id dtype: int64 - name: image dtype: image - name: prompt dtype: string - name: true_label dtype: string - name: prediction dtype: string - name: scores sequence: float64 splits: - name: fewshot_1_bs_16 num_bytes: 362719567.0 num_examples: 1000 - name: fewshot_3_bs_16 num_bytes: 363587206.0 num_examples: 1000 - name: fewshot_5_bs_16 num_bytes: 364454992.0 num_examples: 1000 - name: fewshot_8_bs_16 num_bytes: 365760377.0 num_examples: 1000 - name: fewshot_10_bs_16 num_bytes: 366632224.0 num_examples: 1000 download_size: 1814428039 dataset_size: 1823154366.0 --- # Dataset Card for "Hatefulmemes_test_facebook_opt_6.7b_Hatefulmemes_ns_1000" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_luffycodes__mcq-vicuna-13b-v1.5	--- pretty_name: Evaluation run of luffycodes/mcq-vicuna-13b-v1.5 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [luffycodes/mcq-vicuna-13b-v1.5](https://huggingface.co/luffycodes/mcq-vicuna-13b-v1.5)\ \ 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 4 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_luffycodes__mcq-vicuna-13b-v1.5\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-15T06:51:11.600921](https://huggingface.co/datasets/open-llm-leaderboard/details_luffycodes__mcq-vicuna-13b-v1.5/blob/main/results_2023-10-15T06-51-11.600921.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\": 0.28366191275167785,\n\ \ \"em_stderr\": 0.004616354866148242,\n \"f1\": 0.34618708053691377,\n\ \ \"f1_stderr\": 0.004545404408691654,\n \"acc\": 0.40521747299651206,\n\ \ \"acc_stderr\": 0.009982345972620842\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.28366191275167785,\n \"em_stderr\": 0.004616354866148242,\n\ \ \"f1\": 0.34618708053691377,\n \"f1_stderr\": 0.004545404408691654\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0803639120545868,\n \ \ \"acc_stderr\": 0.007488258573239077\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7300710339384373,\n \"acc_stderr\": 0.012476433372002604\n\ \ }\n}\n```" repo_url: https://huggingface.co/luffycodes/mcq-vicuna-13b-v1.5 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|arc:challenge\|25_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|arc:challenge\|25_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-01T06:07:11.964362.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_13T04_41_01.190569 path: - '/details_harness\|drop\|3_2023-10-13T04-41-01.190569.parquet' - split: 2023_10_15T06_51_11.600921 path: - '/details_harness\|drop\|3_2023-10-15T06-51-11.600921.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-15T06-51-11.600921.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_13T04_41_01.190569 path: - '/details_harness\|gsm8k\|5_2023-10-13T04-41-01.190569.parquet' - split: 2023_10_15T06_51_11.600921 path: - '/details_harness\|gsm8k\|5_2023-10-15T06-51-11.600921.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-15T06-51-11.600921.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hellaswag\|10_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hellaswag\|10_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-01T05:01:33.006362.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-01T06:07:11.964362.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-01T06:07:11.964362.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_01T05_01_33.006362 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-01T05:01:33.006362.parquet' - split: 2023_09_01T06_07_11.964362 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-01T06:07:11.964362.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-01T06:07:11.964362.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_13T04_41_01.190569 path: - '/details_harness\|winogrande\|5_2023-10-13T04-41-01.190569.parquet' - split: 2023_10_15T06_51_11.600921 path: - '/details_harness\|winogrande\|5_2023-10-15T06-51-11.600921.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-15T06-51-11.600921.parquet' - config_name: results data_files: - split: 2023_09_01T05_01_33.006362 path: - results_2023-09-01T05:01:33.006362.parquet - split: 2023_09_01T06_07_11.964362 path: - results_2023-09-01T06:07:11.964362.parquet - split: 2023_10_13T04_41_01.190569 path: - results_2023-10-13T04-41-01.190569.parquet - split: 2023_10_15T06_51_11.600921 path: - results_2023-10-15T06-51-11.600921.parquet - split: latest path: - results_2023-10-15T06-51-11.600921.parquet --- # Dataset Card for Evaluation run of luffycodes/mcq-vicuna-13b-v1.5 ## Dataset Description - Homepage: - Repository: https://huggingface.co/luffycodes/mcq-vicuna-13b-v1.5 - 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 [luffycodes/mcq-vicuna-13b-v1.5](https://huggingface.co/luffycodes/mcq-vicuna-13b-v1.5) 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 4 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_luffycodes__mcq-vicuna-13b-v1.5", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-15T06:51:11.600921](https://huggingface.co/datasets/open-llm-leaderboard/details_luffycodes__mcq-vicuna-13b-v1.5/blob/main/results_2023-10-15T06-51-11.600921.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": 0.28366191275167785, "em_stderr": 0.004616354866148242, "f1": 0.34618708053691377, "f1_stderr": 0.004545404408691654, "acc": 0.40521747299651206, "acc_stderr": 0.009982345972620842 }, "harness\|drop\|3": { "em": 0.28366191275167785, "em_stderr": 0.004616354866148242, "f1": 0.34618708053691377, "f1_stderr": 0.004545404408691654 }, "harness\|gsm8k\|5": { "acc": 0.0803639120545868, "acc_stderr": 0.007488258573239077 }, "harness\|winogrande\|5": { "acc": 0.7300710339384373, "acc_stderr": 0.012476433372002604 } } ``` ### 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]
ckmai24/ghibil-style	--- license: afl-3.0 ---
AISE-TUDelft/ML4SE23_G6_Original_Prev_Diverse	--- license: mit ---
samhellkill/spacekitty-v1	--- license: other ---
liuyanchen1015/MULTI_VALUE_qqp_say_complementizer	--- dataset_info: features: - name: question1 dtype: string - name: question2 dtype: string - name: label dtype: int64 - name: idx dtype: int64 - name: value_score dtype: int64 splits: - name: dev num_bytes: 131067 num_examples: 614 - name: test num_bytes: 1311590 num_examples: 6202 - name: train num_bytes: 1212547 num_examples: 5505 download_size: 1612005 dataset_size: 2655204 --- # Dataset Card for "MULTI_VALUE_qqp_say_complementizer" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
higgsfield/hacker_news_prompt_completion	--- dataset_info: features: - name: prompt dtype: string - name: completion dtype: string splits: - name: train num_bytes: 187231365 num_examples: 100000 download_size: 77649586 dataset_size: 187231365 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "hacker_news_prompt_completion" [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/19f9e05b	--- dataset_info: features: - name: result dtype: string - name: id dtype: int64 splits: - name: train num_bytes: 186 num_examples: 10 download_size: 1332 dataset_size: 186 --- # Dataset Card for "19f9e05b" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
PVIT/pvit_data_stage2	--- license: cc-by-nc-4.0 --- # PVIT dataset This is the stage 2 pretraining dataset of paper: [Position-Enhanced Visual Instruction Tuning for Multimodal Large Language Models](https://arxiv.org/abs/2308.13437). ## Model description Position-enhanced Visual Instruction Tuning (PVIT) extends the MLLM by incorporating an additional region-level vision encoder to facilitate support for region-based inputs. Specifically, we adopt the vision encoder from RegionCLIP and utilize it to extract region-level features by taking images and regions as inputs. As an additional source of information, the incorporation of region-level features in this way has a minimal impact on the original MLLM. Furthermore, since the features provided by RegionCLIP are themselves already aligned to the language at a fine-grained level, the overhead of aligning it to the MLLM will be relatively small. Following [LLaVA](https://github.com/haotian-liu/LLaVA), we design a two-stage training strategy for PVIT that first pre-training a linear projection to align the region features to the LLM word embedding, followed by end-to-end fine-tuning to follow complex fine-grained instructions. For more details, please refer to our [paper](https://arxiv.org/abs/2308.13437) and [github repo](https://github.com/THUNLP-MT/PVIT). ## How to use See [here](https://github.com/THUNLP-MT/PVIT#Train) for instructions of pretraining. ## Intended use Primary intended uses: The primary use of PVIT is research on large multimodal models and chatbots. Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence. ## BibTeX entry and citation info ```bibtex @misc{chen2023positionenhanced, title={Position-Enhanced Visual Instruction Tuning for Multimodal Large Language Models}, author={Chi Chen and Ruoyu Qin and Fuwen Luo and Xiaoyue Mi and Peng Li and Maosong Sun and Yang Liu}, year={2023}, eprint={2308.13437}, archivePrefix={arXiv}, primaryClass={cs.CV} } ```
jpwahle/autoencoder-paraphrase-dataset	--- annotations_creators: - machine-generated language: - en language_creators: - machine-generated license: - cc-by-4.0 multilinguality: - monolingual pretty_name: Autoencoder Paraphrase Dataset (BERT, RoBERTa, Longformer) size_categories: - 100K<n<1M source_datasets: - original tags: - bert - roberta - longformer - plagiarism - paraphrase - academic integrity - arxiv - wikipedia - theses task_categories: - text-classification - text-generation task_ids: [] paperswithcode_id: are-neural-language-models-good-plagiarists-a dataset_info: - split: train download_size: 2980464 dataset_size: 2980464 - split: test download_size: 1690032 dataset_size: 1690032 --- # Dataset Card for Machine Paraphrase Dataset (MPC) ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rat1.ionale](#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 - Paper: https://ieeexplore.ieee.org/document/9651895 - Total size: 2.23 GB - Train size: 1.52 GB - Test size: 861 MB ### Dataset Summary The Autoencoder Paraphrase Corpus (APC) consists of ~200k examples of original, and paraphrases using three neural language models. It uses three models (BERT, RoBERTa, Longformer) on three source texts (Wikipedia, arXiv, student theses). The examples are aligned, i.e., we sample the same paragraphs for originals and paraphrased versions. ### How to use it You can load the dataset using the `load_dataset` function: ```python from datasets import load_dataset ds = load_dataset("jpwahle/autoencoder-paraphrase-dataset") print(ds[0]) #OUTPUT: { 'text': 'War memorial formally unveiled on Whit Monday 16 May 1921 by the Prince of Wales later King Edward VIII with Lutyens in attendance At the unveiling ceremony Captain Fortescue gave a speech during wherein he announced that 11 600 men and women from Devon had been inval while serving in imperialist war He later stated that some 63 700 8 000 regulars 36 700 volunteers 19 000 conscripts had served in the armed forces The heroism of the dead are recorded on a roll of honour of which three copies were made one for Exeter Cathedral one To be held by Tasman county council and another honoring the Prince of Wales placed in a hollow in bedrock base of the war memorial The princes visit generated considerable excitement in the area Thousands of spectators lined the street to greet his motorcade and shops on Market High Street hung out banners with welcoming messages After the unveiling Edward spent ten days touring the local area', 'label': 1, 'dataset': 'wikipedia', 'method': 'longformer' } ``` ### Supported Tasks and Leaderboards Paraphrase Identification ### Languages English ## Dataset Structure ### Data Instances ```json { 'text': 'War memorial formally unveiled on Whit Monday 16 May 1921 by the Prince of Wales later King Edward VIII with Lutyens in attendance At the unveiling ceremony Captain Fortescue gave a speech during wherein he announced that 11 600 men and women from Devon had been inval while serving in imperialist war He later stated that some 63 700 8 000 regulars 36 700 volunteers 19 000 conscripts had served in the armed forces The heroism of the dead are recorded on a roll of honour of which three copies were made one for Exeter Cathedral one To be held by Tasman county council and another honoring the Prince of Wales placed in a hollow in bedrock base of the war memorial The princes visit generated considerable excitement in the area Thousands of spectators lined the street to greet his motorcade and shops on Market High Street hung out banners with welcoming messages After the unveiling Edward spent ten days touring the local area', 'label': 1, 'dataset': 'wikipedia', 'method': 'longformer' } ``` ### Data Fields \| Feature \| Description \| \| --- \| --- \| \| `text` \| The unique identifier of the paper. \| \| `label` \| Whether it is a paraphrase (1) or the original (0). \| \| `dataset` \| The source dataset (Wikipedia, arXiv, or theses). \| \| `method` \| The method used (bert, roberta, longformer). \| ### Data Splits - train (Wikipedia x [bert, roberta, longformer]) - test ([Wikipedia, arXiv, theses] x [bert, roberta, longformer]) ## Dataset Creation ### Curation Rationale Providing a resource for testing against autoencoder paraprhased plagiarism. ### Source Data #### Initial Data Collection and Normalization - Paragraphs from `featured articles` from the English Wikipedia dump - Paragraphs from full-text pdfs of arXMLiv - Paragraphs from full-text pdfs of Czech student thesis (bachelor, master, PhD). #### 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 [Jan Philip Wahle](https://jpwahle.com/) ### Licensing Information The Autoencoder Paraphrase Dataset is released under CC BY-NC 4.0. By using this corpus, you agree to its usage terms. ### Citation Information ```bib @inproceedings{9651895, title = {Are Neural Language Models Good Plagiarists? A Benchmark for Neural Paraphrase Detection}, author = {Wahle, Jan Philip and Ruas, Terry and Meuschke, Norman and Gipp, Bela}, year = 2021, booktitle = {2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)}, volume = {}, number = {}, pages = {226--229}, doi = {10.1109/JCDL52503.2021.00065} } ``` ### Contributions Thanks to [@jpwahle](https://github.com/jpwahle) for adding this dataset.
AdapterOcean/python-code-instructions-18k-alpaca-standardized_cluster_8	--- dataset_info: features: - name: text dtype: string - name: conversation_id dtype: int64 - name: embedding sequence: float64 - name: cluster dtype: int64 splits: - name: train num_bytes: 30601750 num_examples: 3552 download_size: 7874173 dataset_size: 30601750 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "python-code-instructions-18k-alpaca-standardized_cluster_8" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ibivibiv/alpaca_lamini14	--- dataset_info: features: - name: output dtype: string - name: instruction dtype: string - name: input dtype: string splits: - name: train num_bytes: 56180745 num_examples: 129280 download_size: 36259259 dataset_size: 56180745 configs: - config_name: default data_files: - split: train path: data/train-* ---
BangumiBase/joshikouseinomudazukai	--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Joshikousei No Mudazukai This is the image base of bangumi Joshikousei no Mudazukai, we detected 23 characters, 1598 images in total. The full dataset is [here](all.zip). Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual. If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: \| # \| Images \| Download \| Preview 1 \| Preview 2 \| Preview 3 \| Preview 4 \| Preview 5 \| Preview 6 \| Preview 7 \| Preview 8 \| \|:------\|---------:\|:---------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\|:-------------------------------\| \| 0 \| 202 \| [Download](0/dataset.zip) \| ![preview 1](0/preview_1.png) \| ![preview 2](0/preview_2.png) \| ![preview 3](0/preview_3.png) \| ![preview 4](0/preview_4.png) \| ![preview 5](0/preview_5.png) \| ![preview 6](0/preview_6.png) \| ![preview 7](0/preview_7.png) \| ![preview 8](0/preview_8.png) \| \| 1 \| 99 \| [Download](1/dataset.zip) \| ![preview 1](1/preview_1.png) \| ![preview 2](1/preview_2.png) \| ![preview 3](1/preview_3.png) \| ![preview 4](1/preview_4.png) \| ![preview 5](1/preview_5.png) \| ![preview 6](1/preview_6.png) \| ![preview 7](1/preview_7.png) \| ![preview 8](1/preview_8.png) \| \| 2 \| 11 \| [Download](2/dataset.zip) \| ![preview 1](2/preview_1.png) \| ![preview 2](2/preview_2.png) \| ![preview 3](2/preview_3.png) \| ![preview 4](2/preview_4.png) \| ![preview 5](2/preview_5.png) \| ![preview 6](2/preview_6.png) \| ![preview 7](2/preview_7.png) \| ![preview 8](2/preview_8.png) \| \| 3 \| 19 \| [Download](3/dataset.zip) \| ![preview 1](3/preview_1.png) \| ![preview 2](3/preview_2.png) \| ![preview 3](3/preview_3.png) \| ![preview 4](3/preview_4.png) \| ![preview 5](3/preview_5.png) \| ![preview 6](3/preview_6.png) \| ![preview 7](3/preview_7.png) \| ![preview 8](3/preview_8.png) \| \| 4 \| 41 \| [Download](4/dataset.zip) \| ![preview 1](4/preview_1.png) \| ![preview 2](4/preview_2.png) \| ![preview 3](4/preview_3.png) \| ![preview 4](4/preview_4.png) \| ![preview 5](4/preview_5.png) \| ![preview 6](4/preview_6.png) \| ![preview 7](4/preview_7.png) \| ![preview 8](4/preview_8.png) \| \| 5 \| 74 \| [Download](5/dataset.zip) \| ![preview 1](5/preview_1.png) \| ![preview 2](5/preview_2.png) \| ![preview 3](5/preview_3.png) \| ![preview 4](5/preview_4.png) \| ![preview 5](5/preview_5.png) \| ![preview 6](5/preview_6.png) \| ![preview 7](5/preview_7.png) \| ![preview 8](5/preview_8.png) \| \| 6 \| 271 \| [Download](6/dataset.zip) \| ![preview 1](6/preview_1.png) \| ![preview 2](6/preview_2.png) \| ![preview 3](6/preview_3.png) \| ![preview 4](6/preview_4.png) \| ![preview 5](6/preview_5.png) \| ![preview 6](6/preview_6.png) \| ![preview 7](6/preview_7.png) \| ![preview 8](6/preview_8.png) \| \| 7 \| 10 \| [Download](7/dataset.zip) \| ![preview 1](7/preview_1.png) \| ![preview 2](7/preview_2.png) \| ![preview 3](7/preview_3.png) \| ![preview 4](7/preview_4.png) \| ![preview 5](7/preview_5.png) \| ![preview 6](7/preview_6.png) \| ![preview 7](7/preview_7.png) \| ![preview 8](7/preview_8.png) \| \| 8 \| 22 \| [Download](8/dataset.zip) \| ![preview 1](8/preview_1.png) \| ![preview 2](8/preview_2.png) \| ![preview 3](8/preview_3.png) \| ![preview 4](8/preview_4.png) \| ![preview 5](8/preview_5.png) \| ![preview 6](8/preview_6.png) \| ![preview 7](8/preview_7.png) \| ![preview 8](8/preview_8.png) \| \| 9 \| 7 \| [Download](9/dataset.zip) \| ![preview 1](9/preview_1.png) \| ![preview 2](9/preview_2.png) \| ![preview 3](9/preview_3.png) \| ![preview 4](9/preview_4.png) \| ![preview 5](9/preview_5.png) \| ![preview 6](9/preview_6.png) \| ![preview 7](9/preview_7.png) \| N/A \| \| 10 \| 11 \| [Download](10/dataset.zip) \| ![preview 1](10/preview_1.png) \| ![preview 2](10/preview_2.png) \| ![preview 3](10/preview_3.png) \| ![preview 4](10/preview_4.png) \| ![preview 5](10/preview_5.png) \| ![preview 6](10/preview_6.png) \| ![preview 7](10/preview_7.png) \| ![preview 8](10/preview_8.png) \| \| 11 \| 190 \| [Download](11/dataset.zip) \| ![preview 1](11/preview_1.png) \| ![preview 2](11/preview_2.png) \| ![preview 3](11/preview_3.png) \| ![preview 4](11/preview_4.png) \| ![preview 5](11/preview_5.png) \| ![preview 6](11/preview_6.png) \| ![preview 7](11/preview_7.png) \| ![preview 8](11/preview_8.png) \| \| 12 \| 33 \| [Download](12/dataset.zip) \| ![preview 1](12/preview_1.png) \| ![preview 2](12/preview_2.png) \| ![preview 3](12/preview_3.png) \| ![preview 4](12/preview_4.png) \| ![preview 5](12/preview_5.png) \| ![preview 6](12/preview_6.png) \| ![preview 7](12/preview_7.png) \| ![preview 8](12/preview_8.png) \| \| 13 \| 79 \| [Download](13/dataset.zip) \| ![preview 1](13/preview_1.png) \| ![preview 2](13/preview_2.png) \| ![preview 3](13/preview_3.png) \| ![preview 4](13/preview_4.png) \| ![preview 5](13/preview_5.png) \| ![preview 6](13/preview_6.png) \| ![preview 7](13/preview_7.png) \| ![preview 8](13/preview_8.png) \| \| 14 \| 12 \| [Download](14/dataset.zip) \| ![preview 1](14/preview_1.png) \| ![preview 2](14/preview_2.png) \| ![preview 3](14/preview_3.png) \| ![preview 4](14/preview_4.png) \| ![preview 5](14/preview_5.png) \| ![preview 6](14/preview_6.png) \| ![preview 7](14/preview_7.png) \| ![preview 8](14/preview_8.png) \| \| 15 \| 110 \| [Download](15/dataset.zip) \| ![preview 1](15/preview_1.png) \| ![preview 2](15/preview_2.png) \| ![preview 3](15/preview_3.png) \| ![preview 4](15/preview_4.png) \| ![preview 5](15/preview_5.png) \| ![preview 6](15/preview_6.png) \| ![preview 7](15/preview_7.png) \| ![preview 8](15/preview_8.png) \| \| 16 \| 14 \| [Download](16/dataset.zip) \| ![preview 1](16/preview_1.png) \| ![preview 2](16/preview_2.png) \| ![preview 3](16/preview_3.png) \| ![preview 4](16/preview_4.png) \| ![preview 5](16/preview_5.png) \| ![preview 6](16/preview_6.png) \| ![preview 7](16/preview_7.png) \| ![preview 8](16/preview_8.png) \| \| 17 \| 86 \| [Download](17/dataset.zip) \| ![preview 1](17/preview_1.png) \| ![preview 2](17/preview_2.png) \| ![preview 3](17/preview_3.png) \| ![preview 4](17/preview_4.png) \| ![preview 5](17/preview_5.png) \| ![preview 6](17/preview_6.png) \| ![preview 7](17/preview_7.png) \| ![preview 8](17/preview_8.png) \| \| 18 \| 147 \| [Download](18/dataset.zip) \| ![preview 1](18/preview_1.png) \| ![preview 2](18/preview_2.png) \| ![preview 3](18/preview_3.png) \| ![preview 4](18/preview_4.png) \| ![preview 5](18/preview_5.png) \| ![preview 6](18/preview_6.png) \| ![preview 7](18/preview_7.png) \| ![preview 8](18/preview_8.png) \| \| 19 \| 6 \| [Download](19/dataset.zip) \| ![preview 1](19/preview_1.png) \| ![preview 2](19/preview_2.png) \| ![preview 3](19/preview_3.png) \| ![preview 4](19/preview_4.png) \| ![preview 5](19/preview_5.png) \| ![preview 6](19/preview_6.png) \| N/A \| N/A \| \| 20 \| 5 \| [Download](20/dataset.zip) \| ![preview 1](20/preview_1.png) \| ![preview 2](20/preview_2.png) \| ![preview 3](20/preview_3.png) \| ![preview 4](20/preview_4.png) \| ![preview 5](20/preview_5.png) \| N/A \| N/A \| N/A \| \| 21 \| 6 \| [Download](21/dataset.zip) \| ![preview 1](21/preview_1.png) \| ![preview 2](21/preview_2.png) \| ![preview 3](21/preview_3.png) \| ![preview 4](21/preview_4.png) \| ![preview 5](21/preview_5.png) \| ![preview 6](21/preview_6.png) \| N/A \| N/A \| \| noise \| 143 \| [Download](-1/dataset.zip) \| ![preview 1](-1/preview_1.png) \| ![preview 2](-1/preview_2.png) \| ![preview 3](-1/preview_3.png) \| ![preview 4](-1/preview_4.png) \| ![preview 5](-1/preview_5.png) \| ![preview 6](-1/preview_6.png) \| ![preview 7](-1/preview_7.png) \| ![preview 8](-1/preview_8.png) \|
vlsp-2023-vllm/en-to-vi-formal-informal-tranlations	--- dataset_info: features: - name: en dtype: string - name: vi dtype: string - name: fewshot_samples list: - name: en dtype: string - name: vi dtype: string splits: - name: val num_bytes: 178154 num_examples: 160 - name: test num_bytes: 175339 num_examples: 160 download_size: 124988 dataset_size: 353493 --- # Few-shot Translation ## Install To install `lm-eval` from the github repository main branch, run: ```bash git clone https://github.com/hieunguyen1053/lm-evaluation-harness cd lm-evaluation-harness pip install -e . ``` ## Basic Usage > Note: When reporting results from eval harness, please include the task versions (shown in `results["versions"]`) for reproducibility. This allows bug fixes to tasks while also ensuring that previously reported scores are reproducible. See the [Task Versioning](#task-versioning) section for more info. ### Hugging Face `transformers` To evaluate a model hosted on the [HuggingFace Hub](https://huggingface.co/models) (e.g. vlsp-2023-vllm/hoa-1b4) on `hellaswag_vi` you can use the following command: ```bash python main.py \ --model hf-causal \ --model_args pretrained=vlsp-2023-vllm/hoa-1b4 \ --tasks translation_vi \ --batch_size auto \ --device cuda:0 ``` Additional arguments can be provided to the model constructor using the `--model_args` flag. Most notably, this supports the common practice of using the `revisions` feature on the Hub to store partially trained checkpoints, or to specify the datatype for running a model: ```bash python main.py \ --model hf-causal \ --model_args pretrained=vlsp-2023-vllm/hoa-1b4,revision=step100000,dtype="float" \ --tasks translation_vi \ --device cuda:0 ``` To evaluate models that are loaded via `AutoSeq2SeqLM` in Huggingface, you instead use `hf-seq2seq`. To evaluate (causal) models across multiple GPUs, use `--model hf-causal-experimental` > Warning: Choosing the wrong model may result in erroneous outputs despite not erroring.
tner/btc	--- language: - en license: - other multilinguality: - monolingual size_categories: - 1k<10K task_categories: - token-classification task_ids: - named-entity-recognition pretty_name: BTC --- # Dataset Card for "tner/btc" ## Dataset Description - Repository: [T-NER](https://github.com/asahi417/tner) - Paper: [https://aclanthology.org/C16-1111/](https://aclanthology.org/C16-1111/) - Dataset: Broad Twitter Corpus - Domain: Twitter - Number of Entity: 3 ### Dataset Summary Broad Twitter Corpus NER dataset formatted in a part of [TNER](https://github.com/asahi417/tner) project. - Entity Types: `LOC`, `ORG`, `PER` ## Dataset Structure ### Data Instances An example of `train` looks as follows. ``` { 'tokens': ['I', 'hate', 'the', 'words', 'chunder', ',', 'vomit', 'and', 'puke', '.', 'BUUH', '.'], 'tags': [6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6] } ``` ### Label ID The label2id dictionary can be found at [here](https://huggingface.co/datasets/tner/btc/raw/main/dataset/label.json). ```python { "B-LOC": 0, "B-ORG": 1, "B-PER": 2, "I-LOC": 3, "I-ORG": 4, "I-PER": 5, "O": 6 } ``` ### Data Splits \| name \|train\|validation\|test\| \|---------\|----:\|---------:\|---:\| \|btc \| 6338\| 1001\|2000\| ### Citation Information ``` @inproceedings{derczynski-etal-2016-broad, title = "Broad {T}witter Corpus: A Diverse Named Entity Recognition Resource", author = "Derczynski, Leon and Bontcheva, Kalina and Roberts, Ian", booktitle = "Proceedings of {COLING} 2016, the 26th International Conference on Computational Linguistics: Technical Papers", month = dec, year = "2016", address = "Osaka, Japan", publisher = "The COLING 2016 Organizing Committee", url = "https://aclanthology.org/C16-1111", pages = "1169--1179", abstract = "One of the main obstacles, hampering method development and comparative evaluation of named entity recognition in social media, is the lack of a sizeable, diverse, high quality annotated corpus, analogous to the CoNLL{'}2003 news dataset. For instance, the biggest Ritter tweet corpus is only 45,000 tokens {--} a mere 15{\%} the size of CoNLL{'}2003. Another major shortcoming is the lack of temporal, geographic, and author diversity. This paper introduces the Broad Twitter Corpus (BTC), which is not only significantly bigger, but sampled across different regions, temporal periods, and types of Twitter users. The gold-standard named entity annotations are made by a combination of NLP experts and crowd workers, which enables us to harness crowd recall while maintaining high quality. We also measure the entity drift observed in our dataset (i.e. how entity representation varies over time), and compare to newswire. The corpus is released openly, including source text and intermediate annotations.", } ```
open-llm-leaderboard/details_posicube__Llama2-chat-AYT-13B	--- pretty_name: Evaluation run of posicube/Llama2-chat-AYT-13B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [posicube/Llama2-chat-AYT-13B](https://huggingface.co/posicube/Llama2-chat-AYT-13B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_posicube__Llama2-chat-AYT-13B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-25T23:47:31.356201](https://huggingface.co/datasets/open-llm-leaderboard/details_posicube__Llama2-chat-AYT-13B/blob/main/results_2023-10-25T23-47-31.356201.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\": 0.02380453020134228,\n\ \ \"em_stderr\": 0.0015611256256327542,\n \"f1\": 0.12621224832214753,\n\ \ \"f1_stderr\": 0.002357573309097525,\n \"acc\": 0.4247779852833908,\n\ \ \"acc_stderr\": 0.009910000290951314\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.02380453020134228,\n \"em_stderr\": 0.0015611256256327542,\n\ \ \"f1\": 0.12621224832214753,\n \"f1_stderr\": 0.002357573309097525\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0887035633055345,\n \ \ \"acc_stderr\": 0.007831458737058714\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.760852407261247,\n \"acc_stderr\": 0.011988541844843915\n\ \ }\n}\n```" repo_url: https://huggingface.co/posicube/Llama2-chat-AYT-13B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|arc:challenge\|25_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-12T13-56-43.141895.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_25T23_47_31.356201 path: - '/details_harness\|drop\|3_2023-10-25T23-47-31.356201.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-25T23-47-31.356201.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_25T23_47_31.356201 path: - '/details_harness\|gsm8k\|5_2023-10-25T23-47-31.356201.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-25T23-47-31.356201.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hellaswag\|10_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-12T13-56-43.141895.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-12T13-56-43.141895.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_12T13_56_43.141895 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-12T13-56-43.141895.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-12T13-56-43.141895.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_25T23_47_31.356201 path: - '/details_harness\|winogrande\|5_2023-10-25T23-47-31.356201.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-25T23-47-31.356201.parquet' - config_name: results data_files: - split: 2023_09_12T13_56_43.141895 path: - results_2023-09-12T13-56-43.141895.parquet - split: 2023_10_25T23_47_31.356201 path: - results_2023-10-25T23-47-31.356201.parquet - split: latest path: - results_2023-10-25T23-47-31.356201.parquet --- # Dataset Card for Evaluation run of posicube/Llama2-chat-AYT-13B ## Dataset Description - Homepage: - Repository: https://huggingface.co/posicube/Llama2-chat-AYT-13B - Paper: - Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - Point of Contact: clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [posicube/Llama2-chat-AYT-13B](https://huggingface.co/posicube/Llama2-chat-AYT-13B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_posicube__Llama2-chat-AYT-13B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-25T23:47:31.356201](https://huggingface.co/datasets/open-llm-leaderboard/details_posicube__Llama2-chat-AYT-13B/blob/main/results_2023-10-25T23-47-31.356201.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": 0.02380453020134228, "em_stderr": 0.0015611256256327542, "f1": 0.12621224832214753, "f1_stderr": 0.002357573309097525, "acc": 0.4247779852833908, "acc_stderr": 0.009910000290951314 }, "harness\|drop\|3": { "em": 0.02380453020134228, "em_stderr": 0.0015611256256327542, "f1": 0.12621224832214753, "f1_stderr": 0.002357573309097525 }, "harness\|gsm8k\|5": { "acc": 0.0887035633055345, "acc_stderr": 0.007831458737058714 }, "harness\|winogrande\|5": { "acc": 0.760852407261247, "acc_stderr": 0.011988541844843915 } } ``` ### 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]
Lotem/check	--- license: bigscience-openrail-m ---
Crosstyan/danbooru-public	--- tags: - danbooru --- # Danbooru Public Danbooru database which including metadata for ["posts"](https://danbooru.donmai.us/wiki_pages/help:posts), ["tags"](https://danbooru.donmai.us/wiki_pages/help:tags) and ["artists"](https://danbooru.donmai.us/artists). Download from [danbooru public google cloud storage](https://console.cloud.google.com/storage/browser/danbooru_public/data?project=danbooru1). Updated at 2023/11/30. Data are encoded with [JSON Lines](https://jsonlines.org/). ```bash tar -xJf tags.tar.xz tar -xJf artists.tar.xz # posts.tar.br is compressed with brotli # --use-compress-program might also works # please note that the output is near 20GB brotli --decompress --stdout posts.tar.br \| tar -xf ``` ## See also - [crosstyan/explore-danbooru](https://github.com/crosstyan/explore-danbooru)
DElmazi/Student_Performance	--- license: cc-by-4.0 task_categories: - feature-extraction language: - en tags: - linear regression size_categories: - n<1K ---
ayeshgk/java_bug_fix_ctx_err_small	--- license: mit dataset_info: features: - name: id dtype: int64 - name: buggy dtype: string - name: fixed dtype: string - name: bug_err_ctx dtype: string splits: - name: train num_bytes: 42495 num_examples: 75 - name: validation num_bytes: 15439 num_examples: 27 - name: test num_bytes: 2614 num_examples: 6 download_size: 25983 dataset_size: 60548 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
severo/test_gated_with_extra_fields	--- extra_gated_prompt: "You agree not to attempt to determine the identity of individuals in this dataset" extra_gated_fields: Company: text Country: text I agree to use this model for non-commercial use ONLY: checkbox ---
AppleHarem/plume_arknights	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of plume (Arknights) This is the dataset of plume (Arknights), containing 131 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). This is a WebUI contains crawlers and other thing: ([LittleAppleWebUI](https://github.com/LittleApple-fp16/LittleAppleWebUI)) \| Name \| Images \| Download \| Description \| \|:----------------\|---------:\|:----------------------------------------\|:-----------------------------------------------------------------------------------------\| \| raw \| 131 \| [Download](dataset-raw.zip) \| Raw data with meta information. \| \| raw-stage3 \| 335 \| [Download](dataset-raw-stage3.zip) \| 3-stage cropped raw data with meta information. \| \| raw-stage3-eyes \| 356 \| [Download](dataset-raw-stage3-eyes.zip) \| 3-stage cropped (with eye-focus) raw data with meta information. \| \| 384x512 \| 131 \| [Download](dataset-384x512.zip) \| 384x512 aligned dataset. \| \| 512x704 \| 131 \| [Download](dataset-512x704.zip) \| 512x704 aligned dataset. \| \| 640x880 \| 131 \| [Download](dataset-640x880.zip) \| 640x880 aligned dataset. \| \| stage3-640 \| 335 \| [Download](dataset-stage3-640.zip) \| 3-stage cropped dataset with the shorter side not exceeding 640 pixels. \| \| stage3-800 \| 335 \| [Download](dataset-stage3-800.zip) \| 3-stage cropped dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p512-640 \| 252 \| [Download](dataset-stage3-p512-640.zip) \| 3-stage cropped dataset with the area not less than 512x512 pixels. \| \| stage3-eyes-640 \| 356 \| [Download](dataset-stage3-eyes-640.zip) \| 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 640 pixels. \| \| stage3-eyes-800 \| 356 \| [Download](dataset-stage3-eyes-800.zip) \| 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 800 pixels. \|
loubnabnl/coffeescript_checks	--- dataset_info: features: - name: entities list: - name: context dtype: string - name: end dtype: int64 - name: score dtype: float32 - name: start dtype: int64 - name: tag dtype: string - name: value dtype: string - name: max_stars_repo_path dtype: string - name: max_stars_repo_name dtype: string - name: max_stars_count dtype: int64 - name: content dtype: string - name: id dtype: string - name: new_content dtype: string - name: modified dtype: bool - name: references dtype: string splits: - name: train num_bytes: 202822078.3919738 num_examples: 23874 download_size: 202150872 dataset_size: 202822078.3919738 --- # Dataset Card for "coffeescript_checks" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
kardosdrur/europarl-scandinavian	--- license: mit configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: da dtype: string - name: en dtype: string - name: sv dtype: string splits: - name: train num_bytes: 620348322.4 num_examples: 1304296 - name: test num_bytes: 155087080.6 num_examples: 326074 download_size: 488376564 dataset_size: 775435403.0 --- # Europarl Scandinavian Languages The data originates from the Europarl parallel corpus, where English transcriptions of parliamentary discussions were aligned with a number of other languages algorithmically. In order to align Danish and Swedish corpora in the dataset, English entries were hashed with 128bit Murmurhash3, and the Danish and Swedish transcriptions were joined on the obtained hash values. Entries that had more than one pair in the other dataset were removed, this ensures that no false positives due to hash collisions got into the dataset. Source code is available in the repository. The dataset was created for aiding the training of sentence transformer models in the Danish Foundation Models project.
incodesatx/siddhu	--- license: artistic-2.0 ---
open-llm-leaderboard/details_nbeerbower__bruphin-lambda	--- pretty_name: Evaluation run of nbeerbower/bruphin-lambda dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [nbeerbower/bruphin-lambda](https://huggingface.co/nbeerbower/bruphin-lambda)\ \ 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_nbeerbower__bruphin-lambda\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-04-02T15:48:06.692625](https://huggingface.co/datasets/open-llm-leaderboard/details_nbeerbower__bruphin-lambda/blob/main/results_2024-04-02T15-48-06.692625.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\": 0.6550555752321207,\n\ \ \"acc_stderr\": 0.03195494564401327,\n \"acc_norm\": 0.6541965490035271,\n\ \ \"acc_norm_stderr\": 0.032626014745260334,\n \"mc1\": 0.5740514075887393,\n\ \ \"mc1_stderr\": 0.01731047190407654,\n \"mc2\": 0.7235913354163169,\n\ \ \"mc2_stderr\": 0.014717519704367223\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.7013651877133106,\n \"acc_stderr\": 0.013374078615068744,\n\ \ \"acc_norm\": 0.7235494880546075,\n \"acc_norm_stderr\": 0.013069662474252423\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.7133041226847242,\n\ \ \"acc_stderr\": 0.004512940497462743,\n \"acc_norm\": 0.882194781915953,\n\ \ \"acc_norm_stderr\": 0.003217184906847943\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.36,\n \"acc_stderr\": 0.04824181513244218,\n \ \ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.04824181513244218\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6592592592592592,\n\ \ \"acc_stderr\": 0.040943762699967926,\n \"acc_norm\": 0.6592592592592592,\n\ \ \"acc_norm_stderr\": 0.040943762699967926\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.7039473684210527,\n \"acc_stderr\": 0.03715062154998904,\n\ \ \"acc_norm\": 0.7039473684210527,\n \"acc_norm_stderr\": 0.03715062154998904\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.65,\n\ \ \"acc_stderr\": 0.0479372485441102,\n \"acc_norm\": 0.65,\n \ \ \"acc_norm_stderr\": 0.0479372485441102\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6981132075471698,\n \"acc_stderr\": 0.02825420034443866,\n\ \ \"acc_norm\": 0.6981132075471698,\n \"acc_norm_stderr\": 0.02825420034443866\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7777777777777778,\n\ \ \"acc_stderr\": 0.03476590104304134,\n \"acc_norm\": 0.7777777777777778,\n\ \ \"acc_norm_stderr\": 0.03476590104304134\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.47,\n \"acc_stderr\": 0.050161355804659205,\n \ \ \"acc_norm\": 0.47,\n \"acc_norm_stderr\": 0.050161355804659205\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.55,\n \"acc_stderr\": 0.05,\n \"acc_norm\": 0.55,\n \ \ \"acc_norm_stderr\": 0.05\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6589595375722543,\n\ \ \"acc_stderr\": 0.03614665424180826,\n \"acc_norm\": 0.6589595375722543,\n\ \ \"acc_norm_stderr\": 0.03614665424180826\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.4117647058823529,\n \"acc_stderr\": 0.048971049527263666,\n\ \ \"acc_norm\": 0.4117647058823529,\n \"acc_norm_stderr\": 0.048971049527263666\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.76,\n \"acc_stderr\": 0.04292346959909282,\n \"acc_norm\": 0.76,\n\ \ \"acc_norm_stderr\": 0.04292346959909282\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5702127659574469,\n \"acc_stderr\": 0.03236214467715564,\n\ \ \"acc_norm\": 0.5702127659574469,\n \"acc_norm_stderr\": 0.03236214467715564\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.47368421052631576,\n\ \ \"acc_stderr\": 0.046970851366478626,\n \"acc_norm\": 0.47368421052631576,\n\ \ \"acc_norm_stderr\": 0.046970851366478626\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5379310344827586,\n \"acc_stderr\": 0.04154659671707548,\n\ \ \"acc_norm\": 0.5379310344827586,\n \"acc_norm_stderr\": 0.04154659671707548\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.43386243386243384,\n \"acc_stderr\": 0.025525034382474887,\n \"\ acc_norm\": 0.43386243386243384,\n \"acc_norm_stderr\": 0.025525034382474887\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\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7903225806451613,\n\ \ \"acc_stderr\": 0.023157879349083522,\n \"acc_norm\": 0.7903225806451613,\n\ \ \"acc_norm_stderr\": 0.023157879349083522\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.5123152709359606,\n \"acc_stderr\": 0.035169204442208966,\n\ \ \"acc_norm\": 0.5123152709359606,\n \"acc_norm_stderr\": 0.035169204442208966\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\"\ : 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7818181818181819,\n \"acc_stderr\": 0.03225078108306289,\n\ \ \"acc_norm\": 0.7818181818181819,\n \"acc_norm_stderr\": 0.03225078108306289\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.803030303030303,\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\": 0.917098445595855,\n \"acc_stderr\": 0.01989934131572178,\n\ \ \"acc_norm\": 0.917098445595855,\n \"acc_norm_stderr\": 0.01989934131572178\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6641025641025641,\n \"acc_stderr\": 0.023946724741563976,\n\ \ \"acc_norm\": 0.6641025641025641,\n \"acc_norm_stderr\": 0.023946724741563976\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3333333333333333,\n \"acc_stderr\": 0.02874204090394848,\n \ \ \"acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.02874204090394848\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6596638655462185,\n \"acc_stderr\": 0.03077805742293167,\n \ \ \"acc_norm\": 0.6596638655462185,\n \"acc_norm_stderr\": 0.03077805742293167\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.3576158940397351,\n \"acc_stderr\": 0.03913453431177258,\n \"\ acc_norm\": 0.3576158940397351,\n \"acc_norm_stderr\": 0.03913453431177258\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8477064220183487,\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\"\ : 0.5138888888888888,\n \"acc_stderr\": 0.034086558679777494,\n \"\ acc_norm\": 0.5138888888888888,\n \"acc_norm_stderr\": 0.034086558679777494\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8431372549019608,\n \"acc_stderr\": 0.025524722324553346,\n \"\ acc_norm\": 0.8431372549019608,\n \"acc_norm_stderr\": 0.025524722324553346\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8059071729957806,\n \"acc_stderr\": 0.025744902532290916,\n \ \ \"acc_norm\": 0.8059071729957806,\n \"acc_norm_stderr\": 0.025744902532290916\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6860986547085202,\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\": 0.816793893129771,\n \"acc_stderr\": 0.03392770926494733,\n\ \ \"acc_norm\": 0.816793893129771,\n \"acc_norm_stderr\": 0.03392770926494733\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7851239669421488,\n \"acc_stderr\": 0.037494924487096966,\n \"\ acc_norm\": 0.7851239669421488,\n \"acc_norm_stderr\": 0.037494924487096966\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7870370370370371,\n\ \ \"acc_stderr\": 0.0395783547198098,\n \"acc_norm\": 0.7870370370370371,\n\ \ \"acc_norm_stderr\": 0.0395783547198098\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7791411042944786,\n \"acc_stderr\": 0.03259177392742178,\n\ \ \"acc_norm\": 0.7791411042944786,\n \"acc_norm_stderr\": 0.03259177392742178\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.42857142857142855,\n\ \ \"acc_stderr\": 0.04697113923010212,\n \"acc_norm\": 0.42857142857142855,\n\ \ \"acc_norm_stderr\": 0.04697113923010212\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7572815533980582,\n \"acc_stderr\": 0.04245022486384495,\n\ \ \"acc_norm\": 0.7572815533980582,\n \"acc_norm_stderr\": 0.04245022486384495\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8846153846153846,\n\ \ \"acc_stderr\": 0.02093019318517933,\n \"acc_norm\": 0.8846153846153846,\n\ \ \"acc_norm_stderr\": 0.02093019318517933\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.72,\n \"acc_stderr\": 0.045126085985421276,\n \ \ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.045126085985421276\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8250319284802043,\n\ \ \"acc_stderr\": 0.013586619219903343,\n \"acc_norm\": 0.8250319284802043,\n\ \ \"acc_norm_stderr\": 0.013586619219903343\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7485549132947977,\n \"acc_stderr\": 0.02335736578587403,\n\ \ \"acc_norm\": 0.7485549132947977,\n \"acc_norm_stderr\": 0.02335736578587403\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.43575418994413406,\n\ \ \"acc_stderr\": 0.016583881958602394,\n \"acc_norm\": 0.43575418994413406,\n\ \ \"acc_norm_stderr\": 0.016583881958602394\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7254901960784313,\n \"acc_stderr\": 0.025553169991826524,\n\ \ \"acc_norm\": 0.7254901960784313,\n \"acc_norm_stderr\": 0.025553169991826524\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\": 0.7623456790123457,\n \"acc_stderr\": 0.02368359183700856,\n\ \ \"acc_norm\": 0.7623456790123457,\n \"acc_norm_stderr\": 0.02368359183700856\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.4929078014184397,\n \"acc_stderr\": 0.02982449855912901,\n \ \ \"acc_norm\": 0.4929078014184397,\n \"acc_norm_stderr\": 0.02982449855912901\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.47783572359843546,\n\ \ \"acc_stderr\": 0.012757683047716172,\n \"acc_norm\": 0.47783572359843546,\n\ \ \"acc_norm_stderr\": 0.012757683047716172\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6764705882352942,\n \"acc_stderr\": 0.02841820861940676,\n\ \ \"acc_norm\": 0.6764705882352942,\n \"acc_norm_stderr\": 0.02841820861940676\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6813725490196079,\n \"acc_stderr\": 0.01885008469646872,\n \ \ \"acc_norm\": 0.6813725490196079,\n \"acc_norm_stderr\": 0.01885008469646872\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.7,\n\ \ \"acc_stderr\": 0.04389311454644286,\n \"acc_norm\": 0.7,\n \ \ \"acc_norm_stderr\": 0.04389311454644286\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7306122448979592,\n \"acc_stderr\": 0.02840125202902294,\n\ \ \"acc_norm\": 0.7306122448979592,\n \"acc_norm_stderr\": 0.02840125202902294\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8258706467661692,\n\ \ \"acc_stderr\": 0.026814951200421603,\n \"acc_norm\": 0.8258706467661692,\n\ \ \"acc_norm_stderr\": 0.026814951200421603\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.85,\n \"acc_stderr\": 0.0358870281282637,\n \ \ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.0358870281282637\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5602409638554217,\n\ \ \"acc_stderr\": 0.03864139923699122,\n \"acc_norm\": 0.5602409638554217,\n\ \ \"acc_norm_stderr\": 0.03864139923699122\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\": 0.5740514075887393,\n\ \ \"mc1_stderr\": 0.01731047190407654,\n \"mc2\": 0.7235913354163169,\n\ \ \"mc2_stderr\": 0.014717519704367223\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8445146014206788,\n \"acc_stderr\": 0.010184308214775777\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.7073540561031084,\n \ \ \"acc_stderr\": 0.012532334368242887\n }\n}\n```" repo_url: https://huggingface.co/nbeerbower/bruphin-lambda 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_02T15_48_06.692625 path: - '/details_harness\|arc:challenge\|25_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-04-02T15-48-06.692625.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|gsm8k\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hellaswag\|10_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-04-02T15-48-06.692625.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-management\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-virology\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-04-02T15-48-06.692625.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|truthfulqa:mc\|0_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-04-02T15-48-06.692625.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_04_02T15_48_06.692625 path: - '/details_harness\|winogrande\|5_2024-04-02T15-48-06.692625.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-04-02T15-48-06.692625.parquet' - config_name: results data_files: - split: 2024_04_02T15_48_06.692625 path: - results_2024-04-02T15-48-06.692625.parquet - split: latest path: - results_2024-04-02T15-48-06.692625.parquet --- # Dataset Card for Evaluation run of nbeerbower/bruphin-lambda <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [nbeerbower/bruphin-lambda](https://huggingface.co/nbeerbower/bruphin-lambda) 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_nbeerbower__bruphin-lambda", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-04-02T15:48:06.692625](https://huggingface.co/datasets/open-llm-leaderboard/details_nbeerbower__bruphin-lambda/blob/main/results_2024-04-02T15-48-06.692625.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": 0.6550555752321207, "acc_stderr": 0.03195494564401327, "acc_norm": 0.6541965490035271, "acc_norm_stderr": 0.032626014745260334, "mc1": 0.5740514075887393, "mc1_stderr": 0.01731047190407654, "mc2": 0.7235913354163169, "mc2_stderr": 0.014717519704367223 }, "harness\|arc:challenge\|25": { "acc": 0.7013651877133106, "acc_stderr": 0.013374078615068744, "acc_norm": 0.7235494880546075, "acc_norm_stderr": 0.013069662474252423 }, "harness\|hellaswag\|10": { "acc": 0.7133041226847242, "acc_stderr": 0.004512940497462743, "acc_norm": 0.882194781915953, "acc_norm_stderr": 0.003217184906847943 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6592592592592592, "acc_stderr": 0.040943762699967926, "acc_norm": 0.6592592592592592, "acc_norm_stderr": 0.040943762699967926 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.7039473684210527, "acc_stderr": 0.03715062154998904, "acc_norm": 0.7039473684210527, "acc_norm_stderr": 0.03715062154998904 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.65, "acc_stderr": 0.0479372485441102, "acc_norm": 0.65, "acc_norm_stderr": 0.0479372485441102 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6981132075471698, "acc_stderr": 0.02825420034443866, "acc_norm": 0.6981132075471698, "acc_norm_stderr": 0.02825420034443866 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7777777777777778, "acc_stderr": 0.03476590104304134, "acc_norm": 0.7777777777777778, "acc_norm_stderr": 0.03476590104304134 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.55, "acc_stderr": 0.05, "acc_norm": 0.55, "acc_norm_stderr": 0.05 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6589595375722543, "acc_stderr": 0.03614665424180826, "acc_norm": 0.6589595375722543, "acc_norm_stderr": 0.03614665424180826 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.4117647058823529, "acc_stderr": 0.048971049527263666, "acc_norm": 0.4117647058823529, "acc_norm_stderr": 0.048971049527263666 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.76, "acc_stderr": 0.04292346959909282, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909282 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5702127659574469, "acc_stderr": 0.03236214467715564, "acc_norm": 0.5702127659574469, "acc_norm_stderr": 0.03236214467715564 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.47368421052631576, "acc_stderr": 0.046970851366478626, "acc_norm": 0.47368421052631576, "acc_norm_stderr": 0.046970851366478626 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5379310344827586, "acc_stderr": 0.04154659671707548, "acc_norm": 0.5379310344827586, "acc_norm_stderr": 0.04154659671707548 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.43386243386243384, "acc_stderr": 0.025525034382474887, "acc_norm": 0.43386243386243384, "acc_norm_stderr": 0.025525034382474887 }, "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": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7903225806451613, "acc_stderr": 0.023157879349083522, "acc_norm": 0.7903225806451613, "acc_norm_stderr": 0.023157879349083522 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.5123152709359606, "acc_stderr": 0.035169204442208966, "acc_norm": 0.5123152709359606, "acc_norm_stderr": 0.035169204442208966 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7818181818181819, "acc_stderr": 0.03225078108306289, "acc_norm": 0.7818181818181819, "acc_norm_stderr": 0.03225078108306289 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.803030303030303, "acc_stderr": 0.028335609732463362, "acc_norm": 0.803030303030303, "acc_norm_stderr": 0.028335609732463362 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.917098445595855, "acc_stderr": 0.01989934131572178, "acc_norm": 0.917098445595855, "acc_norm_stderr": 0.01989934131572178 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6641025641025641, "acc_stderr": 0.023946724741563976, "acc_norm": 0.6641025641025641, "acc_norm_stderr": 0.023946724741563976 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.02874204090394848, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.02874204090394848 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6596638655462185, "acc_stderr": 0.03077805742293167, "acc_norm": 0.6596638655462185, "acc_norm_stderr": 0.03077805742293167 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.3576158940397351, "acc_stderr": 0.03913453431177258, "acc_norm": 0.3576158940397351, "acc_norm_stderr": 0.03913453431177258 }, "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": 0.5138888888888888, "acc_stderr": 0.034086558679777494, "acc_norm": 0.5138888888888888, "acc_norm_stderr": 0.034086558679777494 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8431372549019608, "acc_stderr": 0.025524722324553346, "acc_norm": 0.8431372549019608, "acc_norm_stderr": 0.025524722324553346 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8059071729957806, "acc_stderr": 0.025744902532290916, "acc_norm": 0.8059071729957806, "acc_norm_stderr": 0.025744902532290916 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6860986547085202, "acc_stderr": 0.031146796482972465, "acc_norm": 0.6860986547085202, "acc_norm_stderr": 0.031146796482972465 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.816793893129771, "acc_stderr": 0.03392770926494733, "acc_norm": 0.816793893129771, "acc_norm_stderr": 0.03392770926494733 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7851239669421488, "acc_stderr": 0.037494924487096966, "acc_norm": 0.7851239669421488, "acc_norm_stderr": 0.037494924487096966 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7870370370370371, "acc_stderr": 0.0395783547198098, "acc_norm": 0.7870370370370371, "acc_norm_stderr": 0.0395783547198098 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7791411042944786, "acc_stderr": 0.03259177392742178, "acc_norm": 0.7791411042944786, "acc_norm_stderr": 0.03259177392742178 }, "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": 0.7572815533980582, "acc_stderr": 0.04245022486384495, "acc_norm": 0.7572815533980582, "acc_norm_stderr": 0.04245022486384495 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8846153846153846, "acc_stderr": 0.02093019318517933, "acc_norm": 0.8846153846153846, "acc_norm_stderr": 0.02093019318517933 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.72, "acc_stderr": 0.045126085985421276, "acc_norm": 0.72, "acc_norm_stderr": 0.045126085985421276 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8250319284802043, "acc_stderr": 0.013586619219903343, "acc_norm": 0.8250319284802043, "acc_norm_stderr": 0.013586619219903343 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7485549132947977, "acc_stderr": 0.02335736578587403, "acc_norm": 0.7485549132947977, "acc_norm_stderr": 0.02335736578587403 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.43575418994413406, "acc_stderr": 0.016583881958602394, "acc_norm": 0.43575418994413406, "acc_norm_stderr": 0.016583881958602394 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7254901960784313, "acc_stderr": 0.025553169991826524, "acc_norm": 0.7254901960784313, "acc_norm_stderr": 0.025553169991826524 }, "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": 0.7623456790123457, "acc_stderr": 0.02368359183700856, "acc_norm": 0.7623456790123457, "acc_norm_stderr": 0.02368359183700856 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4929078014184397, "acc_stderr": 0.02982449855912901, "acc_norm": 0.4929078014184397, "acc_norm_stderr": 0.02982449855912901 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.47783572359843546, "acc_stderr": 0.012757683047716172, "acc_norm": 0.47783572359843546, "acc_norm_stderr": 0.012757683047716172 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6764705882352942, "acc_stderr": 0.02841820861940676, "acc_norm": 0.6764705882352942, "acc_norm_stderr": 0.02841820861940676 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6813725490196079, "acc_stderr": 0.01885008469646872, "acc_norm": 0.6813725490196079, "acc_norm_stderr": 0.01885008469646872 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.7, "acc_stderr": 0.04389311454644286, "acc_norm": 0.7, "acc_norm_stderr": 0.04389311454644286 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7306122448979592, "acc_stderr": 0.02840125202902294, "acc_norm": 0.7306122448979592, "acc_norm_stderr": 0.02840125202902294 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8258706467661692, "acc_stderr": 0.026814951200421603, "acc_norm": 0.8258706467661692, "acc_norm_stderr": 0.026814951200421603 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.85, "acc_stderr": 0.0358870281282637, "acc_norm": 0.85, "acc_norm_stderr": 0.0358870281282637 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5602409638554217, "acc_stderr": 0.03864139923699122, "acc_norm": 0.5602409638554217, "acc_norm_stderr": 0.03864139923699122 }, "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": 0.5740514075887393, "mc1_stderr": 0.01731047190407654, "mc2": 0.7235913354163169, "mc2_stderr": 0.014717519704367223 }, "harness\|winogrande\|5": { "acc": 0.8445146014206788, "acc_stderr": 0.010184308214775777 }, "harness\|gsm8k\|5": { "acc": 0.7073540561031084, "acc_stderr": 0.012532334368242887 } } ``` ## 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]
ConseggioLigure/seed-instruct-eng-lij	--- license: cc-by-sa-4.0 task_categories: - conversational - translation pretty_name: OLDI Seed eng-lij translation dataset (instruction-style) dataset_info: features: - name: inputs dtype: string - name: targets dtype: string - name: template_id dtype: int64 - name: template_lang sequence: string splits: - name: train num_bytes: 2347477 num_examples: 5802 - name: dev num_bytes: 79012 num_examples: 189 - name: test num_bytes: 86660 num_examples: 202 download_size: 1299002 dataset_size: 2513149 configs: - config_name: default data_files: - split: train path: data/train-* - split: dev path: data/dev-* - split: test path: data/test-* --- This is an English→Ligurian sentence-level translation dataset. The original data comes from the [OLDI](https://www.oldi.org) [Seed dataset](https://github.com/openlanguagedata/seed), and it has been converted to the instruction format. The prompts, written in English, ask the model to translate the text to Ligurian. There are several variants of the prompt which were randomly sampled for each sentence: The prompts variously refer to the language as Ligurian and Genoese (the specific dialect of Ligurian used in this datset): ``` Translate to Ligurian: \<sentence> Translate to Ligurian (Genoese): \<sentence> Translate to Genoese: \<sentence> Translate from English to Ligurian: \<sentence> Translate from English to Genoese: \<sentence> Translate from English to Ligurian (Genoese dialect): \<sentence> Translate this sentence to Ligurian: \<sentence> Translate this sentence to Genoese: \<sentence> What’s the Ligurian translation of this sentence? \<sentence> What’s the Genoese translation of this sentence? \<sentence> Can you translate this text to Ligurian? \<sentence> ``` The template used for each dataset entry is referenced in the column `template_id`, with ids ranging from 1 to 11 according to the order given above. The targets are always prefixed with the string "The Ligurian (Genoese) translation is: \<sentence>". The correspondence between `template_id`, prompt template and target template is therefore: ``` [ (1, "Translate to Ligurian:\n", "The Ligurian (Genoese) translation is:\n"), (2, "Translate to Ligurian (Genoese):\n", "The Ligurian (Genoese) translation is:\n"), (3, "Translate to Genoese:\n", "The Ligurian (Genoese) translation is:\n"), (4, "Translate from English to Ligurian:\n", "The Ligurian (Genoese) translation is:\n"), (5, "Translate from English to Genoese:\n", "The Ligurian (Genoese) translation is:\n"), (6, "Translate from English to Ligurian (Genoese dialect):\n", "The Ligurian (Genoese) translation is:\n"), (7, "Translate this sentence to Ligurian:\n", "The Ligurian (Genoese) translation is:\n"), (8, "Translate this sentence to Genoese:\n", "The Ligurian (Genoese) translation is:\n"), (9, "What’s the Ligurian translation of this sentence?\n", "The Ligurian (Genoese) translation is:\n"), (10, "What’s the Genoese translation of this sentence?\n", "The Ligurian (Genoese) translation is:\n"), (11, "Can you translate this text to Ligurian?\n", "The Ligurian (Genoese) translation is:\n"), ] ``` The dataset contains 5802 train samples, 190 validation samples and 201 test samples.
AnyaSchen/russian_poetry_with_keywords	--- dataset_info: features: - name: text dtype: string - name: author dtype: string - name: keywords dtype: string splits: - name: train num_bytes: 4073925 num_examples: 7755 download_size: 2114437 dataset_size: 4073925 --- # Dataset Card for "russian_poetry_with_keywords" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
RinaL/lemmy-world-comments	--- license: apache-2.0 --- This is a data set of lemmy.world comments.
brandnewx/sd-v1-5	--- license: creativeml-openrail-m ---
Nexdata/Emotional_Video_Data	--- YAML tags: - copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging --- # Dataset Card for Nexdata/Emotional_Video_Data ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/977?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 1,003 People - Emotional Video Data. The data diversity includes multiple races, multiple indoor scenes, multiple age groups, multiple languages, multiple emotions (11 types of facial emotions, 15 types of inner emotions). For each sentence in each video, emotion types (including facial emotions and inner emotions), start & end time, and text transcription were annotated.This dataset can be used for tasks such as emotion recognition and sentiment analysis. For more details, please refer to the link: https://www.nexdata.ai/datasets/977?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification, sentiment-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages English, Chinese ## 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 Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions
myanmar_news	--- annotations_creators: - found language_creators: - found language: - my license: - gpl-3.0 multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - text-classification task_ids: - topic-classification pretty_name: MyanmarNews dataset_info: features: - name: text dtype: string - name: category dtype: class_label: names: '0': Sport '1': Politic '2': Business '3': Entertainment splits: - name: train num_bytes: 3797368 num_examples: 8116 download_size: 610592 dataset_size: 3797368 --- # Dataset Card for Myanmar_News ## Dataset Description - Repository: https://github.com/ayehninnkhine/MyanmarNewsClassificationSystem ### Dataset Summary The Myanmar news dataset contains article snippets in four categories: Business, Entertainment, Politics, and Sport. These were collected in October 2017 by Aye Hninn Khine ### Languages Myanmar/Burmese language ## Dataset Structure ### Data Fields - text - text from article - category - a topic: Business, Entertainment, Politic, or Sport (note spellings) ### Data Splits One training set (8,116 total rows) ### Source Data #### Initial Data Collection and Normalization Data was collected by Aye Hninn Khine and shared on GitHub with a GPL-3.0 license. Multiple text files were consolidated into one labeled CSV file by Nick Doiron. ## Additional Information ### Dataset Curators Contributors to original GitHub repo: - https://github.com/ayehninnkhine ### Licensing Information GPL-3.0 ### Citation Information See https://github.com/ayehninnkhine/MyanmarNewsClassificationSystem ### Contributions Thanks to [@mapmeld](https://github.com/mapmeld) for adding this dataset.
cyanelis/15485	--- license: cc-by-nc-4.0 ---
qbwmwsap/amber-data-arxiv-chunked-360	--- license: mit dataset_info: features: - name: token_ids sequence: int64 - name: source dtype: string splits: - name: train num_bytes: 419644080 num_examples: 25560 download_size: 81857266 dataset_size: 419644080 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_NLUHOPOE__test-case-0	--- pretty_name: Evaluation run of NLUHOPOE/test-case-0 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [NLUHOPOE/test-case-0](https://huggingface.co/NLUHOPOE/test-case-0) 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_NLUHOPOE__test-case-0\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-02-16T05:25:06.093843](https://huggingface.co/datasets/open-llm-leaderboard/details_NLUHOPOE__test-case-0/blob/main/results_2024-02-16T05-25-06.093843.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\": 0.5791278236658676,\n\ \ \"acc_stderr\": 0.033494817808173614,\n \"acc_norm\": 0.5837595891503912,\n\ \ \"acc_norm_stderr\": 0.03419368461778056,\n \"mc1\": 0.3268053855569155,\n\ \ \"mc1_stderr\": 0.01641987473113503,\n \"mc2\": 0.4880155663864428,\n\ \ \"mc2_stderr\": 0.015371746911854285\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5349829351535836,\n \"acc_stderr\": 0.01457558392201967,\n\ \ \"acc_norm\": 0.5750853242320819,\n \"acc_norm_stderr\": 0.014445698968520769\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5997809201354312,\n\ \ \"acc_stderr\": 0.004889413126208774,\n \"acc_norm\": 0.796355307707628,\n\ \ \"acc_norm_stderr\": 0.004018847286468061\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.4888888888888889,\n\ \ \"acc_stderr\": 0.04318275491977976,\n \"acc_norm\": 0.4888888888888889,\n\ \ \"acc_norm_stderr\": 0.04318275491977976\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.5855263157894737,\n \"acc_stderr\": 0.04008973785779206,\n\ \ \"acc_norm\": 0.5855263157894737,\n \"acc_norm_stderr\": 0.04008973785779206\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|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-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6490566037735849,\n \"acc_stderr\": 0.02937364625323469,\n\ \ \"acc_norm\": 0.6490566037735849,\n \"acc_norm_stderr\": 0.02937364625323469\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.6736111111111112,\n\ \ \"acc_stderr\": 0.03921067198982266,\n \"acc_norm\": 0.6736111111111112,\n\ \ \"acc_norm_stderr\": 0.03921067198982266\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \ \ \"acc_norm\": 0.44,\n \"acc_norm_stderr\": 0.04988876515698589\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.45,\n \"acc_stderr\": 0.049999999999999996,\n \"acc_norm\": 0.45,\n\ \ \"acc_norm_stderr\": 0.049999999999999996\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.04923659639173309,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04923659639173309\n },\n\ \ \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.5086705202312138,\n\ \ \"acc_stderr\": 0.03811890988940412,\n \"acc_norm\": 0.5086705202312138,\n\ \ \"acc_norm_stderr\": 0.03811890988940412\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.3137254901960784,\n \"acc_stderr\": 0.04617034827006718,\n\ \ \"acc_norm\": 0.3137254901960784,\n \"acc_norm_stderr\": 0.04617034827006718\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\": 0.69,\n\ \ \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.46382978723404256,\n \"acc_stderr\": 0.032600385118357715,\n\ \ \"acc_norm\": 0.46382978723404256,\n \"acc_norm_stderr\": 0.032600385118357715\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.39473684210526316,\n\ \ \"acc_stderr\": 0.045981880578165414,\n \"acc_norm\": 0.39473684210526316,\n\ \ \"acc_norm_stderr\": 0.045981880578165414\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\"\ : 0.3783068783068783,\n \"acc_stderr\": 0.024976954053155254,\n \"\ acc_norm\": 0.3783068783068783,\n \"acc_norm_stderr\": 0.024976954053155254\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.3888888888888889,\n\ \ \"acc_stderr\": 0.04360314860077459,\n \"acc_norm\": 0.3888888888888889,\n\ \ \"acc_norm_stderr\": 0.04360314860077459\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.35,\n \"acc_stderr\": 0.0479372485441102,\n \ \ \"acc_norm\": 0.35,\n \"acc_norm_stderr\": 0.0479372485441102\n },\n\ \ \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7129032258064516,\n\ \ \"acc_stderr\": 0.025736542745594528,\n \"acc_norm\": 0.7129032258064516,\n\ \ \"acc_norm_stderr\": 0.025736542745594528\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.43842364532019706,\n \"acc_stderr\": 0.03491207857486518,\n\ \ \"acc_norm\": 0.43842364532019706,\n \"acc_norm_stderr\": 0.03491207857486518\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.64,\n \"acc_stderr\": 0.048241815132442176,\n \"acc_norm\"\ : 0.64,\n \"acc_norm_stderr\": 0.048241815132442176\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7878787878787878,\n \"acc_stderr\": 0.03192271569548301,\n\ \ \"acc_norm\": 0.7878787878787878,\n \"acc_norm_stderr\": 0.03192271569548301\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7272727272727273,\n \"acc_stderr\": 0.03173071239071724,\n \"\ acc_norm\": 0.7272727272727273,\n \"acc_norm_stderr\": 0.03173071239071724\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8238341968911918,\n \"acc_stderr\": 0.027493504244548047,\n\ \ \"acc_norm\": 0.8238341968911918,\n \"acc_norm_stderr\": 0.027493504244548047\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.5923076923076923,\n \"acc_stderr\": 0.02491524398598785,\n \ \ \"acc_norm\": 0.5923076923076923,\n \"acc_norm_stderr\": 0.02491524398598785\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.32592592592592595,\n \"acc_stderr\": 0.02857834836547308,\n \ \ \"acc_norm\": 0.32592592592592595,\n \"acc_norm_stderr\": 0.02857834836547308\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6554621848739496,\n \"acc_stderr\": 0.030868682604121626,\n\ \ \"acc_norm\": 0.6554621848739496,\n \"acc_norm_stderr\": 0.030868682604121626\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.2913907284768212,\n \"acc_stderr\": 0.03710185726119994,\n \"\ acc_norm\": 0.2913907284768212,\n \"acc_norm_stderr\": 0.03710185726119994\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.7596330275229358,\n \"acc_stderr\": 0.01832060732096407,\n \"\ acc_norm\": 0.7596330275229358,\n \"acc_norm_stderr\": 0.01832060732096407\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.4722222222222222,\n \"acc_stderr\": 0.0340470532865388,\n \"acc_norm\"\ : 0.4722222222222222,\n \"acc_norm_stderr\": 0.0340470532865388\n },\n\ \ \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\": 0.7892156862745098,\n\ \ \"acc_stderr\": 0.028626547912437378,\n \"acc_norm\": 0.7892156862745098,\n\ \ \"acc_norm_stderr\": 0.028626547912437378\n },\n \"harness\|hendrycksTest-high_school_world_history\|5\"\ : {\n \"acc\": 0.7383966244725738,\n \"acc_stderr\": 0.028609516716994934,\n\ \ \"acc_norm\": 0.7383966244725738,\n \"acc_norm_stderr\": 0.028609516716994934\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6367713004484304,\n\ \ \"acc_stderr\": 0.032277904428505,\n \"acc_norm\": 0.6367713004484304,\n\ \ \"acc_norm_stderr\": 0.032277904428505\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.6564885496183206,\n \"acc_stderr\": 0.041649760719448786,\n\ \ \"acc_norm\": 0.6564885496183206,\n \"acc_norm_stderr\": 0.041649760719448786\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7272727272727273,\n \"acc_stderr\": 0.04065578140908705,\n \"\ acc_norm\": 0.7272727272727273,\n \"acc_norm_stderr\": 0.04065578140908705\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.6759259259259259,\n\ \ \"acc_stderr\": 0.045245960070300476,\n \"acc_norm\": 0.6759259259259259,\n\ \ \"acc_norm_stderr\": 0.045245960070300476\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.6748466257668712,\n \"acc_stderr\": 0.036803503712864616,\n\ \ \"acc_norm\": 0.6748466257668712,\n \"acc_norm_stderr\": 0.036803503712864616\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.4375,\n\ \ \"acc_stderr\": 0.04708567521880525,\n \"acc_norm\": 0.4375,\n \ \ \"acc_norm_stderr\": 0.04708567521880525\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\": 0.8376068376068376,\n\ \ \"acc_stderr\": 0.024161618127987745,\n \"acc_norm\": 0.8376068376068376,\n\ \ \"acc_norm_stderr\": 0.024161618127987745\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.64,\n \"acc_stderr\": 0.04824181513244218,\n \ \ \"acc_norm\": 0.64,\n \"acc_norm_stderr\": 0.04824181513244218\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.768837803320562,\n\ \ \"acc_stderr\": 0.015075523238101074,\n \"acc_norm\": 0.768837803320562,\n\ \ \"acc_norm_stderr\": 0.015075523238101074\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6213872832369942,\n \"acc_stderr\": 0.02611374936131034,\n\ \ \"acc_norm\": 0.6213872832369942,\n \"acc_norm_stderr\": 0.02611374936131034\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2569832402234637,\n\ \ \"acc_stderr\": 0.01461446582196633,\n \"acc_norm\": 0.2569832402234637,\n\ \ \"acc_norm_stderr\": 0.01461446582196633\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.6503267973856209,\n \"acc_stderr\": 0.027305308076274695,\n\ \ \"acc_norm\": 0.6503267973856209,\n \"acc_norm_stderr\": 0.027305308076274695\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.662379421221865,\n\ \ \"acc_stderr\": 0.026858825879488544,\n \"acc_norm\": 0.662379421221865,\n\ \ \"acc_norm_stderr\": 0.026858825879488544\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.6388888888888888,\n \"acc_stderr\": 0.026725868809100786,\n\ \ \"acc_norm\": 0.6388888888888888,\n \"acc_norm_stderr\": 0.026725868809100786\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.42907801418439717,\n \"acc_stderr\": 0.029525914302558555,\n \ \ \"acc_norm\": 0.42907801418439717,\n \"acc_norm_stderr\": 0.029525914302558555\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.3924380704041721,\n\ \ \"acc_stderr\": 0.01247124366922911,\n \"acc_norm\": 0.3924380704041721,\n\ \ \"acc_norm_stderr\": 0.01247124366922911\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.5882352941176471,\n \"acc_stderr\": 0.02989616303312547,\n\ \ \"acc_norm\": 0.5882352941176471,\n \"acc_norm_stderr\": 0.02989616303312547\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.5686274509803921,\n \"acc_stderr\": 0.02003639376835263,\n \ \ \"acc_norm\": 0.5686274509803921,\n \"acc_norm_stderr\": 0.02003639376835263\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.5909090909090909,\n\ \ \"acc_stderr\": 0.04709306978661895,\n \"acc_norm\": 0.5909090909090909,\n\ \ \"acc_norm_stderr\": 0.04709306978661895\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.6571428571428571,\n \"acc_stderr\": 0.030387262919547735,\n\ \ \"acc_norm\": 0.6571428571428571,\n \"acc_norm_stderr\": 0.030387262919547735\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8258706467661692,\n\ \ \"acc_stderr\": 0.026814951200421603,\n \"acc_norm\": 0.8258706467661692,\n\ \ \"acc_norm_stderr\": 0.026814951200421603\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.76,\n \"acc_stderr\": 0.042923469599092816,\n \ \ \"acc_norm\": 0.76,\n \"acc_norm_stderr\": 0.042923469599092816\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.4819277108433735,\n\ \ \"acc_stderr\": 0.038899512528272166,\n \"acc_norm\": 0.4819277108433735,\n\ \ \"acc_norm_stderr\": 0.038899512528272166\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8187134502923976,\n \"acc_stderr\": 0.029547741687640038,\n\ \ \"acc_norm\": 0.8187134502923976,\n \"acc_norm_stderr\": 0.029547741687640038\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.3268053855569155,\n\ \ \"mc1_stderr\": 0.01641987473113503,\n \"mc2\": 0.4880155663864428,\n\ \ \"mc2_stderr\": 0.015371746911854285\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7782162588792423,\n \"acc_stderr\": 0.011676109244497813\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.3434420015163002,\n \ \ \"acc_stderr\": 0.013079933811800311\n }\n}\n```" repo_url: https://huggingface.co/NLUHOPOE/test-case-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: 2024_02_16T05_25_06.093843 path: - '/details_harness\|arc:challenge\|25_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-02-16T05-25-06.093843.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|gsm8k\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hellaswag\|10_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-02-16T05-25-06.093843.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-management\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-02-16T05-25-06.093843.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|truthfulqa:mc\|0_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-02-16T05-25-06.093843.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_02_16T05_25_06.093843 path: - '/details_harness\|winogrande\|5_2024-02-16T05-25-06.093843.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-02-16T05-25-06.093843.parquet' - config_name: results data_files: - split: 2024_02_16T05_25_06.093843 path: - results_2024-02-16T05-25-06.093843.parquet - split: latest path: - results_2024-02-16T05-25-06.093843.parquet --- # Dataset Card for Evaluation run of NLUHOPOE/test-case-0 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [NLUHOPOE/test-case-0](https://huggingface.co/NLUHOPOE/test-case-0) 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_NLUHOPOE__test-case-0", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-02-16T05:25:06.093843](https://huggingface.co/datasets/open-llm-leaderboard/details_NLUHOPOE__test-case-0/blob/main/results_2024-02-16T05-25-06.093843.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": 0.5791278236658676, "acc_stderr": 0.033494817808173614, "acc_norm": 0.5837595891503912, "acc_norm_stderr": 0.03419368461778056, "mc1": 0.3268053855569155, "mc1_stderr": 0.01641987473113503, "mc2": 0.4880155663864428, "mc2_stderr": 0.015371746911854285 }, "harness\|arc:challenge\|25": { "acc": 0.5349829351535836, "acc_stderr": 0.01457558392201967, "acc_norm": 0.5750853242320819, "acc_norm_stderr": 0.014445698968520769 }, "harness\|hellaswag\|10": { "acc": 0.5997809201354312, "acc_stderr": 0.004889413126208774, "acc_norm": 0.796355307707628, "acc_norm_stderr": 0.004018847286468061 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.4888888888888889, "acc_stderr": 0.04318275491977976, "acc_norm": 0.4888888888888889, "acc_norm_stderr": 0.04318275491977976 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.5855263157894737, "acc_stderr": 0.04008973785779206, "acc_norm": 0.5855263157894737, "acc_norm_stderr": 0.04008973785779206 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.53, "acc_stderr": 0.050161355804659205, "acc_norm": 0.53, "acc_norm_stderr": 0.050161355804659205 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6490566037735849, "acc_stderr": 0.02937364625323469, "acc_norm": 0.6490566037735849, "acc_norm_stderr": 0.02937364625323469 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.6736111111111112, "acc_stderr": 0.03921067198982266, "acc_norm": 0.6736111111111112, "acc_norm_stderr": 0.03921067198982266 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.45, "acc_stderr": 0.049999999999999996, "acc_norm": 0.45, "acc_norm_stderr": 0.049999999999999996 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.5086705202312138, "acc_stderr": 0.03811890988940412, "acc_norm": 0.5086705202312138, "acc_norm_stderr": 0.03811890988940412 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3137254901960784, "acc_stderr": 0.04617034827006718, "acc_norm": 0.3137254901960784, "acc_norm_stderr": 0.04617034827006718 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.46382978723404256, "acc_stderr": 0.032600385118357715, "acc_norm": 0.46382978723404256, "acc_norm_stderr": 0.032600385118357715 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.39473684210526316, "acc_stderr": 0.045981880578165414, "acc_norm": 0.39473684210526316, "acc_norm_stderr": 0.045981880578165414 }, "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": 0.3783068783068783, "acc_stderr": 0.024976954053155254, "acc_norm": 0.3783068783068783, "acc_norm_stderr": 0.024976954053155254 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.3888888888888889, "acc_stderr": 0.04360314860077459, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.04360314860077459 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7129032258064516, "acc_stderr": 0.025736542745594528, "acc_norm": 0.7129032258064516, "acc_norm_stderr": 0.025736542745594528 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.43842364532019706, "acc_stderr": 0.03491207857486518, "acc_norm": 0.43842364532019706, "acc_norm_stderr": 0.03491207857486518 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.64, "acc_stderr": 0.048241815132442176, "acc_norm": 0.64, "acc_norm_stderr": 0.048241815132442176 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7878787878787878, "acc_stderr": 0.03192271569548301, "acc_norm": 0.7878787878787878, "acc_norm_stderr": 0.03192271569548301 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7272727272727273, "acc_stderr": 0.03173071239071724, "acc_norm": 0.7272727272727273, "acc_norm_stderr": 0.03173071239071724 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8238341968911918, "acc_stderr": 0.027493504244548047, "acc_norm": 0.8238341968911918, "acc_norm_stderr": 0.027493504244548047 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.5923076923076923, "acc_stderr": 0.02491524398598785, "acc_norm": 0.5923076923076923, "acc_norm_stderr": 0.02491524398598785 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.32592592592592595, "acc_stderr": 0.02857834836547308, "acc_norm": 0.32592592592592595, "acc_norm_stderr": 0.02857834836547308 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6554621848739496, "acc_stderr": 0.030868682604121626, "acc_norm": 0.6554621848739496, "acc_norm_stderr": 0.030868682604121626 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.2913907284768212, "acc_stderr": 0.03710185726119994, "acc_norm": 0.2913907284768212, "acc_norm_stderr": 0.03710185726119994 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.7596330275229358, "acc_stderr": 0.01832060732096407, "acc_norm": 0.7596330275229358, "acc_norm_stderr": 0.01832060732096407 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4722222222222222, "acc_stderr": 0.0340470532865388, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.0340470532865388 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7892156862745098, "acc_stderr": 0.028626547912437378, "acc_norm": 0.7892156862745098, "acc_norm_stderr": 0.028626547912437378 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7383966244725738, "acc_stderr": 0.028609516716994934, "acc_norm": 0.7383966244725738, "acc_norm_stderr": 0.028609516716994934 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6367713004484304, "acc_stderr": 0.032277904428505, "acc_norm": 0.6367713004484304, "acc_norm_stderr": 0.032277904428505 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.6564885496183206, "acc_stderr": 0.041649760719448786, "acc_norm": 0.6564885496183206, "acc_norm_stderr": 0.041649760719448786 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7272727272727273, "acc_stderr": 0.04065578140908705, "acc_norm": 0.7272727272727273, "acc_norm_stderr": 0.04065578140908705 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.6759259259259259, "acc_stderr": 0.045245960070300476, "acc_norm": 0.6759259259259259, "acc_norm_stderr": 0.045245960070300476 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.6748466257668712, "acc_stderr": 0.036803503712864616, "acc_norm": 0.6748466257668712, "acc_norm_stderr": 0.036803503712864616 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.4375, "acc_stderr": 0.04708567521880525, "acc_norm": 0.4375, "acc_norm_stderr": 0.04708567521880525 }, "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": 0.8376068376068376, "acc_stderr": 0.024161618127987745, "acc_norm": 0.8376068376068376, "acc_norm_stderr": 0.024161618127987745 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.64, "acc_stderr": 0.04824181513244218, "acc_norm": 0.64, "acc_norm_stderr": 0.04824181513244218 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.768837803320562, "acc_stderr": 0.015075523238101074, "acc_norm": 0.768837803320562, "acc_norm_stderr": 0.015075523238101074 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6213872832369942, "acc_stderr": 0.02611374936131034, "acc_norm": 0.6213872832369942, "acc_norm_stderr": 0.02611374936131034 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.2569832402234637, "acc_stderr": 0.01461446582196633, "acc_norm": 0.2569832402234637, "acc_norm_stderr": 0.01461446582196633 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.6503267973856209, "acc_stderr": 0.027305308076274695, "acc_norm": 0.6503267973856209, "acc_norm_stderr": 0.027305308076274695 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.662379421221865, "acc_stderr": 0.026858825879488544, "acc_norm": 0.662379421221865, "acc_norm_stderr": 0.026858825879488544 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.6388888888888888, "acc_stderr": 0.026725868809100786, "acc_norm": 0.6388888888888888, "acc_norm_stderr": 0.026725868809100786 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.42907801418439717, "acc_stderr": 0.029525914302558555, "acc_norm": 0.42907801418439717, "acc_norm_stderr": 0.029525914302558555 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.3924380704041721, "acc_stderr": 0.01247124366922911, "acc_norm": 0.3924380704041721, "acc_norm_stderr": 0.01247124366922911 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.5882352941176471, "acc_stderr": 0.02989616303312547, "acc_norm": 0.5882352941176471, "acc_norm_stderr": 0.02989616303312547 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.5686274509803921, "acc_stderr": 0.02003639376835263, "acc_norm": 0.5686274509803921, "acc_norm_stderr": 0.02003639376835263 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.5909090909090909, "acc_stderr": 0.04709306978661895, "acc_norm": 0.5909090909090909, "acc_norm_stderr": 0.04709306978661895 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.6571428571428571, "acc_stderr": 0.030387262919547735, "acc_norm": 0.6571428571428571, "acc_norm_stderr": 0.030387262919547735 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8258706467661692, "acc_stderr": 0.026814951200421603, "acc_norm": 0.8258706467661692, "acc_norm_stderr": 0.026814951200421603 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.76, "acc_stderr": 0.042923469599092816, "acc_norm": 0.76, "acc_norm_stderr": 0.042923469599092816 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.4819277108433735, "acc_stderr": 0.038899512528272166, "acc_norm": 0.4819277108433735, "acc_norm_stderr": 0.038899512528272166 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8187134502923976, "acc_stderr": 0.029547741687640038, "acc_norm": 0.8187134502923976, "acc_norm_stderr": 0.029547741687640038 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.3268053855569155, "mc1_stderr": 0.01641987473113503, "mc2": 0.4880155663864428, "mc2_stderr": 0.015371746911854285 }, "harness\|winogrande\|5": { "acc": 0.7782162588792423, "acc_stderr": 0.011676109244497813 }, "harness\|gsm8k\|5": { "acc": 0.3434420015163002, "acc_stderr": 0.013079933811800311 } } ``` ## 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]
biadrivex/yong	--- license: openrail ---
JianhaoDYDY/sample	--- language: - en license: apache-2.0 task_categories: - image-classification configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 2742.0 num_examples: 1 download_size: 20101 dataset_size: 2742.0 ---
yotam56/hugo_tsne_ds	--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': dresses '1': jackets '2': man_hoodie '3': red_tshirts '4': suits '5': white_tshirts '6': women_pants '7': women_shorts '8': women_skirts splits: - name: train num_bytes: 358596.0 num_examples: 45 download_size: 367026 dataset_size: 358596.0 --- # Dataset Card for "hugo_tsne_ds" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
OzoneAsai/calculation	--- license: wtfpl tag: conversational task_categories: - conversational language: - en - zh - de - ru - ko - fr - ja --- # Dataset Card for Calculation ### size JSON file: output1.json≒1.3GB ~ output60.json In total 70 ~ 80GB ### Dataset Summary en: Calculation. Its range will be expanded later. zh: 计算。其范围将在以后扩展。 de: Berechnung. Der Umfang wird später erweitert werden. ru: Расчет. Его диапазон будет расширен позже. ko: 계산. 범위는 나중에 확장될 것입니다. fr: Calcul. Sa portée sera étendue ultérieurement. ja: 計算。範囲は後で拡張されます。 ### Supported Tasks and Leaderboards en: conversation, instruction zh: 会话，指令 de: Unterhaltung, Anweisung ru: разговор, инструкция ko: 대화, 지시사항 fr: conversation, instruction ja: 会話、指示 ### Languages en: It only used numbers and symbols. So any language is able to use this. zh: 该数据集只使用数字和符号。因此任何语言都可以使用它。 de: Es werden nur Zahlen und Symbole verwendet. Daher kann diese Datenbank von jeder Sprache verwendet werden. ru: В нем используются только цифры и символы. Таким образом, любой язык может использовать его. ko: 숫자와 기호만 사용되었습니다. 그래서 모든 언어에서 사용할 수 있습니다. fr: Il n'utilise que des chiffres et des symboles. Ainsi, n'importe quelle langue peut l'utiliser. ja: 数字と記号のみが使用されています。したがって、どんな言語でも使用できます. ## Dataset Structure Input, output, ## Translation Translated by ChatGPT
jhuang14/Labeled_Data	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': airplane '1': bustruck '2': other '3': rail splits: - name: train num_bytes: 1652124.1515151516 num_examples: 92 - name: test num_bytes: 718314.8484848485 num_examples: 40 download_size: 2372957 dataset_size: 2370439.0 --- # Dataset Card for "Labeled_Data" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CyberHarem/scarlet_nikke	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of scarlet/紅蓮/红莲/홍련 (Nikke: Goddess of Victory) This is the dataset of scarlet/紅蓮/红莲/홍련 (Nikke: Goddess of Victory), containing 85 images and their tags. The core tags of this character are `long_hair, breasts, bangs, large_breasts, red_eyes, white_hair, grey_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 \| 85 \| 193.97 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/scarlet_nikke/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 85 \| 83.78 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/scarlet_nikke/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 220 \| 186.62 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/scarlet_nikke/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 85 \| 157.31 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/scarlet_nikke/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 220 \| 310.00 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/scarlet_nikke/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/scarlet_nikke', 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 \| 8 \| ![](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, holding_sword, black_bodysuit, looking_at_viewer, smile \| \| 1 \| 6 \| ![](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) \| 1boy, 1girl, blush, hetero, solo_focus, penis, looking_at_viewer, mosaic_censoring, nipples, open_mouth, sex, sweat, collarbone, completely_nude, cowgirl_position, girl_on_top, hair_between_eyes, hairband, pussy, thighs, vaginal \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| solo \| holding_sword \| black_bodysuit \| looking_at_viewer \| smile \| 1boy \| blush \| hetero \| solo_focus \| penis \| mosaic_censoring \| nipples \| open_mouth \| sex \| sweat \| collarbone \| completely_nude \| cowgirl_position \| girl_on_top \| hair_between_eyes \| hairband \| pussy \| thighs \| vaginal \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:-------\|:----------------\|:-----------------\|:--------------------\|:--------\|:-------\|:--------\|:---------\|:-------------\|:--------\|:-------------------\|:----------\|:-------------\|:------\|:--------\|:-------------\|:------------------\|:-------------------\|:--------------\|:--------------------\|:-----------\|:--------\|:---------\|:----------\| \| 0 \| 8 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 6 \| ![](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 \|
kortukov/answer-equivalence-dataset	--- license: apache-2.0 task_categories: - text-classification size_categories: - 1K<n<10K configs: - config_name: default data_files: - split: train path: "train.jsonl.zip" - split: test path: "ae_test.jsonl.zip" - split: dev path: "ae_dev.jsonl.zip" - split: dev_bidaf path: "dev_bidaf.jsonl.zip" - split: dev_xlnet path: "dev_xlnet.jsonl.zip" - split: dev_luke path: "dev_luke.jsonl.zip" --- # Answer Equivalence Dataset This dataset is introduced and described in [Tomayto, Tomahto. Beyond Token-level Answer Equivalence for Question Answering Evaluation](http://arxiv.org/abs/2202.07654). ## Source This is a repost. The original dataset repository [can be found here.](https://github.com/google-research-datasets/answer-equivalence-dataset/tree/main) ## Data splits and sizes \| AE Split \| # AE Examples \| # Ratings \| \|-----------\|---------------\|-----------\| \| Train \| 9,090 \| 9,090 \| \| Dev \| 2,734 \| 4,446 \| \| Test \| 5,831 \| 9,724 \| \| Total \| 17,655 \| 23,260 \| \| Split by system \| # AE Examples \| # Ratings \| \|------------------\|---------------\|-----------\| \| BiDAF dev predictions \| 5622 \| 7522 \| \| XLNet dev predictions \| 2448 \| 7932 \| \| Luke dev predictions \| 2240 \| 4590 \| \| Total \| 8,565 \| 14,170 \| ## BERT Matching (BEM) model The BEM model from the paper, finetuned on this dataset, is available on [tfhub](https://tfhub.dev/google/answer_equivalence/bem/1). This [colab](https://colab.research.google.com/github/google-research-datasets/answer-equivalence-dataset/blob/main/Answer_Equivalence_BEM_example.ipynb) demonstrates how to use it. ## How to cite AE? ``` @article{bulian-etal-2022-tomayto, author = {Jannis Bulian and Christian Buck and Wojciech Gajewski and Benjamin B{\"o}rschinger and Tal Schuster}, title = {Tomayto, Tomahto. Beyond Token-level Answer Equivalence for Question Answering Evaluation}, journal = {CoRR}, volume = {abs/2202.07654}, year = {2022}, ee = {http://arxiv.org/abs/2202.07654}, } ``` ## Disclaimer This is not an official Google product. ## Contact information For help or issues, please submit [a GitHub issue to this repostory](https://github.com/google-research-datasets/answer-equivalence-dataset/tree/main) or contact the authors by email.
autoevaluate/autoeval-staging-eval-project-sasha__dog-food-8a6c4abe-13775898	--- type: predictions tags: - autotrain - evaluation datasets: - sasha/dog-food eval_info: task: image_binary_classification model: sasha/dog-food-swin-tiny-patch4-window7-224 metrics: ['matthews_correlation'] dataset_name: sasha/dog-food dataset_config: sasha--dog-food dataset_split: train col_mapping: image: image target: label --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Binary Image Classification * Model: sasha/dog-food-swin-tiny-patch4-window7-224 * Dataset: sasha/dog-food * Config: sasha--dog-food * Split: train To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@ahmetgunduz](https://huggingface.co/ahmetgunduz) for evaluating this model.
minh21/COVID-QA-testset-biencoder-data-45_45_10	--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: context_chunks sequence: string - name: document_id dtype: int64 - name: id dtype: int64 - name: context dtype: string splits: - name: train num_bytes: 16708455 num_examples: 201 download_size: 442083 dataset_size: 16708455 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "COVID-QA-testset-biencoder-data-45_45_10" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
yoonlee/abnormal_cat	--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 6845620.0 num_examples: 9 download_size: 6847520 dataset_size: 6845620.0 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "abnormal_cat" [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-109000	--- 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: 1049320 dataset_size: 13336000 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_abhishekchohan__mistral-7B-forest-merge	--- pretty_name: Evaluation run of abhishekchohan/mistral-7B-forest-merge dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [abhishekchohan/mistral-7B-forest-merge](https://huggingface.co/abhishekchohan/mistral-7B-forest-merge)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_abhishekchohan__mistral-7B-forest-merge\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-21T23:23:15.649063](https://huggingface.co/datasets/open-llm-leaderboard/details_abhishekchohan__mistral-7B-forest-merge/blob/main/results_2024-01-21T23-23-15.649063.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\": 0.6022067316089463,\n\ \ \"acc_stderr\": 0.032877722301518426,\n \"acc_norm\": 0.6045609403878123,\n\ \ \"acc_norm_stderr\": 0.03353760382711908,\n \"mc1\": 0.41615667074663404,\n\ \ \"mc1_stderr\": 0.017255657502903043,\n \"mc2\": 0.5748469157653282,\n\ \ \"mc2_stderr\": 0.015758784357589765\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6049488054607508,\n \"acc_stderr\": 0.014285898292938167,\n\ \ \"acc_norm\": 0.636518771331058,\n \"acc_norm_stderr\": 0.014056207319068285\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6519617606054571,\n\ \ \"acc_stderr\": 0.004753746951620151,\n \"acc_norm\": 0.8440549691296555,\n\ \ \"acc_norm_stderr\": 0.0036206175507473956\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.562962962962963,\n\ \ \"acc_stderr\": 0.04284958639753401,\n \"acc_norm\": 0.562962962962963,\n\ \ \"acc_norm_stderr\": 0.04284958639753401\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6578947368421053,\n \"acc_stderr\": 0.03860731599316092,\n\ \ \"acc_norm\": 0.6578947368421053,\n \"acc_norm_stderr\": 0.03860731599316092\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.61,\n\ \ \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.61,\n \ \ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.6679245283018868,\n \"acc_stderr\": 0.02898545565233439,\n\ \ \"acc_norm\": 0.6679245283018868,\n \"acc_norm_stderr\": 0.02898545565233439\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.6597222222222222,\n\ \ \"acc_stderr\": 0.039621355734862175,\n \"acc_norm\": 0.6597222222222222,\n\ \ \"acc_norm_stderr\": 0.039621355734862175\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.41,\n \"acc_stderr\": 0.049431107042371025,\n \ \ \"acc_norm\": 0.41,\n \"acc_norm_stderr\": 0.049431107042371025\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \"acc_norm\"\ : 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.5953757225433526,\n\ \ \"acc_stderr\": 0.03742461193887248,\n \"acc_norm\": 0.5953757225433526,\n\ \ \"acc_norm_stderr\": 0.03742461193887248\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.3431372549019608,\n \"acc_stderr\": 0.04724007352383888,\n\ \ \"acc_norm\": 0.3431372549019608,\n \"acc_norm_stderr\": 0.04724007352383888\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.79,\n \"acc_stderr\": 0.04093601807403326,\n \"acc_norm\": 0.79,\n\ \ \"acc_norm_stderr\": 0.04093601807403326\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5148936170212766,\n \"acc_stderr\": 0.03267151848924777,\n\ \ \"acc_norm\": 0.5148936170212766,\n \"acc_norm_stderr\": 0.03267151848924777\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.38596491228070173,\n\ \ \"acc_stderr\": 0.04579639422070434,\n \"acc_norm\": 0.38596491228070173,\n\ \ \"acc_norm_stderr\": 0.04579639422070434\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5241379310344828,\n \"acc_stderr\": 0.0416180850350153,\n\ \ \"acc_norm\": 0.5241379310344828,\n \"acc_norm_stderr\": 0.0416180850350153\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.4074074074074074,\n \"acc_stderr\": 0.025305906241590632,\n \"\ acc_norm\": 0.4074074074074074,\n \"acc_norm_stderr\": 0.025305906241590632\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.42063492063492064,\n\ \ \"acc_stderr\": 0.04415438226743744,\n \"acc_norm\": 0.42063492063492064,\n\ \ \"acc_norm_stderr\": 0.04415438226743744\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7161290322580646,\n\ \ \"acc_stderr\": 0.02564938106302927,\n \"acc_norm\": 0.7161290322580646,\n\ \ \"acc_norm_stderr\": 0.02564938106302927\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.4187192118226601,\n \"acc_stderr\": 0.034711928605184676,\n\ \ \"acc_norm\": 0.4187192118226601,\n \"acc_norm_stderr\": 0.034711928605184676\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.67,\n \"acc_stderr\": 0.047258156262526094,\n \"acc_norm\"\ : 0.67,\n \"acc_norm_stderr\": 0.047258156262526094\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7333333333333333,\n \"acc_stderr\": 0.03453131801885417,\n\ \ \"acc_norm\": 0.7333333333333333,\n \"acc_norm_stderr\": 0.03453131801885417\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7323232323232324,\n \"acc_stderr\": 0.03154449888270285,\n \"\ acc_norm\": 0.7323232323232324,\n \"acc_norm_stderr\": 0.03154449888270285\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8134715025906736,\n \"acc_stderr\": 0.028112091210117467,\n\ \ \"acc_norm\": 0.8134715025906736,\n \"acc_norm_stderr\": 0.028112091210117467\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.5512820512820513,\n \"acc_stderr\": 0.025217315184846486,\n\ \ \"acc_norm\": 0.5512820512820513,\n \"acc_norm_stderr\": 0.025217315184846486\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.29259259259259257,\n \"acc_stderr\": 0.027738969632176088,\n \ \ \"acc_norm\": 0.29259259259259257,\n \"acc_norm_stderr\": 0.027738969632176088\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.5672268907563025,\n \"acc_stderr\": 0.032183581077426124,\n\ \ \"acc_norm\": 0.5672268907563025,\n \"acc_norm_stderr\": 0.032183581077426124\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.3443708609271523,\n \"acc_stderr\": 0.038796870240733264,\n \"\ acc_norm\": 0.3443708609271523,\n \"acc_norm_stderr\": 0.038796870240733264\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.7871559633027523,\n \"acc_stderr\": 0.017549376389313694,\n \"\ acc_norm\": 0.7871559633027523,\n \"acc_norm_stderr\": 0.017549376389313694\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.4305555555555556,\n \"acc_stderr\": 0.03376922151252336,\n \"\ acc_norm\": 0.4305555555555556,\n \"acc_norm_stderr\": 0.03376922151252336\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.7941176470588235,\n \"acc_stderr\": 0.028379449451588667,\n \"\ acc_norm\": 0.7941176470588235,\n \"acc_norm_stderr\": 0.028379449451588667\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7932489451476793,\n \"acc_stderr\": 0.0263616516683891,\n \ \ \"acc_norm\": 0.7932489451476793,\n \"acc_norm_stderr\": 0.0263616516683891\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6681614349775785,\n\ \ \"acc_stderr\": 0.03160295143776679,\n \"acc_norm\": 0.6681614349775785,\n\ \ \"acc_norm_stderr\": 0.03160295143776679\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7404580152671756,\n \"acc_stderr\": 0.03844876139785271,\n\ \ \"acc_norm\": 0.7404580152671756,\n \"acc_norm_stderr\": 0.03844876139785271\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.7933884297520661,\n \"acc_stderr\": 0.03695980128098822,\n \"\ acc_norm\": 0.7933884297520661,\n \"acc_norm_stderr\": 0.03695980128098822\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.8055555555555556,\n\ \ \"acc_stderr\": 0.038260763248848646,\n \"acc_norm\": 0.8055555555555556,\n\ \ \"acc_norm_stderr\": 0.038260763248848646\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.6809815950920245,\n \"acc_stderr\": 0.03661997551073836,\n\ \ \"acc_norm\": 0.6809815950920245,\n \"acc_norm_stderr\": 0.03661997551073836\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.41964285714285715,\n\ \ \"acc_stderr\": 0.04684099321077106,\n \"acc_norm\": 0.41964285714285715,\n\ \ \"acc_norm_stderr\": 0.04684099321077106\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7766990291262136,\n \"acc_stderr\": 0.04123553189891431,\n\ \ \"acc_norm\": 0.7766990291262136,\n \"acc_norm_stderr\": 0.04123553189891431\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8589743589743589,\n\ \ \"acc_stderr\": 0.02280138253459754,\n \"acc_norm\": 0.8589743589743589,\n\ \ \"acc_norm_stderr\": 0.02280138253459754\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.65,\n \"acc_stderr\": 0.047937248544110196,\n \ \ \"acc_norm\": 0.65,\n \"acc_norm_stderr\": 0.047937248544110196\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.7816091954022989,\n\ \ \"acc_stderr\": 0.014774358319934499,\n \"acc_norm\": 0.7816091954022989,\n\ \ \"acc_norm_stderr\": 0.014774358319934499\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.6560693641618497,\n \"acc_stderr\": 0.02557412378654667,\n\ \ \"acc_norm\": 0.6560693641618497,\n \"acc_norm_stderr\": 0.02557412378654667\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.3664804469273743,\n\ \ \"acc_stderr\": 0.01611523550486548,\n \"acc_norm\": 0.3664804469273743,\n\ \ \"acc_norm_stderr\": 0.01611523550486548\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.6470588235294118,\n \"acc_stderr\": 0.027363593284684972,\n\ \ \"acc_norm\": 0.6470588235294118,\n \"acc_norm_stderr\": 0.027363593284684972\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6913183279742765,\n\ \ \"acc_stderr\": 0.026236965881153273,\n \"acc_norm\": 0.6913183279742765,\n\ \ \"acc_norm_stderr\": 0.026236965881153273\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.6759259259259259,\n \"acc_stderr\": 0.02604176620271716,\n\ \ \"acc_norm\": 0.6759259259259259,\n \"acc_norm_stderr\": 0.02604176620271716\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.425531914893617,\n \"acc_stderr\": 0.029494827600144366,\n \ \ \"acc_norm\": 0.425531914893617,\n \"acc_norm_stderr\": 0.029494827600144366\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4426336375488918,\n\ \ \"acc_stderr\": 0.01268590653820624,\n \"acc_norm\": 0.4426336375488918,\n\ \ \"acc_norm_stderr\": 0.01268590653820624\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6139705882352942,\n \"acc_stderr\": 0.029573269134411124,\n\ \ \"acc_norm\": 0.6139705882352942,\n \"acc_norm_stderr\": 0.029573269134411124\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6078431372549019,\n \"acc_stderr\": 0.019751726508762637,\n \ \ \"acc_norm\": 0.6078431372549019,\n \"acc_norm_stderr\": 0.019751726508762637\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6636363636363637,\n\ \ \"acc_stderr\": 0.04525393596302506,\n \"acc_norm\": 0.6636363636363637,\n\ \ \"acc_norm_stderr\": 0.04525393596302506\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.673469387755102,\n \"acc_stderr\": 0.030021056238440307,\n\ \ \"acc_norm\": 0.673469387755102,\n \"acc_norm_stderr\": 0.030021056238440307\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.7661691542288557,\n\ \ \"acc_stderr\": 0.029929415408348384,\n \"acc_norm\": 0.7661691542288557,\n\ \ \"acc_norm_stderr\": 0.029929415408348384\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.86,\n \"acc_stderr\": 0.034873508801977704,\n \ \ \"acc_norm\": 0.86,\n \"acc_norm_stderr\": 0.034873508801977704\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.4879518072289157,\n\ \ \"acc_stderr\": 0.03891364495835821,\n \"acc_norm\": 0.4879518072289157,\n\ \ \"acc_norm_stderr\": 0.03891364495835821\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8304093567251462,\n \"acc_stderr\": 0.02878210810540171,\n\ \ \"acc_norm\": 0.8304093567251462,\n \"acc_norm_stderr\": 0.02878210810540171\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.41615667074663404,\n\ \ \"mc1_stderr\": 0.017255657502903043,\n \"mc2\": 0.5748469157653282,\n\ \ \"mc2_stderr\": 0.015758784357589765\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7774269928966061,\n \"acc_stderr\": 0.011690933809712664\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.511751326762699,\n \ \ \"acc_stderr\": 0.013768680408142806\n }\n}\n```" repo_url: https://huggingface.co/abhishekchohan/mistral-7B-forest-merge 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_21T23_19_15.004437 path: - '/details_harness\|arc:challenge\|25_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|arc:challenge\|25_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-01-21T23-23-15.649063.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|gsm8k\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|gsm8k\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hellaswag\|10_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hellaswag\|10_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-21T23-19-15.004437.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-21T23-23-15.649063.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-management\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-management\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-21T23-23-15.649063.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|truthfulqa:mc\|0_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|truthfulqa:mc\|0_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-01-21T23-23-15.649063.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_21T23_19_15.004437 path: - '/details_harness\|winogrande\|5_2024-01-21T23-19-15.004437.parquet' - split: 2024_01_21T23_23_15.649063 path: - '/details_harness\|winogrande\|5_2024-01-21T23-23-15.649063.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-01-21T23-23-15.649063.parquet' - config_name: results data_files: - split: 2024_01_21T23_19_15.004437 path: - results_2024-01-21T23-19-15.004437.parquet - split: 2024_01_21T23_23_15.649063 path: - results_2024-01-21T23-23-15.649063.parquet - split: latest path: - results_2024-01-21T23-23-15.649063.parquet --- # Dataset Card for Evaluation run of abhishekchohan/mistral-7B-forest-merge <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [abhishekchohan/mistral-7B-forest-merge](https://huggingface.co/abhishekchohan/mistral-7B-forest-merge) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_abhishekchohan__mistral-7B-forest-merge", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-21T23:23:15.649063](https://huggingface.co/datasets/open-llm-leaderboard/details_abhishekchohan__mistral-7B-forest-merge/blob/main/results_2024-01-21T23-23-15.649063.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": 0.6022067316089463, "acc_stderr": 0.032877722301518426, "acc_norm": 0.6045609403878123, "acc_norm_stderr": 0.03353760382711908, "mc1": 0.41615667074663404, "mc1_stderr": 0.017255657502903043, "mc2": 0.5748469157653282, "mc2_stderr": 0.015758784357589765 }, "harness\|arc:challenge\|25": { "acc": 0.6049488054607508, "acc_stderr": 0.014285898292938167, "acc_norm": 0.636518771331058, "acc_norm_stderr": 0.014056207319068285 }, "harness\|hellaswag\|10": { "acc": 0.6519617606054571, "acc_stderr": 0.004753746951620151, "acc_norm": 0.8440549691296555, "acc_norm_stderr": 0.0036206175507473956 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.562962962962963, "acc_stderr": 0.04284958639753401, "acc_norm": 0.562962962962963, "acc_norm_stderr": 0.04284958639753401 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6578947368421053, "acc_stderr": 0.03860731599316092, "acc_norm": 0.6578947368421053, "acc_norm_stderr": 0.03860731599316092 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.6679245283018868, "acc_stderr": 0.02898545565233439, "acc_norm": 0.6679245283018868, "acc_norm_stderr": 0.02898545565233439 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.6597222222222222, "acc_stderr": 0.039621355734862175, "acc_norm": 0.6597222222222222, "acc_norm_stderr": 0.039621355734862175 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.5953757225433526, "acc_stderr": 0.03742461193887248, "acc_norm": 0.5953757225433526, "acc_norm_stderr": 0.03742461193887248 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3431372549019608, "acc_stderr": 0.04724007352383888, "acc_norm": 0.3431372549019608, "acc_norm_stderr": 0.04724007352383888 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.79, "acc_stderr": 0.04093601807403326, "acc_norm": 0.79, "acc_norm_stderr": 0.04093601807403326 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5148936170212766, "acc_stderr": 0.03267151848924777, "acc_norm": 0.5148936170212766, "acc_norm_stderr": 0.03267151848924777 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.38596491228070173, "acc_stderr": 0.04579639422070434, "acc_norm": 0.38596491228070173, "acc_norm_stderr": 0.04579639422070434 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5241379310344828, "acc_stderr": 0.0416180850350153, "acc_norm": 0.5241379310344828, "acc_norm_stderr": 0.0416180850350153 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.4074074074074074, "acc_stderr": 0.025305906241590632, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.025305906241590632 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.42063492063492064, "acc_stderr": 0.04415438226743744, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.04415438226743744 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7161290322580646, "acc_stderr": 0.02564938106302927, "acc_norm": 0.7161290322580646, "acc_norm_stderr": 0.02564938106302927 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.4187192118226601, "acc_stderr": 0.034711928605184676, "acc_norm": 0.4187192118226601, "acc_norm_stderr": 0.034711928605184676 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.67, "acc_stderr": 0.047258156262526094, "acc_norm": 0.67, "acc_norm_stderr": 0.047258156262526094 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7333333333333333, "acc_stderr": 0.03453131801885417, "acc_norm": 0.7333333333333333, "acc_norm_stderr": 0.03453131801885417 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7323232323232324, "acc_stderr": 0.03154449888270285, "acc_norm": 0.7323232323232324, "acc_norm_stderr": 0.03154449888270285 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8134715025906736, "acc_stderr": 0.028112091210117467, "acc_norm": 0.8134715025906736, "acc_norm_stderr": 0.028112091210117467 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.5512820512820513, "acc_stderr": 0.025217315184846486, "acc_norm": 0.5512820512820513, "acc_norm_stderr": 0.025217315184846486 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.29259259259259257, "acc_stderr": 0.027738969632176088, "acc_norm": 0.29259259259259257, "acc_norm_stderr": 0.027738969632176088 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.5672268907563025, "acc_stderr": 0.032183581077426124, "acc_norm": 0.5672268907563025, "acc_norm_stderr": 0.032183581077426124 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.3443708609271523, "acc_stderr": 0.038796870240733264, "acc_norm": 0.3443708609271523, "acc_norm_stderr": 0.038796870240733264 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.7871559633027523, "acc_stderr": 0.017549376389313694, "acc_norm": 0.7871559633027523, "acc_norm_stderr": 0.017549376389313694 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4305555555555556, "acc_stderr": 0.03376922151252336, "acc_norm": 0.4305555555555556, "acc_norm_stderr": 0.03376922151252336 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7941176470588235, "acc_stderr": 0.028379449451588667, "acc_norm": 0.7941176470588235, "acc_norm_stderr": 0.028379449451588667 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7932489451476793, "acc_stderr": 0.0263616516683891, "acc_norm": 0.7932489451476793, "acc_norm_stderr": 0.0263616516683891 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6681614349775785, "acc_stderr": 0.03160295143776679, "acc_norm": 0.6681614349775785, "acc_norm_stderr": 0.03160295143776679 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7404580152671756, "acc_stderr": 0.03844876139785271, "acc_norm": 0.7404580152671756, "acc_norm_stderr": 0.03844876139785271 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.7933884297520661, "acc_stderr": 0.03695980128098822, "acc_norm": 0.7933884297520661, "acc_norm_stderr": 0.03695980128098822 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.8055555555555556, "acc_stderr": 0.038260763248848646, "acc_norm": 0.8055555555555556, "acc_norm_stderr": 0.038260763248848646 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.6809815950920245, "acc_stderr": 0.03661997551073836, "acc_norm": 0.6809815950920245, "acc_norm_stderr": 0.03661997551073836 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.41964285714285715, "acc_stderr": 0.04684099321077106, "acc_norm": 0.41964285714285715, "acc_norm_stderr": 0.04684099321077106 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7766990291262136, "acc_stderr": 0.04123553189891431, "acc_norm": 0.7766990291262136, "acc_norm_stderr": 0.04123553189891431 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8589743589743589, "acc_stderr": 0.02280138253459754, "acc_norm": 0.8589743589743589, "acc_norm_stderr": 0.02280138253459754 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.7816091954022989, "acc_stderr": 0.014774358319934499, "acc_norm": 0.7816091954022989, "acc_norm_stderr": 0.014774358319934499 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.6560693641618497, "acc_stderr": 0.02557412378654667, "acc_norm": 0.6560693641618497, "acc_norm_stderr": 0.02557412378654667 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.3664804469273743, "acc_stderr": 0.01611523550486548, "acc_norm": 0.3664804469273743, "acc_norm_stderr": 0.01611523550486548 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.6470588235294118, "acc_stderr": 0.027363593284684972, "acc_norm": 0.6470588235294118, "acc_norm_stderr": 0.027363593284684972 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6913183279742765, "acc_stderr": 0.026236965881153273, "acc_norm": 0.6913183279742765, "acc_norm_stderr": 0.026236965881153273 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.6759259259259259, "acc_stderr": 0.02604176620271716, "acc_norm": 0.6759259259259259, "acc_norm_stderr": 0.02604176620271716 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.425531914893617, "acc_stderr": 0.029494827600144366, "acc_norm": 0.425531914893617, "acc_norm_stderr": 0.029494827600144366 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4426336375488918, "acc_stderr": 0.01268590653820624, "acc_norm": 0.4426336375488918, "acc_norm_stderr": 0.01268590653820624 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6139705882352942, "acc_stderr": 0.029573269134411124, "acc_norm": 0.6139705882352942, "acc_norm_stderr": 0.029573269134411124 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6078431372549019, "acc_stderr": 0.019751726508762637, "acc_norm": 0.6078431372549019, "acc_norm_stderr": 0.019751726508762637 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6636363636363637, "acc_stderr": 0.04525393596302506, "acc_norm": 0.6636363636363637, "acc_norm_stderr": 0.04525393596302506 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.673469387755102, "acc_stderr": 0.030021056238440307, "acc_norm": 0.673469387755102, "acc_norm_stderr": 0.030021056238440307 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.7661691542288557, "acc_stderr": 0.029929415408348384, "acc_norm": 0.7661691542288557, "acc_norm_stderr": 0.029929415408348384 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.86, "acc_stderr": 0.034873508801977704, "acc_norm": 0.86, "acc_norm_stderr": 0.034873508801977704 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.4879518072289157, "acc_stderr": 0.03891364495835821, "acc_norm": 0.4879518072289157, "acc_norm_stderr": 0.03891364495835821 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8304093567251462, "acc_stderr": 0.02878210810540171, "acc_norm": 0.8304093567251462, "acc_norm_stderr": 0.02878210810540171 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.41615667074663404, "mc1_stderr": 0.017255657502903043, "mc2": 0.5748469157653282, "mc2_stderr": 0.015758784357589765 }, "harness\|winogrande\|5": { "acc": 0.7774269928966061, "acc_stderr": 0.011690933809712664 }, "harness\|gsm8k\|5": { "acc": 0.511751326762699, "acc_stderr": 0.013768680408142806 } } ``` ## 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 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CATIE-AQ/xwinograd_fr_prompt_coreference	--- language: - fr license: - cc-by-4.0 size_categories: - n<1K tags: - coreference - DFP - french prompts annotations_creators: - found language_creators: - found multilinguality: - monolingual source_datasets: - xwinograd --- # xwinograd_fr_prompt_coreference ## Summary xwinograd_fr_prompt_coreference is a subset of the [Dataset of French Prompts (DFP)](https://huggingface.co/datasets/CATIE-AQ/DFP). It contains 830 rows that can be used for a coreference task. The original data (without prompts) comes from the dataset [xwinograd](https://huggingface.co/datasets/Muennighoff/xwinograd) by Muennighoff where only the French part has been kept. A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the [xP3](https://huggingface.co/datasets/bigscience/xP3) dataset by Muennighoff et al. ## Prompts used ### List 10 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement. ``` '"'+sentence+'"\nRemplacer le "_" dans la phrase ci-dessus par la bonne option :\n- "'+option1+'"\n- "'+option2+'"', '"'+sentence+'"\nRemplace le "_" dans la phrase ci-dessus par la bonne option :\n- "'+option1+'"\n- "'+option2+'"', '"'+sentence+'"\nRemplacez le "_" dans la phrase ci-dessus par la bonne option :\n- "'+option1+'"\n- "'+option2+'"', '"'+sentence+'" Dans la phrase précédente, "_" fait-il référence à "'+option1+'" ou "'+option2+'" ?', '"'+sentence+'" À quoi le "_" dans la phrase ci-dessus fait-il référence ? "'+option1+'" ou "'+option2+'" ?', '"'+sentence+'" Le "_" dans la phrase ci-dessous fait référence à "'+option1+'"\n- "'+option2+'" ?', 'Remplisser le "_" de la phrase suivante : "'+sentence+ '"\nChoix :\n- "'+option1+'"\n- "'+option2+'"\nRéponse :', 'Remplis le "_" de la phrase suivante : "'+sentence+ '"\nChoix :\n- "'+option1+'"\n- "'+option2+'"\nRéponse :', 'Remplissez le "_" de la phrase suivante : "'+sentence+ '"\nChoix :\n- "'+option1+'"\n- "'+option2+'"\nRéponse :', 'Dans la phrase ci-dessous, le "_" renvoie-t-il à "'+option1+'" ou "'+option2+'" ? : '+sentence, ``` ### Features used in the prompts In the prompt list above, `option1`, `option2`, `sentence` and `targets` have been constructed from: ``` xwinograd = load_dataset('Muennighoff/xwinograd','fr') sentence = xwinograd['test'][i]['sentence'] option1 = xwinograd['test'][i]['option1'] option2 = xwinograd['test'][i]['option2'] targets = str(xwinograd['test'][i]['answer']).replace("1",xwinograd['test'][i]['option1']).replace("2",xwinograd['test'][i]['option2']) ``` # Splits - `train` with 830 samples - no `valid` split - no `test` split # How to use? ``` from datasets import load_dataset dataset = load_dataset("CATIE-AQ/xwinograd_fr_prompt_coreference") ``` # Citation ## Original data > @misc{muennighoff2022crosslingual, title={Crosslingual Generalization through Multitask Finetuning}, author={Niklas Muennighoff and Thomas Wang and Lintang Sutawika and Adam Roberts and Stella Biderman and Teven Le Scao and M Saiful Bari and Sheng Shen and Zheng-Xin Yong and Hailey Schoelkopf and Xiangru Tang and Dragomir Radev and Alham Fikri Aji and Khalid Almubarak and Samuel Albanie and Zaid Alyafeai and Albert Webson and Edward Raff and Colin Raffel}, year={2022}, eprint={2211.01786}, archivePrefix={arXiv}, primaryClass={cs.CL} } > @misc{tikhonov2021heads, title={It's All in the Heads: Using Attention Heads as a Baseline for Cross-Lingual Transfer in Commonsense Reasoning}, author={Alexey Tikhonov and Max Ryabinin}, year={2021}, eprint={2106.12066}, archivePrefix={arXiv}, primaryClass={cs.CL} } ## This Dataset > @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023, author = { {Centre Aquitain des Technologies de l'Information et Electroniques} }, title = { DFP (Revision 1d24c09) }, year = 2023, url = { https://huggingface.co/datasets/CATIE-AQ/DFP }, doi = { 10.57967/hf/1200 }, publisher = { Hugging Face } } ## License [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/deed.en)
distilled-one-sec-cv12-each-chunk-uniq/chunk_248	--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 925956496.0 num_examples: 180428 download_size: 946237901 dataset_size: 925956496.0 --- # Dataset Card for "chunk_248" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
liuyanchen1015/MULTI_VALUE_qqp_participle_past_tense	--- dataset_info: features: - name: question1 dtype: string - name: question2 dtype: string - name: label dtype: int64 - name: idx dtype: int64 - name: value_score dtype: int64 splits: - name: dev num_bytes: 126913 num_examples: 609 - name: test num_bytes: 1380942 num_examples: 6474 - name: train num_bytes: 1258173 num_examples: 5783 download_size: 1709920 dataset_size: 2766028 --- # Dataset Card for "MULTI_VALUE_qqp_participle_past_tense" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
causal-lm/instinwild	--- language: en dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 35761516 num_examples: 46971 - name: validation num_bytes: 4012755 num_examples: 5220 download_size: 22678351 dataset_size: 39774271 --- # Dataset Card for "instinwild" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_Weyaxi__Bagel-Hermes-34B-Slerp	--- pretty_name: Evaluation run of Weyaxi/Bagel-Hermes-34B-Slerp dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [Weyaxi/Bagel-Hermes-34B-Slerp](https://huggingface.co/Weyaxi/Bagel-Hermes-34B-Slerp)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Weyaxi__Bagel-Hermes-34B-Slerp\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-01-14T01:56:18.562449](https://huggingface.co/datasets/open-llm-leaderboard/details_Weyaxi__Bagel-Hermes-34B-Slerp/blob/main/results_2024-01-14T01-56-18.562449.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\": 0.7687638749469244,\n\ \ \"acc_stderr\": 0.02791668972955577,\n \"acc_norm\": 0.7731851983230489,\n\ \ \"acc_norm_stderr\": 0.028441222412067358,\n \"mc1\": 0.4969400244798042,\n\ \ \"mc1_stderr\": 0.01750317326096062,\n \"mc2\": 0.6709148255495884,\n\ \ \"mc2_stderr\": 0.014645409374455808\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6706484641638225,\n \"acc_stderr\": 0.013734057652635474,\n\ \ \"acc_norm\": 0.7073378839590444,\n \"acc_norm_stderr\": 0.013295916103619422\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6638119896434973,\n\ \ \"acc_stderr\": 0.004714386376337134,\n \"acc_norm\": 0.8568014339772954,\n\ \ \"acc_norm_stderr\": 0.0034955936625207526\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956912,\n \ \ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956912\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.7407407407407407,\n\ \ \"acc_stderr\": 0.03785714465066653,\n \"acc_norm\": 0.7407407407407407,\n\ \ \"acc_norm_stderr\": 0.03785714465066653\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.881578947368421,\n \"acc_stderr\": 0.02629399585547494,\n\ \ \"acc_norm\": 0.881578947368421,\n \"acc_norm_stderr\": 0.02629399585547494\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.8,\n\ \ \"acc_stderr\": 0.04020151261036844,\n \"acc_norm\": 0.8,\n \ \ \"acc_norm_stderr\": 0.04020151261036844\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.8188679245283019,\n \"acc_stderr\": 0.023702963526757798,\n\ \ \"acc_norm\": 0.8188679245283019,\n \"acc_norm_stderr\": 0.023702963526757798\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.9166666666666666,\n\ \ \"acc_stderr\": 0.023112508176051236,\n \"acc_norm\": 0.9166666666666666,\n\ \ \"acc_norm_stderr\": 0.023112508176051236\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.63,\n \"acc_stderr\": 0.048523658709391,\n \"acc_norm\":\ \ 0.63,\n \"acc_norm_stderr\": 0.048523658709391\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.48,\n \"acc_stderr\": 0.05021167315686779,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.05021167315686779\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.7456647398843931,\n\ \ \"acc_stderr\": 0.0332055644308557,\n \"acc_norm\": 0.7456647398843931,\n\ \ \"acc_norm_stderr\": 0.0332055644308557\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.5392156862745098,\n \"acc_stderr\": 0.049598599663841815,\n\ \ \"acc_norm\": 0.5392156862745098,\n \"acc_norm_stderr\": 0.049598599663841815\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.82,\n \"acc_stderr\": 0.03861229196653695,\n \"acc_norm\": 0.82,\n\ \ \"acc_norm_stderr\": 0.03861229196653695\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.7957446808510639,\n \"acc_stderr\": 0.026355158413349414,\n\ \ \"acc_norm\": 0.7957446808510639,\n \"acc_norm_stderr\": 0.026355158413349414\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.6052631578947368,\n\ \ \"acc_stderr\": 0.045981880578165414,\n \"acc_norm\": 0.6052631578947368,\n\ \ \"acc_norm_stderr\": 0.045981880578165414\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.7724137931034483,\n \"acc_stderr\": 0.03493950380131184,\n\ \ \"acc_norm\": 0.7724137931034483,\n \"acc_norm_stderr\": 0.03493950380131184\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.6931216931216931,\n \"acc_stderr\": 0.02375292871211213,\n \"\ acc_norm\": 0.6931216931216931,\n \"acc_norm_stderr\": 0.02375292871211213\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.5714285714285714,\n\ \ \"acc_stderr\": 0.04426266681379909,\n \"acc_norm\": 0.5714285714285714,\n\ \ \"acc_norm_stderr\": 0.04426266681379909\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.55,\n \"acc_stderr\": 0.049999999999999996,\n \ \ \"acc_norm\": 0.55,\n \"acc_norm_stderr\": 0.049999999999999996\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\"\ : 0.9096774193548387,\n \"acc_stderr\": 0.016306570644488313,\n \"\ acc_norm\": 0.9096774193548387,\n \"acc_norm_stderr\": 0.016306570644488313\n\ \ },\n \"harness\|hendrycksTest-high_school_chemistry\|5\": {\n \"acc\"\ : 0.6502463054187192,\n \"acc_stderr\": 0.03355400904969566,\n \"\ acc_norm\": 0.6502463054187192,\n \"acc_norm_stderr\": 0.03355400904969566\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.82,\n \"acc_stderr\": 0.038612291966536934,\n \"acc_norm\"\ : 0.82,\n \"acc_norm_stderr\": 0.038612291966536934\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.8666666666666667,\n \"acc_stderr\": 0.026544435312706463,\n\ \ \"acc_norm\": 0.8666666666666667,\n \"acc_norm_stderr\": 0.026544435312706463\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.9292929292929293,\n \"acc_stderr\": 0.018263105420199505,\n \"\ acc_norm\": 0.9292929292929293,\n \"acc_norm_stderr\": 0.018263105420199505\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.9740932642487047,\n \"acc_stderr\": 0.01146452335695318,\n\ \ \"acc_norm\": 0.9740932642487047,\n \"acc_norm_stderr\": 0.01146452335695318\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.8333333333333334,\n \"acc_stderr\": 0.01889552448260495,\n \ \ \"acc_norm\": 0.8333333333333334,\n \"acc_norm_stderr\": 0.01889552448260495\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.42962962962962964,\n \"acc_stderr\": 0.030182099804387262,\n \ \ \"acc_norm\": 0.42962962962962964,\n \"acc_norm_stderr\": 0.030182099804387262\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.8487394957983193,\n \"acc_stderr\": 0.023274255898707946,\n\ \ \"acc_norm\": 0.8487394957983193,\n \"acc_norm_stderr\": 0.023274255898707946\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.5364238410596026,\n \"acc_stderr\": 0.04071636065944217,\n \"\ acc_norm\": 0.5364238410596026,\n \"acc_norm_stderr\": 0.04071636065944217\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.9192660550458716,\n \"acc_stderr\": 0.011680172292862088,\n \"\ acc_norm\": 0.9192660550458716,\n \"acc_norm_stderr\": 0.011680172292862088\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.6527777777777778,\n \"acc_stderr\": 0.032468872436376486,\n \"\ acc_norm\": 0.6527777777777778,\n \"acc_norm_stderr\": 0.032468872436376486\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.9313725490196079,\n \"acc_stderr\": 0.017744453647073322,\n \"\ acc_norm\": 0.9313725490196079,\n \"acc_norm_stderr\": 0.017744453647073322\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.9113924050632911,\n \"acc_stderr\": 0.018498315206865384,\n \ \ \"acc_norm\": 0.9113924050632911,\n \"acc_norm_stderr\": 0.018498315206865384\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.7982062780269058,\n\ \ \"acc_stderr\": 0.02693611191280226,\n \"acc_norm\": 0.7982062780269058,\n\ \ \"acc_norm_stderr\": 0.02693611191280226\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.8854961832061069,\n \"acc_stderr\": 0.027927473753597446,\n\ \ \"acc_norm\": 0.8854961832061069,\n \"acc_norm_stderr\": 0.027927473753597446\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.9008264462809917,\n \"acc_stderr\": 0.027285246312758957,\n \"\ acc_norm\": 0.9008264462809917,\n \"acc_norm_stderr\": 0.027285246312758957\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.8981481481481481,\n\ \ \"acc_stderr\": 0.02923927267563275,\n \"acc_norm\": 0.8981481481481481,\n\ \ \"acc_norm_stderr\": 0.02923927267563275\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.8711656441717791,\n \"acc_stderr\": 0.02632138319878367,\n\ \ \"acc_norm\": 0.8711656441717791,\n \"acc_norm_stderr\": 0.02632138319878367\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.6339285714285714,\n\ \ \"acc_stderr\": 0.04572372358737431,\n \"acc_norm\": 0.6339285714285714,\n\ \ \"acc_norm_stderr\": 0.04572372358737431\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.8932038834951457,\n \"acc_stderr\": 0.030581088928331366,\n\ \ \"acc_norm\": 0.8932038834951457,\n \"acc_norm_stderr\": 0.030581088928331366\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.9401709401709402,\n\ \ \"acc_stderr\": 0.015537514263253876,\n \"acc_norm\": 0.9401709401709402,\n\ \ \"acc_norm_stderr\": 0.015537514263253876\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.89,\n \"acc_stderr\": 0.03144660377352202,\n \ \ \"acc_norm\": 0.89,\n \"acc_norm_stderr\": 0.03144660377352202\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.9067688378033205,\n\ \ \"acc_stderr\": 0.010397417087292849,\n \"acc_norm\": 0.9067688378033205,\n\ \ \"acc_norm_stderr\": 0.010397417087292849\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.8179190751445087,\n \"acc_stderr\": 0.02077676110251298,\n\ \ \"acc_norm\": 0.8179190751445087,\n \"acc_norm_stderr\": 0.02077676110251298\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.794413407821229,\n\ \ \"acc_stderr\": 0.013516116210724202,\n \"acc_norm\": 0.794413407821229,\n\ \ \"acc_norm_stderr\": 0.013516116210724202\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.8366013071895425,\n \"acc_stderr\": 0.021170623011213505,\n\ \ \"acc_norm\": 0.8366013071895425,\n \"acc_norm_stderr\": 0.021170623011213505\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.8295819935691319,\n\ \ \"acc_stderr\": 0.021355343028264053,\n \"acc_norm\": 0.8295819935691319,\n\ \ \"acc_norm_stderr\": 0.021355343028264053\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.8827160493827161,\n \"acc_stderr\": 0.017903112615281123,\n\ \ \"acc_norm\": 0.8827160493827161,\n \"acc_norm_stderr\": 0.017903112615281123\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.648936170212766,\n \"acc_stderr\": 0.028473501272963758,\n \ \ \"acc_norm\": 0.648936170212766,\n \"acc_norm_stderr\": 0.028473501272963758\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.6029986962190352,\n\ \ \"acc_stderr\": 0.012496346982909556,\n \"acc_norm\": 0.6029986962190352,\n\ \ \"acc_norm_stderr\": 0.012496346982909556\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.8419117647058824,\n \"acc_stderr\": 0.022161462608068522,\n\ \ \"acc_norm\": 0.8419117647058824,\n \"acc_norm_stderr\": 0.022161462608068522\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.8169934640522876,\n \"acc_stderr\": 0.015643069911273344,\n \ \ \"acc_norm\": 0.8169934640522876,\n \"acc_norm_stderr\": 0.015643069911273344\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\": 0.8448979591836735,\n \"acc_stderr\": 0.0231747988612186,\n\ \ \"acc_norm\": 0.8448979591836735,\n \"acc_norm_stderr\": 0.0231747988612186\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8855721393034826,\n\ \ \"acc_stderr\": 0.022509345325101706,\n \"acc_norm\": 0.8855721393034826,\n\ \ \"acc_norm_stderr\": 0.022509345325101706\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.91,\n \"acc_stderr\": 0.02876234912646613,\n \ \ \"acc_norm\": 0.91,\n \"acc_norm_stderr\": 0.02876234912646613\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5843373493975904,\n\ \ \"acc_stderr\": 0.03836722176598053,\n \"acc_norm\": 0.5843373493975904,\n\ \ \"acc_norm_stderr\": 0.03836722176598053\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8771929824561403,\n \"acc_stderr\": 0.02517298435015577,\n\ \ \"acc_norm\": 0.8771929824561403,\n \"acc_norm_stderr\": 0.02517298435015577\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.4969400244798042,\n\ \ \"mc1_stderr\": 0.01750317326096062,\n \"mc2\": 0.6709148255495884,\n\ \ \"mc2_stderr\": 0.014645409374455808\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8437253354380426,\n \"acc_stderr\": 0.010205351791873492\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.6626231993934799,\n \ \ \"acc_stderr\": 0.013023665136222096\n }\n}\n```" repo_url: https://huggingface.co/Weyaxi/Bagel-Hermes-34B-Slerp leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|arc:challenge\|25_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-01-14T01-56-18.562449.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|gsm8k\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hellaswag\|10_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-01-14T01-56-18.562449.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-management\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-01-14T01-56-18.562449.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|truthfulqa:mc\|0_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-01-14T01-56-18.562449.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_01_14T01_56_18.562449 path: - '/details_harness\|winogrande\|5_2024-01-14T01-56-18.562449.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-01-14T01-56-18.562449.parquet' - config_name: results data_files: - split: 2024_01_14T01_56_18.562449 path: - results_2024-01-14T01-56-18.562449.parquet - split: latest path: - results_2024-01-14T01-56-18.562449.parquet --- # Dataset Card for Evaluation run of Weyaxi/Bagel-Hermes-34B-Slerp <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [Weyaxi/Bagel-Hermes-34B-Slerp](https://huggingface.co/Weyaxi/Bagel-Hermes-34B-Slerp) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Weyaxi__Bagel-Hermes-34B-Slerp", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-01-14T01:56:18.562449](https://huggingface.co/datasets/open-llm-leaderboard/details_Weyaxi__Bagel-Hermes-34B-Slerp/blob/main/results_2024-01-14T01-56-18.562449.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": 0.7687638749469244, "acc_stderr": 0.02791668972955577, "acc_norm": 0.7731851983230489, "acc_norm_stderr": 0.028441222412067358, "mc1": 0.4969400244798042, "mc1_stderr": 0.01750317326096062, "mc2": 0.6709148255495884, "mc2_stderr": 0.014645409374455808 }, "harness\|arc:challenge\|25": { "acc": 0.6706484641638225, "acc_stderr": 0.013734057652635474, "acc_norm": 0.7073378839590444, "acc_norm_stderr": 0.013295916103619422 }, "harness\|hellaswag\|10": { "acc": 0.6638119896434973, "acc_stderr": 0.004714386376337134, "acc_norm": 0.8568014339772954, "acc_norm_stderr": 0.0034955936625207526 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.7407407407407407, "acc_stderr": 0.03785714465066653, "acc_norm": 0.7407407407407407, "acc_norm_stderr": 0.03785714465066653 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.881578947368421, "acc_stderr": 0.02629399585547494, "acc_norm": 0.881578947368421, "acc_norm_stderr": 0.02629399585547494 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.8, "acc_stderr": 0.04020151261036844, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036844 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.8188679245283019, "acc_stderr": 0.023702963526757798, "acc_norm": 0.8188679245283019, "acc_norm_stderr": 0.023702963526757798 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.9166666666666666, "acc_stderr": 0.023112508176051236, "acc_norm": 0.9166666666666666, "acc_norm_stderr": 0.023112508176051236 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.63, "acc_stderr": 0.048523658709391, "acc_norm": 0.63, "acc_norm_stderr": 0.048523658709391 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.48, "acc_stderr": 0.05021167315686779, "acc_norm": 0.48, "acc_norm_stderr": 0.05021167315686779 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.7456647398843931, "acc_stderr": 0.0332055644308557, "acc_norm": 0.7456647398843931, "acc_norm_stderr": 0.0332055644308557 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.5392156862745098, "acc_stderr": 0.049598599663841815, "acc_norm": 0.5392156862745098, "acc_norm_stderr": 0.049598599663841815 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.82, "acc_stderr": 0.03861229196653695, "acc_norm": 0.82, "acc_norm_stderr": 0.03861229196653695 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.7957446808510639, "acc_stderr": 0.026355158413349414, "acc_norm": 0.7957446808510639, "acc_norm_stderr": 0.026355158413349414 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.6052631578947368, "acc_stderr": 0.045981880578165414, "acc_norm": 0.6052631578947368, "acc_norm_stderr": 0.045981880578165414 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.7724137931034483, "acc_stderr": 0.03493950380131184, "acc_norm": 0.7724137931034483, "acc_norm_stderr": 0.03493950380131184 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.6931216931216931, "acc_stderr": 0.02375292871211213, "acc_norm": 0.6931216931216931, "acc_norm_stderr": 0.02375292871211213 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.5714285714285714, "acc_stderr": 0.04426266681379909, "acc_norm": 0.5714285714285714, "acc_norm_stderr": 0.04426266681379909 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.55, "acc_stderr": 0.049999999999999996, "acc_norm": 0.55, "acc_norm_stderr": 0.049999999999999996 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.9096774193548387, "acc_stderr": 0.016306570644488313, "acc_norm": 0.9096774193548387, "acc_norm_stderr": 0.016306570644488313 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.6502463054187192, "acc_stderr": 0.03355400904969566, "acc_norm": 0.6502463054187192, "acc_norm_stderr": 0.03355400904969566 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.82, "acc_stderr": 0.038612291966536934, "acc_norm": 0.82, "acc_norm_stderr": 0.038612291966536934 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.8666666666666667, "acc_stderr": 0.026544435312706463, "acc_norm": 0.8666666666666667, "acc_norm_stderr": 0.026544435312706463 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.9292929292929293, "acc_stderr": 0.018263105420199505, "acc_norm": 0.9292929292929293, "acc_norm_stderr": 0.018263105420199505 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.9740932642487047, "acc_stderr": 0.01146452335695318, "acc_norm": 0.9740932642487047, "acc_norm_stderr": 0.01146452335695318 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.8333333333333334, "acc_stderr": 0.01889552448260495, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.01889552448260495 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.42962962962962964, "acc_stderr": 0.030182099804387262, "acc_norm": 0.42962962962962964, "acc_norm_stderr": 0.030182099804387262 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.8487394957983193, "acc_stderr": 0.023274255898707946, "acc_norm": 0.8487394957983193, "acc_norm_stderr": 0.023274255898707946 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.5364238410596026, "acc_stderr": 0.04071636065944217, "acc_norm": 0.5364238410596026, "acc_norm_stderr": 0.04071636065944217 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.9192660550458716, "acc_stderr": 0.011680172292862088, "acc_norm": 0.9192660550458716, "acc_norm_stderr": 0.011680172292862088 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.6527777777777778, "acc_stderr": 0.032468872436376486, "acc_norm": 0.6527777777777778, "acc_norm_stderr": 0.032468872436376486 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.9313725490196079, "acc_stderr": 0.017744453647073322, "acc_norm": 0.9313725490196079, "acc_norm_stderr": 0.017744453647073322 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.9113924050632911, "acc_stderr": 0.018498315206865384, "acc_norm": 0.9113924050632911, "acc_norm_stderr": 0.018498315206865384 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.7982062780269058, "acc_stderr": 0.02693611191280226, "acc_norm": 0.7982062780269058, "acc_norm_stderr": 0.02693611191280226 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.8854961832061069, "acc_stderr": 0.027927473753597446, "acc_norm": 0.8854961832061069, "acc_norm_stderr": 0.027927473753597446 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.9008264462809917, "acc_stderr": 0.027285246312758957, "acc_norm": 0.9008264462809917, "acc_norm_stderr": 0.027285246312758957 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.8981481481481481, "acc_stderr": 0.02923927267563275, "acc_norm": 0.8981481481481481, "acc_norm_stderr": 0.02923927267563275 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.8711656441717791, "acc_stderr": 0.02632138319878367, "acc_norm": 0.8711656441717791, "acc_norm_stderr": 0.02632138319878367 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.6339285714285714, "acc_stderr": 0.04572372358737431, "acc_norm": 0.6339285714285714, "acc_norm_stderr": 0.04572372358737431 }, "harness\|hendrycksTest-management\|5": { "acc": 0.8932038834951457, "acc_stderr": 0.030581088928331366, "acc_norm": 0.8932038834951457, "acc_norm_stderr": 0.030581088928331366 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.9401709401709402, "acc_stderr": 0.015537514263253876, "acc_norm": 0.9401709401709402, "acc_norm_stderr": 0.015537514263253876 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.89, "acc_stderr": 0.03144660377352202, "acc_norm": 0.89, "acc_norm_stderr": 0.03144660377352202 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.9067688378033205, "acc_stderr": 0.010397417087292849, "acc_norm": 0.9067688378033205, "acc_norm_stderr": 0.010397417087292849 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.8179190751445087, "acc_stderr": 0.02077676110251298, "acc_norm": 0.8179190751445087, "acc_norm_stderr": 0.02077676110251298 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.794413407821229, "acc_stderr": 0.013516116210724202, "acc_norm": 0.794413407821229, "acc_norm_stderr": 0.013516116210724202 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.8366013071895425, "acc_stderr": 0.021170623011213505, "acc_norm": 0.8366013071895425, "acc_norm_stderr": 0.021170623011213505 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.8295819935691319, "acc_stderr": 0.021355343028264053, "acc_norm": 0.8295819935691319, "acc_norm_stderr": 0.021355343028264053 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.8827160493827161, "acc_stderr": 0.017903112615281123, "acc_norm": 0.8827160493827161, "acc_norm_stderr": 0.017903112615281123 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.648936170212766, "acc_stderr": 0.028473501272963758, "acc_norm": 0.648936170212766, "acc_norm_stderr": 0.028473501272963758 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.6029986962190352, "acc_stderr": 0.012496346982909556, "acc_norm": 0.6029986962190352, "acc_norm_stderr": 0.012496346982909556 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.8419117647058824, "acc_stderr": 0.022161462608068522, "acc_norm": 0.8419117647058824, "acc_norm_stderr": 0.022161462608068522 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.8169934640522876, "acc_stderr": 0.015643069911273344, "acc_norm": 0.8169934640522876, "acc_norm_stderr": 0.015643069911273344 }, "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": 0.8448979591836735, "acc_stderr": 0.0231747988612186, "acc_norm": 0.8448979591836735, "acc_norm_stderr": 0.0231747988612186 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8855721393034826, "acc_stderr": 0.022509345325101706, "acc_norm": 0.8855721393034826, "acc_norm_stderr": 0.022509345325101706 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.91, "acc_stderr": 0.02876234912646613, "acc_norm": 0.91, "acc_norm_stderr": 0.02876234912646613 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5843373493975904, "acc_stderr": 0.03836722176598053, "acc_norm": 0.5843373493975904, "acc_norm_stderr": 0.03836722176598053 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8771929824561403, "acc_stderr": 0.02517298435015577, "acc_norm": 0.8771929824561403, "acc_norm_stderr": 0.02517298435015577 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.4969400244798042, "mc1_stderr": 0.01750317326096062, "mc2": 0.6709148255495884, "mc2_stderr": 0.014645409374455808 }, "harness\|winogrande\|5": { "acc": 0.8437253354380426, "acc_stderr": 0.010205351791873492 }, "harness\|gsm8k\|5": { "acc": 0.6626231993934799, "acc_stderr": 0.013023665136222096 } } ``` ## 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. 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ajyy/MELD_audio	--- dataset_info: - config_name: MELD_Audio features: - name: text dtype: string - name: path dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: emotion dtype: class_label: names: '0': neutral '1': joy '2': sadness '3': anger '4': fear '5': disgust '6': surprise - name: sentiment dtype: class_label: names: '0': neutral '1': positive '2': negative splits: - name: train num_bytes: 3629722 num_examples: 9988 - name: validation num_bytes: 411341 num_examples: 1108 - name: test num_bytes: 945283 num_examples: 2610 download_size: 7840135137 dataset_size: 4986346 license: gpl-3.0 language: - en pretty_name: MELD size_categories: - 10K<n<100K tags: - speech-emotion-recognition --- # Dataset Card for Dataset Name <!-- Provide a quick summary of the dataset. --> The Audio, Speech, and Vision Processing Lab - Emotional Sound Database (ASVP - ESD) ## Dataset Details ### Dataset Description Multimodal EmotionLines Dataset (MELD) has been created by enhancing and extending EmotionLines dataset. MELD contains the same dialogue instances available in EmotionLines, but it also encompasses audio and visual modality along with text. MELD has more than 1400 dialogues and 13000 utterances from Friends TV series. Multiple speakers participated in the dialogues. Each utterance in a dialogue has been labeled by any of these seven emotions -- Anger, Disgust, Sadness, Joy, Neutral, Surprise and Fear. MELD also has sentiment (positive, negative and neutral) annotation for each utterance. This dataset is modified from https://huggingface.co/datasets/zrr1999/MELD_Text_Audio. The audio is extracted from MELD mp4 files while the audio only has one channel with sample rate 16khz. - 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]
davidberenstein1957/ultra-feedback-dutch-cleaned-hq_iter0	--- dataset_info: features: - name: generated list: - name: content dtype: string - name: role dtype: string - name: real list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 82544374.21505675 num_examples: 19426 - name: test num_bytes: 9173957.784943247 num_examples: 2159 download_size: 51274646 dataset_size: 91718332.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* --- # Dataset Card for "ultra-feedback-dutch-cleaned-hq_iter0" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
tyzhu/squad_qa_num_v5_full_recite_full_passage_random_permute_rerun_2	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers sequence: - name: text dtype: string - name: answer_start dtype: int32 - name: answer dtype: string - name: context_id dtype: string - name: inputs dtype: string - name: targets dtype: string splits: - name: train num_bytes: 5985907.839669421 num_examples: 3365 - name: validation num_bytes: 580808 num_examples: 300 download_size: 1607029 dataset_size: 6566715.839669421 --- # Dataset Card for "squad_qa_num_v5_full_recite_full_passage_random_permute_rerun_2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ngxingyu/iwslt17_google_trans	--- license: cc-by-nc-4.0 dataset_info: features: - name: en dtype: string - name: google_zh dtype: string - name: zh dtype: string splits: - name: train num_bytes: 65469523 num_examples: 231266 - name: validation num_bytes: 292199 num_examples: 879 - name: test num_bytes: 2360603 num_examples: 8549 download_size: 44559127 dataset_size: 68122325 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
Romecr/testImages	--- license: other ---
andersonbcdefg/SPECTER-subset-dedup	--- dataset_info: features: - name: query dtype: string - name: pos dtype: string - name: neg dtype: string splits: - name: train num_bytes: 556150901.5824461 num_examples: 128807 download_size: 319036990 dataset_size: 556150901.5824461 configs: - config_name: default data_files: - split: train path: data/train-* ---
jxie/epsilon	--- dataset_info: features: - name: inputs sequence: sequence: float64 - name: label dtype: int64 splits: - name: train num_bytes: 9604800000 num_examples: 400000 - name: test num_bytes: 2401200000 num_examples: 100000 download_size: 7805263919 dataset_size: 12006000000 --- # Dataset Card for "epsilon" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
hippocrates/re_train	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: valid path: data/valid-* dataset_info: features: - name: id dtype: string - name: conversations list: - name: from dtype: string - name: value dtype: string - name: text dtype: string splits: - name: train num_bytes: 19219537 num_examples: 3572 - name: valid num_bytes: 1626844 num_examples: 305 download_size: 1753501 dataset_size: 20846381 --- # Dataset Card for "re_train" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
marcos292/LPMark	--- license: openrail ---
bnsapa/cybersecurity-ner	--- dataset_info: features: - name: id dtype: string - name: tokens sequence: string - name: ner_tags sequence: class_label: names: '0': B-Indicator '1': B-Malware '2': B-Organization '3': B-System '4': B-Vulnerability '5': I-Indicator '6': I-Malware '7': I-Organization '8': I-System '9': I-Vulnerability '10': O splits: - name: train num_bytes: 1197515 num_examples: 2664 - name: test num_bytes: 336600 num_examples: 717 - name: validation num_bytes: 339858 num_examples: 785 download_size: 385026 dataset_size: 1873973 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: validation path: data/validation-* ---
AndrewTsai0406/RGB_zh	--- dataset_info: features: - name: id dtype: int64 - name: query dtype: string - name: answer dtype: string - name: positive dtype: string - name: negative dtype: string splits: - name: train num_bytes: 5871582 num_examples: 300 download_size: 3226142 dataset_size: 5871582 configs: - config_name: default data_files: - split: train path: data/train-* ---
Minata/512_block_tokenized_src_fm_fc_ms_ff_method2testcases_v0	--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 2980662680 num_examples: 447010 - name: test num_bytes: 282063068 num_examples: 42301 download_size: 541623207 dataset_size: 3262725748 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
Deepank/CITYLID	--- license: mit language: - en - de tags: - code - aerial point-cloud - point-cloud classification - urban streetscapes - cross-sections pretty_name: CTLID --- # CITYLID: A large-scale categorized aerial Lidar dataset for street-level research <!-- Provide a quick summary of the dataset. --> This repository is dedicated to providing categorized aerial Lidar datasets along with the methodology for data preparation. Details regarding data preparation and usage are given in the [GitHub Repository](https://github.com/deepankverma/navigating_streetscapes) ### Dataset Description The dataset covers the entire state of Berlin and is divided into 1060 tiles of 1 sq. km each. The tiles are further grouped under [9 regions](https://fbinter.stadt-berlin.de/fb/atom/DOP/Blattschnitt2x2km.gif). The dataset comprises (a) [Categorized Point clouds](Lidar_point_clouds) and (b) [Raster image files providing solar radiation maps](solar_radiation_rasters). The details regarding the data preparation can be found in [GitHub Repository](https://github.com/deepankverma/navigating_streetscapes). ## Citation <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> [Verma, D., Mumm, O., & Carlow, V. M. (2023). Generating citywide street cross-sections using aerial LiDAR and detailed street plan. Sustainable Cities and Society, 96, 104673](https://www.sciencedirect.com/science/article/pii/S2210670723002846)
FINNUMBER/FINCH_TRAIN_NQA_ARI_100	--- dataset_info: features: - name: task dtype: string - name: context dtype: string - name: question dtype: string - name: answer dtype: string - name: instruction dtype: string - name: output dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 282939 num_examples: 100 download_size: 176220 dataset_size: 282939 configs: - config_name: default data_files: - split: train path: data/train-* ---
linqus/github-issues	--- dataset_info: features: - name: url dtype: string - name: repository_url dtype: string - name: labels_url dtype: string - name: comments_url dtype: string - name: events_url dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: number dtype: int64 - name: title dtype: string - name: user struct: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: labels list: - name: color dtype: string - name: default dtype: bool - name: description dtype: string - name: id dtype: int64 - name: name dtype: string - name: node_id dtype: string - name: url dtype: string - name: state dtype: string - name: locked dtype: bool - name: assignee struct: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: assignees list: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: milestone struct: - name: closed_at dtype: string - name: closed_issues dtype: int64 - name: created_at dtype: string - name: creator struct: - name: avatar_url dtype: string - name: events_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: gravatar_id dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: login dtype: string - name: node_id dtype: string - name: organizations_url dtype: string - name: received_events_url dtype: string - name: repos_url dtype: string - name: site_admin dtype: bool - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: type dtype: string - name: url dtype: string - name: description dtype: string - name: due_on dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: labels_url dtype: string - name: node_id dtype: string - name: number dtype: int64 - name: open_issues dtype: int64 - name: state dtype: string - name: title dtype: string - name: updated_at dtype: string - name: url dtype: string - name: comments sequence: string - name: created_at dtype: timestamp[ns, tz=UTC] - name: updated_at dtype: timestamp[ns, tz=UTC] - name: closed_at dtype: timestamp[ns, tz=UTC] - name: author_association dtype: string - name: active_lock_reason dtype: float64 - name: body dtype: string - name: reactions struct: - name: '+1' dtype: int64 - name: '-1' dtype: int64 - name: confused dtype: int64 - name: eyes dtype: int64 - name: heart dtype: int64 - name: hooray dtype: int64 - name: laugh dtype: int64 - name: rocket dtype: int64 - name: total_count dtype: int64 - name: url dtype: string - name: timeline_url dtype: string - name: performed_via_github_app dtype: float64 - name: state_reason dtype: string - name: draft dtype: float64 - name: pull_request struct: - name: diff_url dtype: string - name: html_url dtype: string - name: merged_at dtype: string - name: patch_url dtype: string - name: url dtype: string - name: is_pull_request dtype: bool splits: - name: train num_bytes: 1717058 num_examples: 100 download_size: 564909 dataset_size: 1717058 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for Dataset Name <!-- Provide a quick summary of the dataset. --> This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). ## 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-eval-cnn_dailymail-3.0.0-8ddaed-1457553860	--- type: predictions tags: - autotrain - evaluation datasets: - cnn_dailymail eval_info: task: summarization model: ARTeLab/it5-summarization-fanpage metrics: [] dataset_name: cnn_dailymail dataset_config: 3.0.0 dataset_split: train col_mapping: text: article target: highlights --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Summarization * Model: ARTeLab/it5-summarization-fanpage * Dataset: cnn_dailymail * Config: 3.0.0 * Split: train To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@ehahaha](https://huggingface.co/ehahaha) for evaluating this model.
Elfsong/Bias_NLI	--- dataset_info: features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: '0': entailment '1': neutral '2': contradiction splits: - name: train num_bytes: 136716914 num_examples: 1912390 download_size: 48712225 dataset_size: 136716914 configs: - config_name: default data_files: - split: train path: data/train-* ---
yzhuang/autotree_pmlb_100000_banana_sgosdt_l256_dim10_d3_sd0	--- dataset_info: features: - name: id dtype: int64 - name: input_x sequence: sequence: float32 - name: input_y sequence: sequence: float32 - name: input_y_clean sequence: sequence: float32 - name: rtg sequence: float64 - name: status sequence: sequence: float32 - name: split_threshold sequence: sequence: float32 - name: split_dimension sequence: int64 splits: - name: train num_bytes: 1545200000 num_examples: 100000 - name: validation num_bytes: 154520000 num_examples: 10000 download_size: 281108655 dataset_size: 1699720000 --- # Dataset Card for "autotree_pmlb_100000_banana_sgosdt_l256_dim10_d3_sd0" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
vkaradeniz/moneypay_sss_final_english	--- dataset_info: features: - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 23898 num_examples: 74 download_size: 18721 dataset_size: 23898 configs: - config_name: default data_files: - split: train path: data/train-* ---
ricahrd/MckevinV4	--- license: openrail ---
yezhengli9/opus_books_demo	--- dataset_info: features: - name: id dtype: string - name: translation dtype: translation: languages: - en - fr splits: - name: train num_bytes: 32997043 num_examples: 127085 download_size: 20985324 dataset_size: 32997043 --- # Dataset Card for "opus_books_demo" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
r0ll/zelensky	--- license: openrail language: - us - ua - ru --- Vladimir Zelenskiy 1500 epoch RVC v2. For a good sound, set the pitch to -
andersonbcdefg/amazon_qa_pairs_processed	--- dataset_info: features: - name: query dtype: string - name: pos dtype: string splits: - name: train num_bytes: 837921623 num_examples: 2507114 download_size: 416692810 dataset_size: 837921623 configs: - config_name: default data_files: - split: train path: data/train-* ---
zliu333/truck_at_port	--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 72377986.0 num_examples: 50 download_size: 72368630 dataset_size: 72377986.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
FreedomIntelligence/huatuo_knowledge_graph_qa	--- license: apache-2.0 task_categories: - text-generation language: - zh tags: - medical size_categories: - 100K<n<1M --- # Dataset Card for Huatuo_knowledge_graph_qa ## Dataset Description - Homepage: https://www.huatuogpt.cn/ - Repository: https://github.com/FreedomIntelligence/HuatuoGPT - Paper: https://arxiv.org/abs/2305.01526 - Leaderboard: - Point of Contact: ### Dataset Summary We built this QA dataset based on the medical knowledge map, with a total of 798,444 pieces of data, in which the questions are constructed by means of templates, and the answers are the contents of the entries in the knowledge map. ## Dataset Creation ### Source Data https://cpubmed.openi.org.cn/graph/wiki https://github.com/zhihao-chen/QASystemOnMedicalGraph https://github.com/baiyang2464/chatbot-base-on-Knowledge-Graph ## Citation ``` @misc{li2023huatuo26m, title={Huatuo-26M, a Large-scale Chinese Medical QA Dataset}, author={Jianquan Li and Xidong Wang and Xiangbo Wu and Zhiyi Zhang and Xiaolong Xu and Jie Fu and Prayag Tiwari and Xiang Wan and Benyou Wang}, year={2023}, eprint={2305.01526}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```
Sujithanumala/TheFinalPropagandaDataset	--- dataset_info: features: - name: content dtype: string - name: labels sequence: string splits: - name: train num_bytes: 7806192 num_examples: 1062 download_size: 1241070 dataset_size: 7806192 configs: - config_name: default data_files: - split: train path: data/train-* ---
CoCoRooXin/eu_topic_inclusion	--- dataset_info: features: - name: topic dtype: string - name: syntagm dtype: string - name: labels dtype: int64 - name: root dtype: string splits: - name: train num_bytes: 2330816 num_examples: 34295 - name: test num_bytes: 496594 num_examples: 7350 - name: eval num_bytes: 499052 num_examples: 7349 download_size: 1104598 dataset_size: 3326462 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: eval path: data/eval-* ---
open-llm-leaderboard/details_abdulrahman-nuzha__finetuned-llama-v2.0	--- pretty_name: Evaluation run of abdulrahman-nuzha/finetuned-llama-v2.0 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [abdulrahman-nuzha/finetuned-llama-v2.0](https://huggingface.co/abdulrahman-nuzha/finetuned-llama-v2.0)\ \ 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_abdulrahman-nuzha__finetuned-llama-v2.0\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-10T10:47:40.022995](https://huggingface.co/datasets/open-llm-leaderboard/details_abdulrahman-nuzha__finetuned-llama-v2.0/blob/main/results_2023-12-10T10-47-40.022995.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\": 0.43945994951550066,\n\ \ \"acc_stderr\": 0.034385529407471936,\n \"acc_norm\": 0.4442918982351828,\n\ \ \"acc_norm_stderr\": 0.035190222707291795,\n \"mc1\": 0.24969400244798043,\n\ \ \"mc1_stderr\": 0.015152286907148128,\n \"mc2\": 0.3908033560283727,\n\ \ \"mc2_stderr\": 0.013656125379191442\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.4803754266211604,\n \"acc_stderr\": 0.014600132075947087,\n\ \ \"acc_norm\": 0.5315699658703071,\n \"acc_norm_stderr\": 0.014582236460866978\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5789683330013942,\n\ \ \"acc_stderr\": 0.0049271558825981845,\n \"acc_norm\": 0.7775343557060347,\n\ \ \"acc_norm_stderr\": 0.0041505226302310265\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.42962962962962964,\n\ \ \"acc_stderr\": 0.04276349494376599,\n \"acc_norm\": 0.42962962962962964,\n\ \ \"acc_norm_stderr\": 0.04276349494376599\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.40789473684210525,\n \"acc_stderr\": 0.03999309712777471,\n\ \ \"acc_norm\": 0.40789473684210525,\n \"acc_norm_stderr\": 0.03999309712777471\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.49,\n\ \ \"acc_stderr\": 0.05024183937956911,\n \"acc_norm\": 0.49,\n \ \ \"acc_norm_stderr\": 0.05024183937956911\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.44528301886792454,\n \"acc_stderr\": 0.030588052974270655,\n\ \ \"acc_norm\": 0.44528301886792454,\n \"acc_norm_stderr\": 0.030588052974270655\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.4444444444444444,\n\ \ \"acc_stderr\": 0.04155319955593146,\n \"acc_norm\": 0.4444444444444444,\n\ \ \"acc_norm_stderr\": 0.04155319955593146\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \"acc_norm\": 0.4,\n\ \ \"acc_norm_stderr\": 0.049236596391733084\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.37572254335260113,\n\ \ \"acc_stderr\": 0.036928207672648664,\n \"acc_norm\": 0.37572254335260113,\n\ \ \"acc_norm_stderr\": 0.036928207672648664\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.18627450980392157,\n \"acc_stderr\": 0.038739587141493524,\n\ \ \"acc_norm\": 0.18627450980392157,\n \"acc_norm_stderr\": 0.038739587141493524\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.58,\n \"acc_stderr\": 0.04960449637488583,\n \"acc_norm\": 0.58,\n\ \ \"acc_norm_stderr\": 0.04960449637488583\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.4425531914893617,\n \"acc_stderr\": 0.03246956919789958,\n\ \ \"acc_norm\": 0.4425531914893617,\n \"acc_norm_stderr\": 0.03246956919789958\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.2982456140350877,\n\ \ \"acc_stderr\": 0.04303684033537315,\n \"acc_norm\": 0.2982456140350877,\n\ \ \"acc_norm_stderr\": 0.04303684033537315\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.46206896551724136,\n \"acc_stderr\": 0.041546596717075474,\n\ \ \"acc_norm\": 0.46206896551724136,\n \"acc_norm_stderr\": 0.041546596717075474\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.24074074074074073,\n \"acc_stderr\": 0.02201908001221789,\n \"\ acc_norm\": 0.24074074074074073,\n \"acc_norm_stderr\": 0.02201908001221789\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.04216370213557835,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.04216370213557835\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.36,\n \"acc_stderr\": 0.04824181513244218,\n \ \ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.04824181513244218\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.4290322580645161,\n\ \ \"acc_stderr\": 0.02815603653823321,\n \"acc_norm\": 0.4290322580645161,\n\ \ \"acc_norm_stderr\": 0.02815603653823321\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.3448275862068966,\n \"acc_stderr\": 0.03344283744280458,\n\ \ \"acc_norm\": 0.3448275862068966,\n \"acc_norm_stderr\": 0.03344283744280458\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\"\ : 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.5636363636363636,\n \"acc_stderr\": 0.03872592983524754,\n\ \ \"acc_norm\": 0.5636363636363636,\n \"acc_norm_stderr\": 0.03872592983524754\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.4696969696969697,\n \"acc_stderr\": 0.03555804051763929,\n \"\ acc_norm\": 0.4696969696969697,\n \"acc_norm_stderr\": 0.03555804051763929\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.6321243523316062,\n \"acc_stderr\": 0.034801756684660366,\n\ \ \"acc_norm\": 0.6321243523316062,\n \"acc_norm_stderr\": 0.034801756684660366\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.4,\n \"acc_stderr\": 0.024838811988033158,\n \"acc_norm\"\ : 0.4,\n \"acc_norm_stderr\": 0.024838811988033158\n },\n \"harness\|hendrycksTest-high_school_mathematics\|5\"\ : {\n \"acc\": 0.24814814814814815,\n \"acc_stderr\": 0.0263357394040558,\n\ \ \"acc_norm\": 0.24814814814814815,\n \"acc_norm_stderr\": 0.0263357394040558\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.3907563025210084,\n \"acc_stderr\": 0.031693802357129965,\n\ \ \"acc_norm\": 0.3907563025210084,\n \"acc_norm_stderr\": 0.031693802357129965\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.2980132450331126,\n \"acc_stderr\": 0.03734535676787198,\n \"\ acc_norm\": 0.2980132450331126,\n \"acc_norm_stderr\": 0.03734535676787198\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.5853211009174312,\n \"acc_stderr\": 0.021122903208602585,\n \"\ acc_norm\": 0.5853211009174312,\n \"acc_norm_stderr\": 0.021122903208602585\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.18055555555555555,\n \"acc_stderr\": 0.02623287897149166,\n \"\ acc_norm\": 0.18055555555555555,\n \"acc_norm_stderr\": 0.02623287897149166\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.4803921568627451,\n \"acc_stderr\": 0.03506612560524867,\n \"\ acc_norm\": 0.4803921568627451,\n \"acc_norm_stderr\": 0.03506612560524867\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.5443037974683544,\n \"acc_stderr\": 0.03241920684693334,\n \ \ \"acc_norm\": 0.5443037974683544,\n \"acc_norm_stderr\": 0.03241920684693334\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.5291479820627802,\n\ \ \"acc_stderr\": 0.03350073248773404,\n \"acc_norm\": 0.5291479820627802,\n\ \ \"acc_norm_stderr\": 0.03350073248773404\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.46564885496183206,\n \"acc_stderr\": 0.04374928560599738,\n\ \ \"acc_norm\": 0.46564885496183206,\n \"acc_norm_stderr\": 0.04374928560599738\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.628099173553719,\n \"acc_stderr\": 0.044120158066245044,\n \"\ acc_norm\": 0.628099173553719,\n \"acc_norm_stderr\": 0.044120158066245044\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.4722222222222222,\n\ \ \"acc_stderr\": 0.04826217294139894,\n \"acc_norm\": 0.4722222222222222,\n\ \ \"acc_norm_stderr\": 0.04826217294139894\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.4601226993865031,\n \"acc_stderr\": 0.03915857291436972,\n\ \ \"acc_norm\": 0.4601226993865031,\n \"acc_norm_stderr\": 0.03915857291436972\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.38392857142857145,\n\ \ \"acc_stderr\": 0.04616143075028547,\n \"acc_norm\": 0.38392857142857145,\n\ \ \"acc_norm_stderr\": 0.04616143075028547\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.47572815533980584,\n \"acc_stderr\": 0.049449010929737795,\n\ \ \"acc_norm\": 0.47572815533980584,\n \"acc_norm_stderr\": 0.049449010929737795\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.6837606837606838,\n\ \ \"acc_stderr\": 0.030463656747340275,\n \"acc_norm\": 0.6837606837606838,\n\ \ \"acc_norm_stderr\": 0.030463656747340275\n },\n \"harness\|hendrycksTest-medical_genetics\|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-miscellaneous\|5\": {\n \"acc\": 0.6002554278416348,\n\ \ \"acc_stderr\": 0.017516847907053282,\n \"acc_norm\": 0.6002554278416348,\n\ \ \"acc_norm_stderr\": 0.017516847907053282\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.48554913294797686,\n \"acc_stderr\": 0.02690784985628254,\n\ \ \"acc_norm\": 0.48554913294797686,\n \"acc_norm_stderr\": 0.02690784985628254\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.23798882681564246,\n\ \ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\ \ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.5,\n \"acc_stderr\": 0.028629916715693413,\n \ \ \"acc_norm\": 0.5,\n \"acc_norm_stderr\": 0.028629916715693413\n \ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.5562700964630225,\n\ \ \"acc_stderr\": 0.028217683556652308,\n \"acc_norm\": 0.5562700964630225,\n\ \ \"acc_norm_stderr\": 0.028217683556652308\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.5030864197530864,\n \"acc_stderr\": 0.027820214158594363,\n\ \ \"acc_norm\": 0.5030864197530864,\n \"acc_norm_stderr\": 0.027820214158594363\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.32269503546099293,\n \"acc_stderr\": 0.02788913930053478,\n \ \ \"acc_norm\": 0.32269503546099293,\n \"acc_norm_stderr\": 0.02788913930053478\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.32920469361147325,\n\ \ \"acc_stderr\": 0.012002091666902297,\n \"acc_norm\": 0.32920469361147325,\n\ \ \"acc_norm_stderr\": 0.012002091666902297\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.44485294117647056,\n \"acc_stderr\": 0.030187532060329387,\n\ \ \"acc_norm\": 0.44485294117647056,\n \"acc_norm_stderr\": 0.030187532060329387\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.4297385620915033,\n \"acc_stderr\": 0.020027122784928554,\n \ \ \"acc_norm\": 0.4297385620915033,\n \"acc_norm_stderr\": 0.020027122784928554\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.45454545454545453,\n\ \ \"acc_stderr\": 0.04769300568972744,\n \"acc_norm\": 0.45454545454545453,\n\ \ \"acc_norm_stderr\": 0.04769300568972744\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.363265306122449,\n \"acc_stderr\": 0.03078905113903081,\n\ \ \"acc_norm\": 0.363265306122449,\n \"acc_norm_stderr\": 0.03078905113903081\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.5920398009950248,\n\ \ \"acc_stderr\": 0.03475116365194092,\n \"acc_norm\": 0.5920398009950248,\n\ \ \"acc_norm_stderr\": 0.03475116365194092\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.65,\n \"acc_stderr\": 0.047937248544110196,\n \ \ \"acc_norm\": 0.65,\n \"acc_norm_stderr\": 0.047937248544110196\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.3855421686746988,\n\ \ \"acc_stderr\": 0.037891344246115496,\n \"acc_norm\": 0.3855421686746988,\n\ \ \"acc_norm_stderr\": 0.037891344246115496\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.6374269005847953,\n \"acc_stderr\": 0.0368713061556206,\n\ \ \"acc_norm\": 0.6374269005847953,\n \"acc_norm_stderr\": 0.0368713061556206\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.24969400244798043,\n\ \ \"mc1_stderr\": 0.015152286907148128,\n \"mc2\": 0.3908033560283727,\n\ \ \"mc2_stderr\": 0.013656125379191442\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.744277821625888,\n \"acc_stderr\": 0.012261253845440474\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.09931766489764973,\n \ \ \"acc_stderr\": 0.008238371412683965\n }\n}\n```" repo_url: https://huggingface.co/abdulrahman-nuzha/finetuned-llama-v2.0 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_12_10T10_47_40.022995 path: - '/details_harness\|arc:challenge\|25_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-12-10T10-47-40.022995.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|gsm8k\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hellaswag\|10_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-10T10-47-40.022995.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-management\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-10T10-47-40.022995.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|truthfulqa:mc\|0_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-12-10T10-47-40.022995.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_10T10_47_40.022995 path: - '/details_harness\|winogrande\|5_2023-12-10T10-47-40.022995.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-12-10T10-47-40.022995.parquet' - config_name: results data_files: - split: 2023_12_10T10_47_40.022995 path: - results_2023-12-10T10-47-40.022995.parquet - split: latest path: - results_2023-12-10T10-47-40.022995.parquet --- # Dataset Card for Evaluation run of abdulrahman-nuzha/finetuned-llama-v2.0 ## Dataset Description - Homepage: - Repository: https://huggingface.co/abdulrahman-nuzha/finetuned-llama-v2.0 - 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 [abdulrahman-nuzha/finetuned-llama-v2.0](https://huggingface.co/abdulrahman-nuzha/finetuned-llama-v2.0) 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_abdulrahman-nuzha__finetuned-llama-v2.0", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-10T10:47:40.022995](https://huggingface.co/datasets/open-llm-leaderboard/details_abdulrahman-nuzha__finetuned-llama-v2.0/blob/main/results_2023-12-10T10-47-40.022995.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": 0.43945994951550066, "acc_stderr": 0.034385529407471936, "acc_norm": 0.4442918982351828, "acc_norm_stderr": 0.035190222707291795, "mc1": 0.24969400244798043, "mc1_stderr": 0.015152286907148128, "mc2": 0.3908033560283727, "mc2_stderr": 0.013656125379191442 }, "harness\|arc:challenge\|25": { "acc": 0.4803754266211604, "acc_stderr": 0.014600132075947087, "acc_norm": 0.5315699658703071, "acc_norm_stderr": 0.014582236460866978 }, "harness\|hellaswag\|10": { "acc": 0.5789683330013942, "acc_stderr": 0.0049271558825981845, "acc_norm": 0.7775343557060347, "acc_norm_stderr": 0.0041505226302310265 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.42962962962962964, "acc_stderr": 0.04276349494376599, "acc_norm": 0.42962962962962964, "acc_norm_stderr": 0.04276349494376599 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.40789473684210525, "acc_stderr": 0.03999309712777471, "acc_norm": 0.40789473684210525, "acc_norm_stderr": 0.03999309712777471 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.49, "acc_stderr": 0.05024183937956911, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956911 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.44528301886792454, "acc_stderr": 0.030588052974270655, "acc_norm": 0.44528301886792454, "acc_norm_stderr": 0.030588052974270655 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.4444444444444444, "acc_stderr": 0.04155319955593146, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.04155319955593146 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.37572254335260113, "acc_stderr": 0.036928207672648664, "acc_norm": 0.37572254335260113, "acc_norm_stderr": 0.036928207672648664 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.18627450980392157, "acc_stderr": 0.038739587141493524, "acc_norm": 0.18627450980392157, "acc_norm_stderr": 0.038739587141493524 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.58, "acc_stderr": 0.04960449637488583, "acc_norm": 0.58, "acc_norm_stderr": 0.04960449637488583 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.4425531914893617, "acc_stderr": 0.03246956919789958, "acc_norm": 0.4425531914893617, "acc_norm_stderr": 0.03246956919789958 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.2982456140350877, "acc_stderr": 0.04303684033537315, "acc_norm": 0.2982456140350877, "acc_norm_stderr": 0.04303684033537315 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.46206896551724136, "acc_stderr": 0.041546596717075474, "acc_norm": 0.46206896551724136, "acc_norm_stderr": 0.041546596717075474 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.24074074074074073, "acc_stderr": 0.02201908001221789, "acc_norm": 0.24074074074074073, "acc_norm_stderr": 0.02201908001221789 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04216370213557835, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04216370213557835 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.4290322580645161, "acc_stderr": 0.02815603653823321, "acc_norm": 0.4290322580645161, "acc_norm_stderr": 0.02815603653823321 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.3448275862068966, "acc_stderr": 0.03344283744280458, "acc_norm": 0.3448275862068966, "acc_norm_stderr": 0.03344283744280458 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.5636363636363636, "acc_stderr": 0.03872592983524754, "acc_norm": 0.5636363636363636, "acc_norm_stderr": 0.03872592983524754 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.4696969696969697, "acc_stderr": 0.03555804051763929, "acc_norm": 0.4696969696969697, "acc_norm_stderr": 0.03555804051763929 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.6321243523316062, "acc_stderr": 0.034801756684660366, "acc_norm": 0.6321243523316062, "acc_norm_stderr": 0.034801756684660366 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.4, "acc_stderr": 0.024838811988033158, "acc_norm": 0.4, "acc_norm_stderr": 0.024838811988033158 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.24814814814814815, "acc_stderr": 0.0263357394040558, "acc_norm": 0.24814814814814815, "acc_norm_stderr": 0.0263357394040558 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.3907563025210084, "acc_stderr": 0.031693802357129965, "acc_norm": 0.3907563025210084, "acc_norm_stderr": 0.031693802357129965 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.2980132450331126, "acc_stderr": 0.03734535676787198, "acc_norm": 0.2980132450331126, "acc_norm_stderr": 0.03734535676787198 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.5853211009174312, "acc_stderr": 0.021122903208602585, "acc_norm": 0.5853211009174312, "acc_norm_stderr": 0.021122903208602585 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.18055555555555555, "acc_stderr": 0.02623287897149166, "acc_norm": 0.18055555555555555, "acc_norm_stderr": 0.02623287897149166 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.4803921568627451, "acc_stderr": 0.03506612560524867, "acc_norm": 0.4803921568627451, "acc_norm_stderr": 0.03506612560524867 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.5443037974683544, "acc_stderr": 0.03241920684693334, "acc_norm": 0.5443037974683544, "acc_norm_stderr": 0.03241920684693334 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.5291479820627802, "acc_stderr": 0.03350073248773404, "acc_norm": 0.5291479820627802, "acc_norm_stderr": 0.03350073248773404 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.46564885496183206, "acc_stderr": 0.04374928560599738, "acc_norm": 0.46564885496183206, "acc_norm_stderr": 0.04374928560599738 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.628099173553719, "acc_stderr": 0.044120158066245044, "acc_norm": 0.628099173553719, "acc_norm_stderr": 0.044120158066245044 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.4722222222222222, "acc_stderr": 0.04826217294139894, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.04826217294139894 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.4601226993865031, "acc_stderr": 0.03915857291436972, "acc_norm": 0.4601226993865031, "acc_norm_stderr": 0.03915857291436972 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.38392857142857145, "acc_stderr": 0.04616143075028547, "acc_norm": 0.38392857142857145, "acc_norm_stderr": 0.04616143075028547 }, "harness\|hendrycksTest-management\|5": { "acc": 0.47572815533980584, "acc_stderr": 0.049449010929737795, "acc_norm": 0.47572815533980584, "acc_norm_stderr": 0.049449010929737795 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.6837606837606838, "acc_stderr": 0.030463656747340275, "acc_norm": 0.6837606837606838, "acc_norm_stderr": 0.030463656747340275 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.6002554278416348, "acc_stderr": 0.017516847907053282, "acc_norm": 0.6002554278416348, "acc_norm_stderr": 0.017516847907053282 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.48554913294797686, "acc_stderr": 0.02690784985628254, "acc_norm": 0.48554913294797686, "acc_norm_stderr": 0.02690784985628254 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.23798882681564246, "acc_stderr": 0.014242630070574915, "acc_norm": 0.23798882681564246, "acc_norm_stderr": 0.014242630070574915 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.5, "acc_stderr": 0.028629916715693413, "acc_norm": 0.5, "acc_norm_stderr": 0.028629916715693413 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.5562700964630225, "acc_stderr": 0.028217683556652308, "acc_norm": 0.5562700964630225, "acc_norm_stderr": 0.028217683556652308 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.5030864197530864, "acc_stderr": 0.027820214158594363, "acc_norm": 0.5030864197530864, "acc_norm_stderr": 0.027820214158594363 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.32269503546099293, "acc_stderr": 0.02788913930053478, "acc_norm": 0.32269503546099293, "acc_norm_stderr": 0.02788913930053478 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.32920469361147325, "acc_stderr": 0.012002091666902297, "acc_norm": 0.32920469361147325, "acc_norm_stderr": 0.012002091666902297 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.44485294117647056, "acc_stderr": 0.030187532060329387, "acc_norm": 0.44485294117647056, "acc_norm_stderr": 0.030187532060329387 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.4297385620915033, "acc_stderr": 0.020027122784928554, "acc_norm": 0.4297385620915033, "acc_norm_stderr": 0.020027122784928554 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.45454545454545453, "acc_stderr": 0.04769300568972744, "acc_norm": 0.45454545454545453, "acc_norm_stderr": 0.04769300568972744 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.363265306122449, "acc_stderr": 0.03078905113903081, "acc_norm": 0.363265306122449, "acc_norm_stderr": 0.03078905113903081 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.5920398009950248, "acc_stderr": 0.03475116365194092, "acc_norm": 0.5920398009950248, "acc_norm_stderr": 0.03475116365194092 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.3855421686746988, "acc_stderr": 0.037891344246115496, "acc_norm": 0.3855421686746988, "acc_norm_stderr": 0.037891344246115496 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.6374269005847953, "acc_stderr": 0.0368713061556206, "acc_norm": 0.6374269005847953, "acc_norm_stderr": 0.0368713061556206 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.24969400244798043, "mc1_stderr": 0.015152286907148128, "mc2": 0.3908033560283727, "mc2_stderr": 0.013656125379191442 }, "harness\|winogrande\|5": { "acc": 0.744277821625888, "acc_stderr": 0.012261253845440474 }, "harness\|gsm8k\|5": { "acc": 0.09931766489764973, "acc_stderr": 0.008238371412683965 } } ``` ### 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]
OmarAmir2001/my-image-dataset	--- dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 11730860.0 num_examples: 119 download_size: 11636743 dataset_size: 11730860.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
AlekseyKorshuk/cup-it-ds-classification-small-2	--- dataset_info: features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 4545195 num_examples: 7930 - name: validation num_bytes: 1259443 num_examples: 2203 download_size: 3520634 dataset_size: 5804638 --- # Dataset Card for "cup-it-ds-classification-small-2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Leon-LLM/Leon-Chess-Dataset-1M	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 551374495 num_examples: 1028170 download_size: 282346024 dataset_size: 551374495 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "Leon-Chess-Dataset-1M" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Nille1991/Leitliniendatenbank	--- license: bigscience-openrail-m language: - de size_categories: - n<1K --- In dieser Datenbank werden alle AWMF Leitlinien hinterlegt, die die Deutsche Gesellschaft für Orthopädie und Unfallchirurgie (DGOU) erstellt hat.
reichenbach/arxiv_ppr_embeds	--- annotations_creators: - found language: - en language_creators: - found license: - unknown multilinguality: - monolingual pretty_name: ScientificPapers size_categories: - 100K<n<1M source_datasets: - scientific_papers task_categories: - summarization task_ids: [] paperswithcode_id: null tags: - abstractive-summarization dataset_info: features: - name: article dtype: string - name: abstract dtype: string - name: embeddings sequence: float64 splits: - name: train num_bytes: 8367611540 num_examples: 203037 - name: validation num_bytes: 256178362 num_examples: 6440 - name: test num_bytes: 255771184 num_examples: 6436 download_size: 4718720913 dataset_size: 8879561086 --- # Dataset Card for "scientific_papers" This dataset is derived from https://huggingface.co/datasets/scientific_papers with additional creation of embeddings via https://huggingface.co/docs/transformers/model_doc/rag for Natural Questions trained Base Model. This dataset is created for purpose of Retrieval Augmented Generation examples and experiments. ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: - Repository: https://github.com/armancohan/long-summarization - Paper: [A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents](https://arxiv.org/abs/1804.05685) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Dataset Summary Scientific papers datasets contains one sets of long and structured documents. The datasets are obtained from ArXiv repositories. ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Dataset Structure ### Data Instances #### arxiv - Size of downloaded dataset files: 4.50 GB - Size of the generated dataset: 7.58 GB - Total amount of disk used: 12.09 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "abstract": "\" we have studied the leptonic decay @xmath0 , via the decay channel @xmath1 , using a sample of tagged @xmath2 decays collected...", "article": "\"the leptonic decays of a charged pseudoscalar meson @xmath7 are processes of the type @xmath8 , where @xmath9 , @xmath10 , or @...", "section_names": "[sec:introduction]introduction\n[sec:detector]data and the cleo- detector\n[sec:analysys]analysis method\n[sec:conclusion]summary" } ``` ### Data Fields The data fields are the same among all splits. #### arxiv - `article`: a `string` feature. - `abstract`: a `string` feature. - `section_names`: a `string` feature. - `embeddings`: a `float` 768 dimensional vector ### Data Splits \| name \|train \|validation\|test\| \|------\|-----:\|---------:\|---:\| \|arxiv \|203037\| 6436\|6440\| ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @article{Cohan_2018, title={A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents}, url={http://dx.doi.org/10.18653/v1/n18-2097}, DOI={10.18653/v1/n18-2097}, journal={Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)}, publisher={Association for Computational Linguistics}, author={Cohan, Arman and Dernoncourt, Franck and Kim, Doo Soon and Bui, Trung and Kim, Seokhwan and Chang, Walter and Goharian, Nazli}, year={2018} } ``` ### Contributions Thanks to [@thomwolf](https://github.com/thomwolf), [@jplu](https://github.com/jplu), [@lewtun](https://github.com/lewtun), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.
open-llm-leaderboard/details_JunchengXie__Mistral-7B-Instruct-v0.1-gpt-4-80k-base_lora	--- pretty_name: Evaluation run of JunchengXie/Mistral-7B-Instruct-v0.1-gpt-4-80k-base_lora dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [JunchengXie/Mistral-7B-Instruct-v0.1-gpt-4-80k-base_lora](https://huggingface.co/JunchengXie/Mistral-7B-Instruct-v0.1-gpt-4-80k-base_lora)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_JunchengXie__Mistral-7B-Instruct-v0.1-gpt-4-80k-base_lora\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-27T23:56:07.967023](https://huggingface.co/datasets/open-llm-leaderboard/details_JunchengXie__Mistral-7B-Instruct-v0.1-gpt-4-80k-base_lora/blob/main/results_2024-03-27T23-56-07.967023.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\": 0.5452277178528238,\n\ \ \"acc_stderr\": 0.03410493442579154,\n \"acc_norm\": 0.5519072949752738,\n\ \ \"acc_norm_stderr\": 0.03485960483749285,\n \"mc1\": 0.412484700122399,\n\ \ \"mc1_stderr\": 0.01723329939957122,\n \"mc2\": 0.5680735045864234,\n\ \ \"mc2_stderr\": 0.01559042793493668\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.5162116040955631,\n \"acc_stderr\": 0.014603708567414945,\n\ \ \"acc_norm\": 0.5366894197952219,\n \"acc_norm_stderr\": 0.01457200052775699\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5514837681736706,\n\ \ \"acc_stderr\": 0.004963259311700565,\n \"acc_norm\": 0.7358095996813384,\n\ \ \"acc_norm_stderr\": 0.004400000822742066\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.4444444444444444,\n\ \ \"acc_stderr\": 0.04292596718256981,\n \"acc_norm\": 0.4444444444444444,\n\ \ \"acc_norm_stderr\": 0.04292596718256981\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.5460526315789473,\n \"acc_stderr\": 0.04051646342874141,\n\ \ \"acc_norm\": 0.5460526315789473,\n \"acc_norm_stderr\": 0.04051646342874141\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.53,\n\ \ \"acc_stderr\": 0.05016135580465919,\n \"acc_norm\": 0.53,\n \ \ \"acc_norm_stderr\": 0.05016135580465919\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.569811320754717,\n \"acc_stderr\": 0.030471445867183235,\n\ \ \"acc_norm\": 0.569811320754717,\n \"acc_norm_stderr\": 0.030471445867183235\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.6319444444444444,\n\ \ \"acc_stderr\": 0.040329990539607195,\n \"acc_norm\": 0.6319444444444444,\n\ \ \"acc_norm_stderr\": 0.040329990539607195\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.42,\n \"acc_stderr\": 0.04960449637488584,\n \ \ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.04960449637488584\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|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_mathematics\|5\"\ : {\n \"acc\": 0.37,\n \"acc_stderr\": 0.04852365870939099,\n \ \ \"acc_norm\": 0.37,\n \"acc_norm_stderr\": 0.04852365870939099\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.5260115606936416,\n\ \ \"acc_stderr\": 0.03807301726504513,\n \"acc_norm\": 0.5260115606936416,\n\ \ \"acc_norm_stderr\": 0.03807301726504513\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.28431372549019607,\n \"acc_stderr\": 0.04488482852329017,\n\ \ \"acc_norm\": 0.28431372549019607,\n \"acc_norm_stderr\": 0.04488482852329017\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.71,\n \"acc_stderr\": 0.045604802157206845,\n \"acc_norm\": 0.71,\n\ \ \"acc_norm_stderr\": 0.045604802157206845\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.4808510638297872,\n \"acc_stderr\": 0.03266204299064678,\n\ \ \"acc_norm\": 0.4808510638297872,\n \"acc_norm_stderr\": 0.03266204299064678\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.35964912280701755,\n\ \ \"acc_stderr\": 0.04514496132873633,\n \"acc_norm\": 0.35964912280701755,\n\ \ \"acc_norm_stderr\": 0.04514496132873633\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5241379310344828,\n \"acc_stderr\": 0.0416180850350153,\n\ \ \"acc_norm\": 0.5241379310344828,\n \"acc_norm_stderr\": 0.0416180850350153\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.35714285714285715,\n \"acc_stderr\": 0.024677862841332786,\n \"\ acc_norm\": 0.35714285714285715,\n \"acc_norm_stderr\": 0.024677862841332786\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.3888888888888889,\n\ \ \"acc_stderr\": 0.04360314860077459,\n \"acc_norm\": 0.3888888888888889,\n\ \ \"acc_norm_stderr\": 0.04360314860077459\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.36,\n \"acc_stderr\": 0.04824181513244218,\n \ \ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.04824181513244218\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.6451612903225806,\n\ \ \"acc_stderr\": 0.027218889773308753,\n \"acc_norm\": 0.6451612903225806,\n\ \ \"acc_norm_stderr\": 0.027218889773308753\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.3891625615763547,\n \"acc_stderr\": 0.034304624161038716,\n\ \ \"acc_norm\": 0.3891625615763547,\n \"acc_norm_stderr\": 0.034304624161038716\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.54,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\"\ : 0.54,\n \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.6787878787878788,\n \"acc_stderr\": 0.0364620496325381,\n\ \ \"acc_norm\": 0.6787878787878788,\n \"acc_norm_stderr\": 0.0364620496325381\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7121212121212122,\n \"acc_stderr\": 0.03225883512300992,\n \"\ acc_norm\": 0.7121212121212122,\n \"acc_norm_stderr\": 0.03225883512300992\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.7357512953367875,\n \"acc_stderr\": 0.03182155050916645,\n\ \ \"acc_norm\": 0.7357512953367875,\n \"acc_norm_stderr\": 0.03182155050916645\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.5128205128205128,\n \"acc_stderr\": 0.02534267129380725,\n \ \ \"acc_norm\": 0.5128205128205128,\n \"acc_norm_stderr\": 0.02534267129380725\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2962962962962963,\n \"acc_stderr\": 0.027840811495871916,\n \ \ \"acc_norm\": 0.2962962962962963,\n \"acc_norm_stderr\": 0.027840811495871916\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.5252100840336135,\n \"acc_stderr\": 0.03243718055137411,\n \ \ \"acc_norm\": 0.5252100840336135,\n \"acc_norm_stderr\": 0.03243718055137411\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\"\ : 0.7137614678899082,\n \"acc_stderr\": 0.01937943662892,\n \"acc_norm\"\ : 0.7137614678899082,\n \"acc_norm_stderr\": 0.01937943662892\n },\n \ \ \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\": 0.4166666666666667,\n\ \ \"acc_stderr\": 0.03362277436608044,\n \"acc_norm\": 0.4166666666666667,\n\ \ \"acc_norm_stderr\": 0.03362277436608044\n },\n \"harness\|hendrycksTest-high_school_us_history\|5\"\ : {\n \"acc\": 0.7107843137254902,\n \"acc_stderr\": 0.031822318676475544,\n\ \ \"acc_norm\": 0.7107843137254902,\n \"acc_norm_stderr\": 0.031822318676475544\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7088607594936709,\n \"acc_stderr\": 0.02957160106575337,\n \ \ \"acc_norm\": 0.7088607594936709,\n \"acc_norm_stderr\": 0.02957160106575337\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6502242152466368,\n\ \ \"acc_stderr\": 0.03200736719484503,\n \"acc_norm\": 0.6502242152466368,\n\ \ \"acc_norm_stderr\": 0.03200736719484503\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.6412213740458015,\n \"acc_stderr\": 0.04206739313864908,\n\ \ \"acc_norm\": 0.6412213740458015,\n \"acc_norm_stderr\": 0.04206739313864908\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.6694214876033058,\n \"acc_stderr\": 0.04294340845212094,\n \"\ acc_norm\": 0.6694214876033058,\n \"acc_norm_stderr\": 0.04294340845212094\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.6574074074074074,\n\ \ \"acc_stderr\": 0.04587904741301809,\n \"acc_norm\": 0.6574074074074074,\n\ \ \"acc_norm_stderr\": 0.04587904741301809\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.6441717791411042,\n \"acc_stderr\": 0.03761521380046734,\n\ \ \"acc_norm\": 0.6441717791411042,\n \"acc_norm_stderr\": 0.03761521380046734\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.4732142857142857,\n\ \ \"acc_stderr\": 0.047389751192741546,\n \"acc_norm\": 0.4732142857142857,\n\ \ \"acc_norm_stderr\": 0.047389751192741546\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.6796116504854369,\n \"acc_stderr\": 0.04620284082280041,\n\ \ \"acc_norm\": 0.6796116504854369,\n \"acc_norm_stderr\": 0.04620284082280041\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8290598290598291,\n\ \ \"acc_stderr\": 0.024662496845209818,\n \"acc_norm\": 0.8290598290598291,\n\ \ \"acc_norm_stderr\": 0.024662496845209818\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.66,\n \"acc_stderr\": 0.04760952285695237,\n \ \ \"acc_norm\": 0.66,\n \"acc_norm_stderr\": 0.04760952285695237\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.7445721583652618,\n\ \ \"acc_stderr\": 0.015594955384455773,\n \"acc_norm\": 0.7445721583652618,\n\ \ \"acc_norm_stderr\": 0.015594955384455773\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.5780346820809249,\n \"acc_stderr\": 0.02658923114217426,\n\ \ \"acc_norm\": 0.5780346820809249,\n \"acc_norm_stderr\": 0.02658923114217426\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.2212290502793296,\n\ \ \"acc_stderr\": 0.01388216459888727,\n \"acc_norm\": 0.2212290502793296,\n\ \ \"acc_norm_stderr\": 0.01388216459888727\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.5849673202614379,\n \"acc_stderr\": 0.028213504177824096,\n\ \ \"acc_norm\": 0.5849673202614379,\n \"acc_norm_stderr\": 0.028213504177824096\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.6045016077170418,\n\ \ \"acc_stderr\": 0.02777091853142784,\n \"acc_norm\": 0.6045016077170418,\n\ \ \"acc_norm_stderr\": 0.02777091853142784\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.5925925925925926,\n \"acc_stderr\": 0.02733954664066273,\n\ \ \"acc_norm\": 0.5925925925925926,\n \"acc_norm_stderr\": 0.02733954664066273\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.40070921985815605,\n \"acc_stderr\": 0.029233465745573086,\n \ \ \"acc_norm\": 0.40070921985815605,\n \"acc_norm_stderr\": 0.029233465745573086\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.40547588005215124,\n\ \ \"acc_stderr\": 0.012539960672377204,\n \"acc_norm\": 0.40547588005215124,\n\ \ \"acc_norm_stderr\": 0.012539960672377204\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.5514705882352942,\n \"acc_stderr\": 0.0302114796091216,\n\ \ \"acc_norm\": 0.5514705882352942,\n \"acc_norm_stderr\": 0.0302114796091216\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.5326797385620915,\n \"acc_stderr\": 0.020184583359102202,\n \ \ \"acc_norm\": 0.5326797385620915,\n \"acc_norm_stderr\": 0.020184583359102202\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6272727272727273,\n\ \ \"acc_stderr\": 0.04631381319425464,\n \"acc_norm\": 0.6272727272727273,\n\ \ \"acc_norm_stderr\": 0.04631381319425464\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.636734693877551,\n \"acc_stderr\": 0.030789051139030806,\n\ \ \"acc_norm\": 0.636734693877551,\n \"acc_norm_stderr\": 0.030789051139030806\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.7263681592039801,\n\ \ \"acc_stderr\": 0.03152439186555404,\n \"acc_norm\": 0.7263681592039801,\n\ \ \"acc_norm_stderr\": 0.03152439186555404\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.77,\n \"acc_stderr\": 0.04229525846816506,\n \ \ \"acc_norm\": 0.77,\n \"acc_norm_stderr\": 0.04229525846816506\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.42771084337349397,\n\ \ \"acc_stderr\": 0.038515976837185335,\n \"acc_norm\": 0.42771084337349397,\n\ \ \"acc_norm_stderr\": 0.038515976837185335\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.7017543859649122,\n \"acc_stderr\": 0.03508771929824563,\n\ \ \"acc_norm\": 0.7017543859649122,\n \"acc_norm_stderr\": 0.03508771929824563\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.412484700122399,\n\ \ \"mc1_stderr\": 0.01723329939957122,\n \"mc2\": 0.5680735045864234,\n\ \ \"mc2_stderr\": 0.01559042793493668\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7237569060773481,\n \"acc_stderr\": 0.01256681501569816\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.177407126611069,\n \ \ \"acc_stderr\": 0.010522533016890778\n }\n}\n```" repo_url: https://huggingface.co/JunchengXie/Mistral-7B-Instruct-v0.1-gpt-4-80k-base_lora leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|arc:challenge\|25_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-03-27T23-56-07.967023.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|gsm8k\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hellaswag\|10_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-27T23-56-07.967023.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-27T23-56-07.967023.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-03-27T23-56-07.967023.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_27T23_56_07.967023 path: - '/details_harness\|winogrande\|5_2024-03-27T23-56-07.967023.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-03-27T23-56-07.967023.parquet' - config_name: results data_files: - split: 2024_03_27T23_56_07.967023 path: - results_2024-03-27T23-56-07.967023.parquet - split: latest path: - results_2024-03-27T23-56-07.967023.parquet --- # Dataset Card for Evaluation run of JunchengXie/Mistral-7B-Instruct-v0.1-gpt-4-80k-base_lora <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [JunchengXie/Mistral-7B-Instruct-v0.1-gpt-4-80k-base_lora](https://huggingface.co/JunchengXie/Mistral-7B-Instruct-v0.1-gpt-4-80k-base_lora) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_JunchengXie__Mistral-7B-Instruct-v0.1-gpt-4-80k-base_lora", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-27T23:56:07.967023](https://huggingface.co/datasets/open-llm-leaderboard/details_JunchengXie__Mistral-7B-Instruct-v0.1-gpt-4-80k-base_lora/blob/main/results_2024-03-27T23-56-07.967023.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": 0.5452277178528238, "acc_stderr": 0.03410493442579154, "acc_norm": 0.5519072949752738, "acc_norm_stderr": 0.03485960483749285, "mc1": 0.412484700122399, "mc1_stderr": 0.01723329939957122, "mc2": 0.5680735045864234, "mc2_stderr": 0.01559042793493668 }, "harness\|arc:challenge\|25": { "acc": 0.5162116040955631, "acc_stderr": 0.014603708567414945, "acc_norm": 0.5366894197952219, "acc_norm_stderr": 0.01457200052775699 }, "harness\|hellaswag\|10": { "acc": 0.5514837681736706, "acc_stderr": 0.004963259311700565, "acc_norm": 0.7358095996813384, "acc_norm_stderr": 0.004400000822742066 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.4444444444444444, "acc_stderr": 0.04292596718256981, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.04292596718256981 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.5460526315789473, "acc_stderr": 0.04051646342874141, "acc_norm": 0.5460526315789473, "acc_norm_stderr": 0.04051646342874141 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.569811320754717, "acc_stderr": 0.030471445867183235, "acc_norm": 0.569811320754717, "acc_norm_stderr": 0.030471445867183235 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.6319444444444444, "acc_stderr": 0.040329990539607195, "acc_norm": 0.6319444444444444, "acc_norm_stderr": 0.040329990539607195 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.42, "acc_stderr": 0.04960449637488584, "acc_norm": 0.42, "acc_norm_stderr": 0.04960449637488584 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.5260115606936416, "acc_stderr": 0.03807301726504513, "acc_norm": 0.5260115606936416, "acc_norm_stderr": 0.03807301726504513 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.28431372549019607, "acc_stderr": 0.04488482852329017, "acc_norm": 0.28431372549019607, "acc_norm_stderr": 0.04488482852329017 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.71, "acc_stderr": 0.045604802157206845, "acc_norm": 0.71, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.4808510638297872, "acc_stderr": 0.03266204299064678, "acc_norm": 0.4808510638297872, "acc_norm_stderr": 0.03266204299064678 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.35964912280701755, "acc_stderr": 0.04514496132873633, "acc_norm": 0.35964912280701755, "acc_norm_stderr": 0.04514496132873633 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5241379310344828, "acc_stderr": 0.0416180850350153, "acc_norm": 0.5241379310344828, "acc_norm_stderr": 0.0416180850350153 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.35714285714285715, "acc_stderr": 0.024677862841332786, "acc_norm": 0.35714285714285715, "acc_norm_stderr": 0.024677862841332786 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.3888888888888889, "acc_stderr": 0.04360314860077459, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.04360314860077459 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.6451612903225806, "acc_stderr": 0.027218889773308753, "acc_norm": 0.6451612903225806, "acc_norm_stderr": 0.027218889773308753 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.3891625615763547, "acc_stderr": 0.034304624161038716, "acc_norm": 0.3891625615763547, "acc_norm_stderr": 0.034304624161038716 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.6787878787878788, "acc_stderr": 0.0364620496325381, "acc_norm": 0.6787878787878788, "acc_norm_stderr": 0.0364620496325381 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7121212121212122, "acc_stderr": 0.03225883512300992, "acc_norm": 0.7121212121212122, "acc_norm_stderr": 0.03225883512300992 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.7357512953367875, "acc_stderr": 0.03182155050916645, "acc_norm": 0.7357512953367875, "acc_norm_stderr": 0.03182155050916645 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.5128205128205128, "acc_stderr": 0.02534267129380725, "acc_norm": 0.5128205128205128, "acc_norm_stderr": 0.02534267129380725 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.2962962962962963, "acc_stderr": 0.027840811495871916, "acc_norm": 0.2962962962962963, "acc_norm_stderr": 0.027840811495871916 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.5252100840336135, "acc_stderr": 0.03243718055137411, "acc_norm": 0.5252100840336135, "acc_norm_stderr": 0.03243718055137411 }, "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": 0.7137614678899082, "acc_stderr": 0.01937943662892, "acc_norm": 0.7137614678899082, "acc_norm_stderr": 0.01937943662892 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.4166666666666667, "acc_stderr": 0.03362277436608044, "acc_norm": 0.4166666666666667, "acc_norm_stderr": 0.03362277436608044 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.7107843137254902, "acc_stderr": 0.031822318676475544, "acc_norm": 0.7107843137254902, "acc_norm_stderr": 0.031822318676475544 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7088607594936709, "acc_stderr": 0.02957160106575337, "acc_norm": 0.7088607594936709, "acc_norm_stderr": 0.02957160106575337 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6502242152466368, "acc_stderr": 0.03200736719484503, "acc_norm": 0.6502242152466368, "acc_norm_stderr": 0.03200736719484503 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.6412213740458015, "acc_stderr": 0.04206739313864908, "acc_norm": 0.6412213740458015, "acc_norm_stderr": 0.04206739313864908 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.6694214876033058, "acc_stderr": 0.04294340845212094, "acc_norm": 0.6694214876033058, "acc_norm_stderr": 0.04294340845212094 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.6574074074074074, "acc_stderr": 0.04587904741301809, "acc_norm": 0.6574074074074074, "acc_norm_stderr": 0.04587904741301809 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.6441717791411042, "acc_stderr": 0.03761521380046734, "acc_norm": 0.6441717791411042, "acc_norm_stderr": 0.03761521380046734 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.4732142857142857, "acc_stderr": 0.047389751192741546, "acc_norm": 0.4732142857142857, "acc_norm_stderr": 0.047389751192741546 }, "harness\|hendrycksTest-management\|5": { "acc": 0.6796116504854369, "acc_stderr": 0.04620284082280041, "acc_norm": 0.6796116504854369, "acc_norm_stderr": 0.04620284082280041 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8290598290598291, "acc_stderr": 0.024662496845209818, "acc_norm": 0.8290598290598291, "acc_norm_stderr": 0.024662496845209818 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.7445721583652618, "acc_stderr": 0.015594955384455773, "acc_norm": 0.7445721583652618, "acc_norm_stderr": 0.015594955384455773 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.5780346820809249, "acc_stderr": 0.02658923114217426, "acc_norm": 0.5780346820809249, "acc_norm_stderr": 0.02658923114217426 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.2212290502793296, "acc_stderr": 0.01388216459888727, "acc_norm": 0.2212290502793296, "acc_norm_stderr": 0.01388216459888727 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.5849673202614379, "acc_stderr": 0.028213504177824096, "acc_norm": 0.5849673202614379, "acc_norm_stderr": 0.028213504177824096 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.6045016077170418, "acc_stderr": 0.02777091853142784, "acc_norm": 0.6045016077170418, "acc_norm_stderr": 0.02777091853142784 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.5925925925925926, "acc_stderr": 0.02733954664066273, "acc_norm": 0.5925925925925926, "acc_norm_stderr": 0.02733954664066273 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.40070921985815605, "acc_stderr": 0.029233465745573086, "acc_norm": 0.40070921985815605, "acc_norm_stderr": 0.029233465745573086 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.40547588005215124, "acc_stderr": 0.012539960672377204, "acc_norm": 0.40547588005215124, "acc_norm_stderr": 0.012539960672377204 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.5514705882352942, "acc_stderr": 0.0302114796091216, "acc_norm": 0.5514705882352942, "acc_norm_stderr": 0.0302114796091216 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.5326797385620915, "acc_stderr": 0.020184583359102202, "acc_norm": 0.5326797385620915, "acc_norm_stderr": 0.020184583359102202 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6272727272727273, "acc_stderr": 0.04631381319425464, "acc_norm": 0.6272727272727273, "acc_norm_stderr": 0.04631381319425464 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.636734693877551, "acc_stderr": 0.030789051139030806, "acc_norm": 0.636734693877551, "acc_norm_stderr": 0.030789051139030806 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.7263681592039801, "acc_stderr": 0.03152439186555404, "acc_norm": 0.7263681592039801, "acc_norm_stderr": 0.03152439186555404 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.77, "acc_stderr": 0.04229525846816506, "acc_norm": 0.77, "acc_norm_stderr": 0.04229525846816506 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.42771084337349397, "acc_stderr": 0.038515976837185335, "acc_norm": 0.42771084337349397, "acc_norm_stderr": 0.038515976837185335 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.7017543859649122, "acc_stderr": 0.03508771929824563, "acc_norm": 0.7017543859649122, "acc_norm_stderr": 0.03508771929824563 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.412484700122399, "mc1_stderr": 0.01723329939957122, "mc2": 0.5680735045864234, "mc2_stderr": 0.01559042793493668 }, "harness\|winogrande\|5": { "acc": 0.7237569060773481, "acc_stderr": 0.01256681501569816 }, "harness\|gsm8k\|5": { "acc": 0.177407126611069, "acc_stderr": 0.010522533016890778 } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - Curated by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

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