davanstrien/summary-test · Datasets at Hugging Face

datasetId stringlengths 2 117	card stringlengths 19 1.01M
louisbrulenaudet/tax-fr	--- license: apache-2.0 language: - fr multilinguality: - monolingual tags: - instruction-finetuning - legal - tax - llm - fiscal source_datasets: - original pretty_name: >- Instruction fine-tuning Large Language Models for tax practice using quantization and LoRA: a boilerplate task_categories: - text-generation - table-question-answering - summarization - conversational size_categories: - n<1K --- # Instruction fine-tuning Large Language Models for tax practice using quantization and LoRA: a boilerplate This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice. Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the model's parameters through a further round of training on task-specific or domain-specific data. While conventional fine-tuning strategies involve supervised learning with labeled data, instruction-based fine-tuning introduces a more structured and interpretable approach. Instruction-based fine-tuning leverages the power of human-provided instructions to guide the model's behavior. These instructions can be in the form of text prompts, prompts with explicit task descriptions, or a combination of both. This approach allows for a more controlled and context-aware interaction with the LLM, making it adaptable to a multitude of specialized tasks. Instruction-based fine-tuning significantly enhances the performance of LLMs in the following ways: - Task-Specific Adaptation: LLMs, when fine-tuned with specific instructions, exhibit remarkable adaptability to diverse tasks. They can switch seamlessly between translation, summarization, and question-answering, guided by the provided instructions. - Reduced Ambiguity: Traditional LLMs might generate ambiguous or contextually inappropriate responses. Instruction-based fine-tuning allows for a clearer and more context-aware generation, reducing the likelihood of nonsensical outputs. - Efficient Knowledge Transfer: Instructions can encapsulate domain-specific knowledge, enabling LLMs to benefit from expert guidance. This knowledge transfer is particularly valuable in fields like tax practice, law, medicine, and more. - Interpretability: Instruction-based fine-tuning also makes LLM behavior more interpretable. Since the instructions are human-readable, it becomes easier to understand and control model outputs. - Adaptive Behavior: LLMs, post instruction-based fine-tuning, exhibit adaptive behavior that is responsive to both explicit task descriptions and implicit cues within the provided text. ## Dataset generation This JSON file is a list of dictionaries, each dictionary contains the following fields: - `instruction`: `str`, describes the task the model should perform. Each of the instructions is unique. - `input`: `str`, optional context or input for the task. - `output`: `str`, the answer to the instruction. We used the following prompt for generating the dataset: ``` Objectif : Élaboration d'un ensemble de 5-10 problématiques ou instructions diverses dans un fichier JSON à destination d'un modèle de langage pour un objectif d'entrainement (fine-tuning) aux fins d'assistance du métier de fiscaliste. Schéma de la liste de dictionnaires souhaitée : [ { "instruction" :"xxx", "input" : "xxx", "output" : "xxx" } ] Exigences à respecter : 1. Élimination de la répétition et utilisation de structures de phrases élaborées. Éviter toute redondance de contenu dans les phrases successives tout en favorisant l'utilisation de structures de phrases complexes qui élargissent la portée de l'expression. 2. Diversité linguistique des instructions. Les directives doivent être formulées de manière variée, en combinant des questions avec des instructions impératives. 3. Variété des types d'instructions. Les types d'instructions doivent être variés, couvrant une gamme de tâches propres à l'activité de fiscaliste, telles que la génération de questions ouvertes, la classification, etc. 4. Qualité linguistique. Les instructions, les entrées et les sorties doivent être rédigées en français sans aucune faute d'orthographe, de syntaxe, de ponctuation ou de grammaire. 5. Langage professionnel et académique. Les instructions, les entrées et les sorties doivent être reformulées pour adopter un discours professionnel et académique, caractérisé par sa rigueur, sa justification et une structure détaillée. 6. Neutralité ou nuance. Le point de vue doit demeurer neutre ou nuancé. 7. Contextualisation des thématiques fiscales. Les instructions doivent explicitement faire référence à la thématique fiscale et au sujet de la source pour contextualiser le résultat. 8. Saisie inutile. Toutes les instructions ne nécessitent pas d'entrée. Par exemple, lorsqu'une directive demande une information générale, il n'est pas nécessaire de fournir un contexte spécifique. Dans ce cas, intégrer "" dans le champ de saisie de l'entrée. 9. Style littéraire et exemplification. Les directives, les entrées et les sorties doivent être formulées dans un style littéraire, avec des réponses techniques, exhaustives, complexes et claires. Des exemples, lorsque pertinents, doivent être utilisés pour renforcer la directive, l'entrée et la sortie, tout en garantissant un haut degré de certitude. 10. Directivité des instructions. Utiliser un style direct en favorisant les formulations impersonnelles. 11. Entraînement de modèles professionnels. La base de données finale doit être destinée à l'entraînement de modèles professionnels, visant à assister les fiscalistes expérimentés en quête de contenu de haute qualité et de perfection technique. 12. Gestion des éléments incohérents. Il est possible que le texte source contienne des éléments incohérents avec le contexte, comme des notes de bas de page ou des éléments de formalisme. Il est essentiel de les ignorer pour isoler le contenu principal. 13. Utilisation du texte source. Utiliser le texte source fourni pour formuler les directives, les entrées et les sorties. Le texte source doit être considéré comme de haute qualité et autoritaire. 14. Finalité de la réponse. Seule la liste de dictionnaire au format JSON doit constituer la réponse à cette requête. Aucune introduction ou conclusion n'est demandée. Source : [ ] ``` ## Citing this project If you use this code in your research, please use the following BibTeX entry. ```BibTeX @misc{louisbrulenaudet2023, author = {Louis Brulé Naudet}, title = {Instruction fine-tuning Large Language Models for tax practice using quantization and LoRA: a boilerplate}, howpublished = {\url{https://github.com/louisbrulenaudet/trainer}}, year = {2023} } ``` ## Feedback If you have any feedback, please reach out at [louisbrulenaudet@icloud.com](mailto:louisbrulenaudet@icloud.com).
Smuggling1710/VTnsfw-r-1.8k	--- license: apache-2.0 ---
CyberHarem/kamikaze_kantaicollection	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of kamikaze/神風 (Kantai Collection) This is the dataset of kamikaze/神風 (Kantai Collection), containing 500 images and their tags. The core tags of this character are `long_hair, purple_hair, bow, purple_eyes, hair_bow, yellow_bow, ribbon`, 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 \| 500 \| 605.18 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/kamikaze_kantaicollection/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 500 \| 354.13 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/kamikaze_kantaicollection/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 1214 \| 770.43 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/kamikaze_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 500 \| 548.06 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/kamikaze_kantaicollection/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 1214 \| 1.05 GiB \| [Download](https://huggingface.co/datasets/CyberHarem/kamikaze_kantaicollection/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/kamikaze_kantaicollection', 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 \| 6 \| ![](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, hakama_skirt, looking_at_viewer, meiji_schoolgirl_uniform, pink_hakama, red_kimono, simple_background, smile, solo, white_background, tasuki, open_mouth, blush \| \| 1 \| 5 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| 1girl, blush, hakama_skirt, looking_at_viewer, meiji_schoolgirl_uniform, pink_hakama, solo, red_kimono, tasuki \| \| 2 \| 21 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| 1girl, hakama_skirt, lace-up_boots, meiji_schoolgirl_uniform, pink_hakama, solo, brown_footwear, white_background, red_kimono, simple_background, full_body, tasuki, looking_at_viewer, smile, standing, sitting \| \| 3 \| 5 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| 1girl, hakama_skirt, holding_sword, katana, kimono, meiji_schoolgirl_uniform, pink_hakama, solo, looking_at_viewer, tasuki, unsheathing, open_mouth \| \| 4 \| 5 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| 1girl, brown_footwear, frilled_apron, gift, hair_flower, hakama_skirt, maid_headdress, meiji_schoolgirl_uniform, open_mouth, pink_hakama, red_kimono, solo, tube, wa_maid, white_apron, full_body, lace-up_boots, smile, looking_at_viewer, simple_background, white_background, upper_teeth_only \| \| 5 \| 7 \| ![](samples/5/clu5-sample0.png) \| ![](samples/5/clu5-sample1.png) \| ![](samples/5/clu5-sample2.png) \| ![](samples/5/clu5-sample3.png) \| ![](samples/5/clu5-sample4.png) \| 1girl, frilled_apron, hair_flower, hakama_skirt, looking_at_viewer, maid_headdress, pink_hakama, red_kimono, solo, wa_maid, white_apron, maid_apron, meiji_schoolgirl_uniform, cowboy_shot, heart, open_mouth, white_background, :d, blush, dated, one-hour_drawing_challenge, simple_background \| \| 6 \| 9 \| ![](samples/6/clu6-sample0.png) \| ![](samples/6/clu6-sample1.png) \| ![](samples/6/clu6-sample2.png) \| ![](samples/6/clu6-sample3.png) \| ![](samples/6/clu6-sample4.png) \| 1boy, 1girl, hetero, kimono, nipples, sex, solo_focus, vaginal, blush, open_mouth, penis, censored, small_breasts, navel, cowgirl_position, cum_in_pussy, girl_on_top, hakama_skirt, medium_breasts, meiji_schoolgirl_uniform, open_clothes, pink_hakama \| \| 7 \| 5 \| ![](samples/7/clu7-sample0.png) \| ![](samples/7/clu7-sample1.png) \| ![](samples/7/clu7-sample2.png) \| ![](samples/7/clu7-sample3.png) \| ![](samples/7/clu7-sample4.png) \| 1girl, detached_collar, fake_animal_ears, looking_at_viewer, playboy_bunny, rabbit_ears, solo, strapless_leotard, cowboy_shot, open_mouth, red_leotard, white_background, wrist_cuffs, yellow_ribbon, alternate_costume, black_pantyhose, brown_pantyhose, simple_background, small_breasts, smile, covered_navel, highleg, pink_bowtie, pink_leotard, red_bowtie, yellow_bowtie \| \| 8 \| 6 \| ![](samples/8/clu8-sample0.png) \| ![](samples/8/clu8-sample1.png) \| ![](samples/8/clu8-sample2.png) \| ![](samples/8/clu8-sample3.png) \| ![](samples/8/clu8-sample4.png) \| 1girl, cowboy_shot, school_uniform, solo, white_shirt, alternate_costume, long_sleeves, looking_at_viewer, pleated_skirt, yellow_ribbon, blush, collared_shirt, simple_background, smile, white_background, blue_skirt, hair_ribbon, one-hour_drawing_challenge, twitter_username \| \| 9 \| 8 \| ![](samples/9/clu9-sample0.png) \| ![](samples/9/clu9-sample1.png) \| ![](samples/9/clu9-sample2.png) \| ![](samples/9/clu9-sample3.png) \| ![](samples/9/clu9-sample4.png) \| 1girl, alternate_costume, looking_at_viewer, open_mouth, solo, blush, :d, frills, white_background, white_dress, yellow_ribbon, bare_shoulders, holding, long_sleeves, simple_background \| \| 10 \| 5 \| ![](samples/10/clu10-sample0.png) \| ![](samples/10/clu10-sample1.png) \| ![](samples/10/clu10-sample2.png) \| ![](samples/10/clu10-sample3.png) \| ![](samples/10/clu10-sample4.png) \| 1girl, alternate_costume, pleated_skirt, solo, looking_at_viewer, serafuku, yellow_ribbon, black_skirt, hair_ornament, hair_ribbon, indoors, red_neckerchief, red_skirt, sailor_collar, school_bag \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| hakama_skirt \| looking_at_viewer \| meiji_schoolgirl_uniform \| pink_hakama \| red_kimono \| simple_background \| smile \| solo \| white_background \| tasuki \| open_mouth \| blush \| lace-up_boots \| brown_footwear \| full_body \| standing \| sitting \| holding_sword \| katana \| kimono \| unsheathing \| frilled_apron \| gift \| hair_flower \| maid_headdress \| tube \| wa_maid \| white_apron \| upper_teeth_only \| maid_apron \| cowboy_shot \| heart \| :d \| dated \| one-hour_drawing_challenge \| 1boy \| hetero \| nipples \| sex \| solo_focus \| vaginal \| penis \| censored \| small_breasts \| navel \| cowgirl_position \| cum_in_pussy \| girl_on_top \| medium_breasts \| open_clothes \| detached_collar \| fake_animal_ears \| playboy_bunny \| rabbit_ears \| strapless_leotard \| red_leotard \| wrist_cuffs \| yellow_ribbon \| alternate_costume \| black_pantyhose \| brown_pantyhose \| covered_navel \| highleg \| pink_bowtie \| pink_leotard \| red_bowtie \| yellow_bowtie \| school_uniform \| white_shirt \| long_sleeves \| pleated_skirt \| collared_shirt \| blue_skirt \| hair_ribbon \| twitter_username \| frills \| white_dress \| bare_shoulders \| holding \| serafuku \| black_skirt \| hair_ornament \| indoors \| red_neckerchief \| red_skirt \| sailor_collar \| school_bag \| \|----:\|----------:\|:----------------------------------\|:----------------------------------\|:----------------------------------\|:----------------------------------\|:----------------------------------\|:--------\|:---------------\|:--------------------\|:---------------------------\|:--------------\|:-------------\|:--------------------\|:--------\|:-------\|:-------------------\|:---------\|:-------------\|:--------\|:----------------\|:-----------------\|:------------\|:-----------\|:----------\|:----------------\|:---------\|:---------\|:--------------\|:----------------\|:-------\|:--------------\|:-----------------\|:-------\|:----------\|:--------------\|:-------------------\|:-------------\|:--------------\|:--------\|:-----\|:--------\|:-----------------------------\|:-------\|:---------\|:----------\|:------\|:-------------\|:----------\|:--------\|:-----------\|:----------------\|:--------\|:-------------------\|:---------------\|:--------------\|:-----------------\|:---------------\|:------------------\|:-------------------\|:----------------\|:--------------\|:--------------------\|:--------------\|:--------------\|:----------------\|:--------------------\|:------------------\|:------------------\|:----------------\|:----------\|:--------------\|:---------------\|:-------------\|:----------------\|:-----------------\|:--------------\|:---------------\|:----------------\|:-----------------\|:-------------\|:--------------\|:-------------------\|:---------\|:--------------\|:-----------------\|:----------\|:-----------\|:--------------\|:----------------\|:----------\|:------------------\|:------------\|:----------------\|:-------------\| \| 0 \| 6 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 5 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 21 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 3 \| 5 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| X \| X \| X \| X \| X \| \| \| \| X \| \| X \| X \| \| \| \| \| \| \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 4 \| 5 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| X \| \| X \| X \| X \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 5 \| 7 \| ![](samples/5/clu5-sample0.png) \| ![](samples/5/clu5-sample1.png) \| ![](samples/5/clu5-sample2.png) \| ![](samples/5/clu5-sample3.png) \| ![](samples/5/clu5-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| \| X \| X \| \| X \| X \| \| \| \| \| \| \| \| \| \| X \| \| X \| X \| \| X \| X \| \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 6 \| 9 \| ![](samples/6/clu6-sample0.png) \| ![](samples/6/clu6-sample1.png) \| ![](samples/6/clu6-sample2.png) \| ![](samples/6/clu6-sample3.png) \| ![](samples/6/clu6-sample4.png) \| X \| X \| \| X \| X \| \| \| \| \| \| \| X \| X \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 7 \| 5 \| ![](samples/7/clu7-sample0.png) \| ![](samples/7/clu7-sample1.png) \| ![](samples/7/clu7-sample2.png) \| ![](samples/7/clu7-sample3.png) \| ![](samples/7/clu7-sample4.png) \| X \| \| X \| \| \| \| X \| X \| X \| X \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 8 \| 6 \| ![](samples/8/clu8-sample0.png) \| ![](samples/8/clu8-sample1.png) \| ![](samples/8/clu8-sample2.png) \| ![](samples/8/clu8-sample3.png) \| ![](samples/8/clu8-sample4.png) \| X \| \| X \| \| \| \| X \| X \| X \| X \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| \| \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| 9 \| 8 \| ![](samples/9/clu9-sample0.png) \| ![](samples/9/clu9-sample1.png) \| ![](samples/9/clu9-sample2.png) \| ![](samples/9/clu9-sample3.png) \| ![](samples/9/clu9-sample4.png) \| X \| \| X \| \| \| \| X \| \| X \| X \| \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| \| \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| 10 \| 5 \| ![](samples/10/clu10-sample0.png) \| ![](samples/10/clu10-sample1.png) \| ![](samples/10/clu10-sample2.png) \| ![](samples/10/clu10-sample3.png) \| ![](samples/10/clu10-sample4.png) \| X \| \| X \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| X \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \|
deberain/ChatGPT-Tweets	--- dataset_info: features: - name: Date dtype: string - name: Tweet dtype: string - name: Url dtype: string - name: User dtype: string - name: UserCreated dtype: string - name: UserVerified dtype: string - name: UserFollowers dtype: string - name: UserFriends dtype: string - name: Retweets dtype: string - name: Likes dtype: string - name: Location dtype: string - name: UserDescription dtype: string splits: - name: train num_bytes: 143971145 num_examples: 305432 download_size: 81419852 dataset_size: 143971145 --- # Dataset Card for "ChatGPT-Tweets" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Back-up/merge-stock-part-1-v2	--- dataset_info: features: - name: title dtype: string - name: url dtype: string - name: date dtype: string - name: view struct: - name: number_of_response dtype: string - name: number_of_view dtype: string - name: content list: - name: date_comment dtype: string - name: res dtype: string - name: d struct: - name: 01/01/2016 dtype: int64 - name: 01/01/2020 dtype: int64 - name: 01/01/2021 dtype: int64 - name: 01/01/2022 dtype: int64 - name: 01/01/2023 dtype: int64 - name: 01/01/2024 dtype: int64 - name: 01/02/2009 dtype: int64 - name: 01/02/2010 dtype: int64 - name: 01/02/2016 dtype: int64 - name: 01/02/2017 dtype: int64 - name: 01/02/2018 dtype: int64 - name: 01/02/2020 dtype: int64 - name: 01/02/2021 dtype: int64 - name: 01/02/2022 dtype: int64 - name: 01/02/2023 dtype: int64 - name: 01/03/2008 dtype: int64 - name: 01/03/2010 dtype: int64 - name: 01/03/2016 dtype: int64 - name: 01/03/2018 dtype: int64 - name: 01/03/2019 dtype: int64 - name: 01/03/2020 dtype: int64 - 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name: 31/03/2012 dtype: int64 - name: 31/03/2016 dtype: int64 - name: 31/03/2017 dtype: int64 - name: 31/03/2019 dtype: int64 - name: 31/03/2020 dtype: int64 - name: 31/03/2021 dtype: int64 - name: 31/03/2022 dtype: int64 - name: 31/03/2023 dtype: int64 - name: 31/05/2016 dtype: int64 - name: 31/05/2017 dtype: int64 - name: 31/05/2018 dtype: int64 - name: 31/05/2019 dtype: int64 - name: 31/05/2020 dtype: int64 - name: 31/05/2021 dtype: int64 - name: 31/05/2022 dtype: int64 - name: 31/05/2023 dtype: int64 - name: 31/07/2008 dtype: int64 - name: 31/07/2016 dtype: int64 - name: 31/07/2017 dtype: int64 - name: 31/07/2018 dtype: int64 - name: 31/07/2019 dtype: int64 - name: 31/07/2020 dtype: int64 - name: 31/07/2021 dtype: int64 - name: 31/07/2022 dtype: int64 - name: 31/07/2023 dtype: int64 - name: 31/08/2009 dtype: int64 - name: 31/08/2017 dtype: int64 - name: 31/08/2018 dtype: int64 - name: 31/08/2019 dtype: int64 - name: 31/08/2020 dtype: int64 - name: 31/08/2021 dtype: int64 - name: 31/08/2022 dtype: int64 - name: 31/08/2023 dtype: int64 - name: 31/10/2008 dtype: int64 - name: 31/10/2017 dtype: int64 - name: 31/10/2018 dtype: int64 - name: 31/10/2019 dtype: int64 - name: 31/10/2020 dtype: int64 - name: 31/10/2021 dtype: int64 - name: 31/10/2022 dtype: int64 - name: 31/10/2023 dtype: int64 - name: 31/12/2007 dtype: int64 - name: 31/12/2015 dtype: int64 - name: 31/12/2017 dtype: int64 - name: 31/12/2018 dtype: int64 - name: 31/12/2019 dtype: int64 - name: 31/12/2020 dtype: int64 - name: 31/12/2021 dtype: int64 - name: 31/12/2022 dtype: int64 - name: 31/12/2023 dtype: int64 splits: - name: train num_bytes: 596396375 num_examples: 5144 download_size: 174754628 dataset_size: 596396375 configs: - config_name: default data_files: - split: train path: data/train-* ---
DataStudio/OCRWordLevelClear_04	--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 32994104944.528 num_examples: 6777332 download_size: 32267197160 dataset_size: 32994104944.528 configs: - config_name: default data_files: - split: train path: data/train-* ---
AdapterOcean/chemistry_dataset_standardized_cluster_0_alpaca	--- dataset_info: features: - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 14675587 num_examples: 5546 download_size: 6391991 dataset_size: 14675587 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "chemistry_dataset_standardized_cluster_0_alpaca" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
amphora/rewrite-se-quant-alp	--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 31370080 num_examples: 11013 download_size: 16594547 dataset_size: 31370080 configs: - config_name: default data_files: - split: train path: data/train-* ---
shape-ai/beaches	--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 1566551.0 num_examples: 1 download_size: 1568255 dataset_size: 1566551.0 --- # Dataset Card for "beaches" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
autoevaluate/autoeval-staging-eval-project-17e9fcc1-7454805	--- type: predictions tags: - autotrain - evaluation datasets: - ag_news eval_info: task: multi_class_classification model: andi611/distilbert-base-uncased-ner-agnews metrics: [] dataset_name: ag_news dataset_config: default dataset_split: test col_mapping: text: text target: label --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Multi-class Text Classification * Model: andi611/distilbert-base-uncased-ner-agnews * Dataset: ag_news To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model.
CognitiveLab/FS_test	--- dataset_info: features: - name: author dtype: string - name: duration dtype: int64 - name: description dtype: string - name: transcript struct: - name: metadata struct: - name: channels dtype: int64 - name: created dtype: string - name: duration dtype: float64 - name: model_info struct: - name: 30089e05-99d1-4376-b32e-c263170674af struct: - name: arch dtype: string - name: name dtype: string - name: version dtype: string - name: models sequence: string - name: request_id dtype: string - name: sha256 dtype: string - name: summary_info struct: - name: input_tokens dtype: int64 - name: model_uuid dtype: string - name: output_tokens dtype: int64 - name: transaction_key dtype: string - name: warnings dtype: 'null' - name: results struct: - name: channels list: - name: alternatives list: - name: confidence dtype: float64 - name: entities dtype: 'null' - name: paragraphs struct: - name: paragraphs list: - name: end dtype: float64 - name: num_words dtype: float64 - name: sentences list: - name: end dtype: float64 - name: start dtype: float64 - name: text dtype: string - name: speaker dtype: int64 - name: start dtype: float64 - name: transcript dtype: string - name: summaries dtype: 'null' - name: topics list: - name: end_word dtype: float64 - name: start_word dtype: float64 - name: text dtype: string - name: topics list: - name: confidence dtype: float64 - name: topic dtype: string - name: transcript dtype: string - name: translations dtype: 'null' - name: words list: - name: confidence dtype: float64 - name: end dtype: float64 - name: punctuated_word dtype: string - name: speaker dtype: int64 - name: speaker_confidence dtype: float64 - name: start dtype: float64 - name: word dtype: string - name: detected_language dtype: string - name: language_confidence dtype: float64 - name: search dtype: 'null' - name: summary struct: - name: result dtype: string - name: short dtype: string - name: utterances dtype: 'null' - name: audio_path dtype: string - name: link dtype: string - name: title dtype: string - name: views dtype: int64 splits: - name: train num_bytes: 62271386 num_examples: 522 download_size: 22172106 dataset_size: 62271386 configs: - config_name: default data_files: - split: train path: data/train-* ---
mask-distilled-one-sec-cv12/chunk_22	--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1073011700 num_examples: 210725 download_size: 1093912534 dataset_size: 1073011700 --- # Dataset Card for "chunk_22" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Alpaca69B/reviews_appstore_instagram_absa	--- dataset_info: features: - name: title dtype: string - name: content dtype: string - name: category dtype: string - name: aspect dtype: string - name: sentiment dtype: string - name: combined dtype: string - name: text dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1025846.404 num_examples: 346 - name: validation num_bytes: 216435.802 num_examples: 73 - name: test num_bytes: 222365.55 num_examples: 75 download_size: 2608530 dataset_size: 1464647.7559999998 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: validation path: data/validation-* ---
jinaai/fashion-captions-de	--- license: cc-by-4.0 dataset_info: features: - name: text dtype: string - name: image dtype: image splits: - name: train num_bytes: 282285477 num_examples: 10000 - name: test num_bytes: 56612023.875 num_examples: 2001 download_size: 320681179 dataset_size: 338897500.875 task_categories: - text-to-image multilinguality: - monolingual language: - de size_categories: - 1K<n<10K source_datasets: - original pretty_name: Fashion12k DE --- <br><br> <p align="center"> <img src="https://github.com/jina-ai/finetuner/blob/main/docs/_static/finetuner-logo-ani.svg?raw=true" alt="Finetuner logo: Finetuner helps you to create experiments in order to improve embeddings on search tasks. It accompanies you to deliver the last mile of performance-tuning for neural search applications." width="150px"> </p> <p align="center"> <b>The data offered by Jina AI, Finetuner team.</b> </p> ## Summary This dataset is a German-language dataset based on the [Fashion12K](https://github.com/Toloka/Fashion12K_german_queries) dataset, which originally contains both English and German text descriptions for each item. This dataset was used to to finetuner CLIP using the [Finetuner](https://finetuner.jina.ai/) tool. ## Fine-tuning Please refer to our documentation: [Multilingual Text-to-Image Search with MultilingualCLIP](https://finetuner.jina.ai/notebooks/multilingual_text_to_image/) and blog [Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models](https://jina.ai/news/improving-search-quality-non-english-queries-fine-tuned-multilingual-clip-models/) ## Instances Each data point consists of a 'text' and an 'image' field, where the 'text' field describes an item of clothing in German, and the 'image' field contains and image of that item of clothing. ## Fields - 'text': A string describing the item of clothing. - 'image': A `PIL.Image.Image` object containing the image. Note that when accessing the image column: `dataset[0]["image"]` the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. `dataset[0]["image"]` should always be preferred over dataset["image"][0]. ## Splits \| \| train \| test \| \|------------\|-------\|------\| \| # of items \| 10000 \| 2001 \| ## Source Images were sampled from the [Fashion200K dataset](https://github.com/xthan/fashion-200k). ## Annotations Data was annotated using [Toloka](https://toloka.ai/). See their site for more details. ## Licensing Information This work is licensed under a Creative Commons Attribution 4.0 International License. ## Contributors Thanks to contributors from [Jina AI](https://jina.ai) and [Toloka](https://toloka.ai) for adding this dataset.
indicbench/arc_kn	--- dataset_info: - config_name: ARC-Challenge features: - name: answerKey dtype: string - name: choices struct: - name: label sequence: string - name: text sequence: string - name: id dtype: string - name: question dtype: string splits: - name: validation num_bytes: 233068 num_examples: 299 - name: test num_bytes: 904224 num_examples: 1172 download_size: 414164 dataset_size: 1137292 - config_name: default features: - name: _data_files list: - name: filename dtype: string - name: _fingerprint dtype: string - name: _format_columns dtype: 'null' - name: _format_type dtype: 'null' - name: _output_all_columns dtype: bool - name: _split dtype: 'null' splits: - name: validation num_bytes: 54 num_examples: 1 - name: test num_bytes: 54 num_examples: 1 download_size: 6510 dataset_size: 108 configs: - config_name: ARC-Challenge data_files: - split: validation path: ARC-Challenge/validation-* - split: test path: ARC-Challenge/test-* - config_name: default data_files: - split: validation path: data/validation-* - split: test path: data/test-* ---
sobamchan/aclsum	--- license: mit task_categories: - summarization language: - en pretty_name: aclsum size_categories: - n<1K configs: - config_name: abstractive default: true data_files: - split: train path: "abstractive/train.jsonl" - split: validation path: "abstractive/val.jsonl" - split: test path: "abstractive/test.jsonl" - config_name: extractive data_files: - split: train path: "extractive/train.jsonl" - split: validation path: "extractive/val.jsonl" - split: test path: "extractive/test.jsonl" --- # ACLSum: A New Dataset for Aspect-based Summarization of Scientific Publications This repository contains data for our paper "ACLSum: A New Dataset for Aspect-based Summarization of Scientific Publications" and a small utility class to work with it. ## HuggingFace datasets You can also use Huggin Face datasets to load ACLSum ([dataset link](https://huggingface.co/datasets/sobamchan/aclsum)). This would be convenient if you want to train transformer models using our dataset. Just do, ```py from datasets import load_dataset dataset = load_dataset("sobamchan/aclsum", "challenge", split="train") ```
mlfoundations/open_lm_example_data	--- license: mit ---
liuyanchen1015/MULTI_VALUE_mrpc_possessives_belong	--- dataset_info: features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: label dtype: int64 - name: idx dtype: int64 - name: value_score dtype: int64 splits: - name: test num_bytes: 212907 num_examples: 741 - name: train num_bytes: 431892 num_examples: 1493 - name: validation num_bytes: 53815 num_examples: 184 download_size: 454461 dataset_size: 698614 --- # Dataset Card for "MULTI_VALUE_mrpc_possessives_belong" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
charsiu/librispeech_full_frame_labels	--- dataset_info: features: - name: chapter_id dtype: int64 - name: file dtype: string - name: frame_labels sequence: string - name: frame_labels_10ms sequence: string - name: id dtype: string - name: speaker_id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 3303356482 num_examples: 281191 download_size: 219671524 dataset_size: 3303356482 --- # Dataset Card for "librispeech_full_frame_labels" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Iceclear/DIV8K_TrainingSet	--- license: apache-2.0 task_categories: - image-to-image size_categories: - 1K<n<10K --- The training set of [DIV8K](https://competitions.codalab.org/competitions/22217#participate). ## Citation ```bibtex @inproceedings{gu2019div8k, title={Div8k: Diverse 8k resolution image dataset}, author={Gu, Shuhang and Lugmayr, Andreas and Danelljan, Martin and Fritsche, Manuel and Lamour, Julien and Timofte, Radu}, booktitle={ICCVW}, year={2019}, } ```
tyzhu/squad_context_v3_train_30_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: 991636 num_examples: 378 - name: validation num_bytes: 113558 num_examples: 60 download_size: 188469 dataset_size: 1105194 --- # Dataset Card for "squad_context_v3_train_30_eval_10" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CM/codexglue_code2text_javascript	--- dataset_info: features: - name: id dtype: int32 - name: repo dtype: string - name: path dtype: string - name: func_name dtype: string - name: original_string dtype: string - name: language dtype: string - name: code dtype: string - name: code_tokens sequence: string - name: docstring dtype: string - name: docstring_tokens sequence: string - name: sha dtype: string - name: url dtype: string splits: - name: train num_bytes: 160860431 num_examples: 58025 - name: validation num_bytes: 10337344 num_examples: 3885 - name: test num_bytes: 10190713 num_examples: 3291 download_size: 65795549 dataset_size: 181388488 --- # Dataset Card for "codexglue_code2text_javascript" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
galman33/gal_yair_8300_100x100_fixed	--- dataset_info: features: - name: lat dtype: float64 - name: lon dtype: float64 - name: country_code dtype: class_label: names: '0': ad '1': ae '2': al '3': aq '4': ar '5': au '6': bd '7': be '8': bg '9': bm '10': bo '11': br '12': bt '13': bw '14': ca '15': ch '16': cl '17': co '18': cz '19': de '20': dk '21': ec '22': ee '23': es '24': fi '25': fr '26': gb '27': gh '28': gl '29': gr '30': gt '31': hk '32': hr '33': hu '34': id '35': ie '36': il '37': is '38': it '39': ix '40': jp '41': kg '42': kh '43': kr '44': la '45': lk '46': ls '47': lt '48': lu '49': lv '50': me '51': mg '52': mk '53': mn '54': mo '55': mt '56': mx '57': my '58': nl '59': 'no' '60': nz '61': pe '62': ph '63': pl '64': pt '65': ro '66': rs '67': ru '68': se '69': sg '70': si '71': sk '72': sn '73': sz '74': th '75': tn '76': tr '77': tw '78': ua '79': ug '80': us '81': uy '82': za - name: image dtype: image splits: - name: train num_bytes: 142019429.5 num_examples: 8300 download_size: 141877783 dataset_size: 142019429.5 --- # Dataset Card for "gal_yair_8300_100x100_fixed" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
ibupari/hitobrot	--- dataset_info: features: - name: title dtype: string - name: subtitle dtype: string - name: paragraph dtype: string - name: sentences dtype: string splits: - name: train num_bytes: 1324745 num_examples: 1000 download_size: 264663 dataset_size: 1324745 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_lgaalves__tinyllama-1.1b-chat-v0.3_platypus	--- pretty_name: Evaluation run of lgaalves/tinyllama-1.1b-chat-v0.3_platypus dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [lgaalves/tinyllama-1.1b-chat-v0.3_platypus](https://huggingface.co/lgaalves/tinyllama-1.1b-chat-v0.3_platypus)\ \ 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_lgaalves__tinyllama-1.1b-chat-v0.3_platypus\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-23T23:05:04.270048](https://huggingface.co/datasets/open-llm-leaderboard/details_lgaalves__tinyllama-1.1b-chat-v0.3_platypus/blob/main/results_2023-10-23T23-05-04.270048.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\": 0.0025167785234899327,\n\ \ \"em_stderr\": 0.0005131152834514911,\n \"f1\": 0.049414848993288615,\n\ \ \"f1_stderr\": 0.0012773102707031435,\n \"acc\": 0.2816590502599073,\n\ \ \"acc_stderr\": 0.00797944490002852\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.0025167785234899327,\n \"em_stderr\": 0.0005131152834514911,\n\ \ \"f1\": 0.049414848993288615,\n \"f1_stderr\": 0.0012773102707031435\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.00530705079605762,\n \ \ \"acc_stderr\": 0.002001305720948044\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.5580110497237569,\n \"acc_stderr\": 0.013957584079108994\n\ \ }\n}\n```" repo_url: https://huggingface.co/lgaalves/tinyllama-1.1b-chat-v0.3_platypus 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_10T14_53_56.428911 path: - '/details_harness\|arc:challenge\|25_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-10-10T14-53-56.428911.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_23T23_05_04.270048 path: - '/details_harness\|drop\|3_2023-10-23T23-05-04.270048.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-23T23-05-04.270048.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_23T23_05_04.270048 path: - '/details_harness\|gsm8k\|5_2023-10-23T23-05-04.270048.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-23T23-05-04.270048.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hellaswag\|10_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-10-10T14-53-56.428911.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-management\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_10T14_53_56.428911 path: - '/details_harness\|truthfulqa:mc\|0_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-10-10T14-53-56.428911.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_23T23_05_04.270048 path: - '/details_harness\|winogrande\|5_2023-10-23T23-05-04.270048.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-23T23-05-04.270048.parquet' - config_name: results data_files: - split: 2023_10_10T14_53_56.428911 path: - results_2023-10-10T14-53-56.428911.parquet - split: 2023_10_23T23_05_04.270048 path: - results_2023-10-23T23-05-04.270048.parquet - split: latest path: - results_2023-10-23T23-05-04.270048.parquet --- # Dataset Card for Evaluation run of lgaalves/tinyllama-1.1b-chat-v0.3_platypus ## Dataset Description - Homepage: - Repository: https://huggingface.co/lgaalves/tinyllama-1.1b-chat-v0.3_platypus - 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 [lgaalves/tinyllama-1.1b-chat-v0.3_platypus](https://huggingface.co/lgaalves/tinyllama-1.1b-chat-v0.3_platypus) 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_lgaalves__tinyllama-1.1b-chat-v0.3_platypus", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-23T23:05:04.270048](https://huggingface.co/datasets/open-llm-leaderboard/details_lgaalves__tinyllama-1.1b-chat-v0.3_platypus/blob/main/results_2023-10-23T23-05-04.270048.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": 0.0025167785234899327, "em_stderr": 0.0005131152834514911, "f1": 0.049414848993288615, "f1_stderr": 0.0012773102707031435, "acc": 0.2816590502599073, "acc_stderr": 0.00797944490002852 }, "harness\|drop\|3": { "em": 0.0025167785234899327, "em_stderr": 0.0005131152834514911, "f1": 0.049414848993288615, "f1_stderr": 0.0012773102707031435 }, "harness\|gsm8k\|5": { "acc": 0.00530705079605762, "acc_stderr": 0.002001305720948044 }, "harness\|winogrande\|5": { "acc": 0.5580110497237569, "acc_stderr": 0.013957584079108994 } } ``` ### 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]
CATIE-AQ/wino_x_fr_prompt_coreference	--- language: - fr license: - mit size_categories: - 10K<n<100K tags: - coreference - DFP - french prompts annotations_creators: - found language_creators: - found multilinguality: - monolingual source_datasets: - wino_x --- # wino_x_fr_prompt_coreference ## Summary wino_x_fr_prompt_coreference is a subset of the [Dataset of French Prompts (DFP)](https://huggingface.co/datasets/CATIE-AQ/DFP). It contains 27,930 rows that can be used for a coreference task. The original data (without prompts) comes from the dataset [wino_x](https://huggingface.co/datasets/demelin/wino_x) by Emelin et al. 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: ``` wino_x = load_dataset('demelin/wino_x','lm_en_fr') sentence = wino_x['test'][i]['context_fr'] option1 = wino_x['test'][i]['option1_fr'] option2 = wino_x['test'][i]['option2_fr'] targets = str(wino_x['test'][i]['answer']).replace("1",wino_x['test'][i]['option1_fr']).replace("2",wino_x['test'][i]['option2_fr']) ``` # Splits - `train` with 27,930 samples - no `valid` split - no `test` split # How to use? ``` from datasets import load_dataset dataset = load_dataset("CATIE-AQ/wino_x_fr_prompt_coreference") ``` # Citation ## Original data > @inproceedings{Emelin2021WinoXMW, title={Wino-X: Multilingual Winograd Schemas for Commonsense Reasoning and Coreference Resolution}, author={Denis Emelin and Rico Sennrich}, booktitle={EMNLP}, year={2021} } ## 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 MIT
mugeakbulut/Kadi_Sicilleri-ds-mini	--- dataset_info: features: - name: DOCNO dtype: int64 - name: ARXIVID_xml dtype: string - name: ARXIVID dtype: string - name: Link dtype: string - name: Title dtype: string - name: Authors dtype: string - name: 'Year ' dtype: int64 - name: Submitted on (gün, ay, yıl olarak submission tarihi) dtype: string - name: Submission history (v1 de dahil olmak üzere hepsi) dtype: string - name: Last revised tarihi dtype: string - name: content dtype: string - name: Comments dtype: string - name: Subject dtype: string - name: Journal reference dtype: string - name: DOI dtype: string - name: Cite as dtype: string - name: 'Unnamed: 16' dtype: float64 - name: 'Unnamed: 17' dtype: float64 - name: 'Unnamed: 18' dtype: float64 - name: 'Unnamed: 19' dtype: float64 - name: 'Unnamed: 20' dtype: string - name: Abstract_no dtype: string - name: 'Unnamed: 22' dtype: string - name: review dtype: string - name: content_length dtype: int64 splits: - name: train num_bytes: 1486810.797385621 num_examples: 413 - name: validation num_bytes: 165601.2026143791 num_examples: 46 download_size: 810073 dataset_size: 1652412.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---
freshpearYoon/train_free_9	--- dataset_info: features: - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 9604734776 num_examples: 10000 download_size: 1379496640 dataset_size: 9604734776 configs: - config_name: default data_files: - split: train path: data/train-* ---
autoevaluate/autoeval-staging-eval-project-e1907042-7494833	--- type: predictions tags: - autotrain - evaluation datasets: - clinc_oos eval_info: task: multi_class_classification model: aytugkaya/distilbert-base-uncased-finetuned-clinc metrics: [] dataset_name: clinc_oos dataset_config: small dataset_split: test col_mapping: text: text target: intent --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Multi-class Text Classification * Model: aytugkaya/distilbert-base-uncased-finetuned-clinc * Dataset: clinc_oos To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model.
gggggggg123/sber-golos	--- dataset_info: features: - name: text dtype: string - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 7677527180 num_examples: 7993 - name: validation num_bytes: 761700288 num_examples: 793 - name: test num_bytes: 9599558230 num_examples: 9994 download_size: 3068066823 dataset_size: 18038785698 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
open-llm-leaderboard/details_RWKV__rwkv-raven-1b5	--- pretty_name: Evaluation run of RWKV/rwkv-raven-1b5 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [RWKV/rwkv-raven-1b5](https://huggingface.co/RWKV/rwkv-raven-1b5) 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_RWKV__rwkv-raven-1b5\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-25T00:45:24.942259](https://huggingface.co/datasets/open-llm-leaderboard/details_RWKV__rwkv-raven-1b5/blob/main/results_2023-10-25T00-45-24.942259.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\": 0.05641778523489933,\n\ \ \"em_stderr\": 0.002362857556122875,\n \"f1\": 0.09820364932885885,\n\ \ \"f1_stderr\": 0.002610921727017063,\n \"acc\": 0.26953433307024466,\n\ \ \"acc_stderr\": 0.007004760840490157\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.05641778523489933,\n \"em_stderr\": 0.002362857556122875,\n\ \ \"f1\": 0.09820364932885885,\n \"f1_stderr\": 0.002610921727017063\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n },\n \"harness\|winogrande\|5\": {\n \"acc\": 0.5390686661404893,\n\ \ \"acc_stderr\": 0.014009521680980314\n }\n}\n```" repo_url: https://huggingface.co/RWKV/rwkv-raven-1b5 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_03T05_21_18.307582 path: - '/details_harness\|arc:challenge\|25_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-09-03T05:21:18.307582.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_25T00_45_24.942259 path: - '/details_harness\|drop\|3_2023-10-25T00-45-24.942259.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-25T00-45-24.942259.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_25T00_45_24.942259 path: - '/details_harness\|gsm8k\|5_2023-10-25T00-45-24.942259.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-25T00-45-24.942259.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hellaswag\|10_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-09-03T05:21:18.307582.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-management\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_03T05_21_18.307582 path: - '/details_harness\|truthfulqa:mc\|0_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-09-03T05:21:18.307582.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_25T00_45_24.942259 path: - '/details_harness\|winogrande\|5_2023-10-25T00-45-24.942259.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-25T00-45-24.942259.parquet' - config_name: results data_files: - split: 2023_09_03T05_21_18.307582 path: - results_2023-09-03T05:21:18.307582.parquet - split: 2023_10_25T00_45_24.942259 path: - results_2023-10-25T00-45-24.942259.parquet - split: latest path: - results_2023-10-25T00-45-24.942259.parquet --- # Dataset Card for Evaluation run of RWKV/rwkv-raven-1b5 ## Dataset Description - Homepage: - Repository: https://huggingface.co/RWKV/rwkv-raven-1b5 - 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 [RWKV/rwkv-raven-1b5](https://huggingface.co/RWKV/rwkv-raven-1b5) 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_RWKV__rwkv-raven-1b5", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-25T00:45:24.942259](https://huggingface.co/datasets/open-llm-leaderboard/details_RWKV__rwkv-raven-1b5/blob/main/results_2023-10-25T00-45-24.942259.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": 0.05641778523489933, "em_stderr": 0.002362857556122875, "f1": 0.09820364932885885, "f1_stderr": 0.002610921727017063, "acc": 0.26953433307024466, "acc_stderr": 0.007004760840490157 }, "harness\|drop\|3": { "em": 0.05641778523489933, "em_stderr": 0.002362857556122875, "f1": 0.09820364932885885, "f1_stderr": 0.002610921727017063 }, "harness\|gsm8k\|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness\|winogrande\|5": { "acc": 0.5390686661404893, "acc_stderr": 0.014009521680980314 } } ``` ### 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]
autoevaluate/autoeval-eval-futin__feed-top_vi_-7f787f-2245771643	--- type: predictions tags: - autotrain - evaluation datasets: - futin/feed eval_info: task: text_zero_shot_classification model: bigscience/bloom-560m metrics: [] dataset_name: futin/feed dataset_config: top_vi_ dataset_split: test col_mapping: text: text classes: classes target: target --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Zero-Shot Text Classification * Model: bigscience/bloom-560m * Dataset: futin/feed * Config: top_vi_ * Split: test To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@futin](https://huggingface.co/futin) for evaluating this model.
AppleHarem/frost_arknights	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of frost (Arknights) This is the dataset of frost (Arknights), containing 74 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 \| 74 \| [Download](dataset-raw.zip) \| Raw data with meta information. \| \| raw-stage3 \| 182 \| [Download](dataset-raw-stage3.zip) \| 3-stage cropped raw data with meta information. \| \| raw-stage3-eyes \| 200 \| [Download](dataset-raw-stage3-eyes.zip) \| 3-stage cropped (with eye-focus) raw data with meta information. \| \| 384x512 \| 74 \| [Download](dataset-384x512.zip) \| 384x512 aligned dataset. \| \| 512x704 \| 74 \| [Download](dataset-512x704.zip) \| 512x704 aligned dataset. \| \| 640x880 \| 74 \| [Download](dataset-640x880.zip) \| 640x880 aligned dataset. \| \| stage3-640 \| 182 \| [Download](dataset-stage3-640.zip) \| 3-stage cropped dataset with the shorter side not exceeding 640 pixels. \| \| stage3-800 \| 182 \| [Download](dataset-stage3-800.zip) \| 3-stage cropped dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p512-640 \| 142 \| [Download](dataset-stage3-p512-640.zip) \| 3-stage cropped dataset with the area not less than 512x512 pixels. \| \| stage3-eyes-640 \| 200 \| [Download](dataset-stage3-eyes-640.zip) \| 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 640 pixels. \| \| stage3-eyes-800 \| 200 \| [Download](dataset-stage3-eyes-800.zip) \| 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 800 pixels. \|
cheafdevo56/InfluentialTriplets	--- dataset_info: features: - name: query struct: - name: abstract dtype: string - name: corpus_id dtype: int64 - name: title dtype: string - name: pos struct: - name: abstract dtype: string - name: corpus_id dtype: int64 - name: title dtype: string - name: neg struct: - name: abstract dtype: string - name: corpus_id dtype: int64 - name: score dtype: int64 - name: title dtype: string splits: - name: train num_bytes: 73286160.22355364 num_examples: 19227 - name: validation num_bytes: 8145447.776446358 num_examples: 2137 download_size: 48583049 dataset_size: 81431608.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/cf3a3ead	--- dataset_info: features: - name: result dtype: string - name: id dtype: int64 splits: - name: train num_bytes: 180 num_examples: 10 download_size: 1335 dataset_size: 180 --- # Dataset Card for "cf3a3ead" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
NathanRoll/TalkBank_CA_CORAAL	--- dataset_info: features: - name: audio sequence: float32 - name: __index_level_0__ dtype: string splits: - name: train num_bytes: 9325350278 num_examples: 85 download_size: 9338282164 dataset_size: 9325350278 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "TalkBank_CA_CORAAL" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
nguyenth1312/traditional_clothes	--- dataset_info: features: - name: image dtype: image - name: 'Unnamed: 0' dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 148739545.0 num_examples: 59 download_size: 110961466 dataset_size: 148739545.0 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "traditional_clothes" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Slowblood/guanaco-llama2-1k	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1654448 num_examples: 1000 download_size: 966693 dataset_size: 1654448 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "guanaco-llama2-1k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Hev832/nah	--- license: mit ---
huggingartists/gizmo	--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/gizmo" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [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) - [About](#about) ## Dataset Description - Homepage: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Repository: [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - Paper: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - Size of the generated dataset: 0.361766 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/9dd7d13194aa588b336b78bcf05530f0.638x638x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/gizmo"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">gizmo</div> <a href="https://genius.com/artists/gizmo"> <div style="text-align: center; font-size: 14px;">@gizmo</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/gizmo). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/gizmo") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits \| train \|validation\|test\| \|------:\|---------:\|---:\| \|248\| -\| -\| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/gizmo") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])train_percentage), int(len(datasets['train']['text'])(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## 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 ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About Built by Aleksey Korshuk [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. 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aliciiavs/sign_language_image_dataset	--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': A '1': B '2': C '3': D '4': E '5': F '6': G '7': H '8': I '9': K '10': L '11': M '12': N '13': O '14': P '15': Q '16': R '17': S '18': T '19': U '20': V '21': W '22': X '23': Y splits: - name: train num_bytes: 1817258226.134 num_examples: 8442 download_size: 1803545459 dataset_size: 1817258226.134 configs: - config_name: default data_files: - split: train path: data/train-* ---
ravithejads/telugu_gpteacher_ft	--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 119244218 num_examples: 87228 download_size: 57558525 dataset_size: 119244218 configs: - config_name: default data_files: - split: train path: data/train-* ---
FreedomIntelligence/sharegpt-arabic	--- license: apache-2.0 --- Arabic ShareGPT data translated by gpt-3.5-turbo. The dataset is used in the research related to [MultilingualSIFT](https://github.com/FreedomIntelligence/MultilingualSIFT).
Ali-C137/Goud-Sum-Instruct-test-v0	--- dataset_info: features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 22447355 num_examples: 9497 download_size: 10247768 dataset_size: 22447355 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "Goud-Sum-Instruct" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
kewu93/sketch_100	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: val path: data/val-* dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 1431746.0 num_examples: 100 - name: val num_bytes: 1431746.0 num_examples: 100 download_size: 2858841 dataset_size: 2863492.0 --- # Dataset Card for "sketch_100" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
opinosis	--- annotations_creators: - crowdsourced language: - en language_creators: - found license: - apache-2.0 multilinguality: - monolingual pretty_name: Opinosis size_categories: - n<1K source_datasets: - original task_categories: - summarization task_ids: [] paperswithcode_id: opinosis tags: - abstractive-summarization dataset_info: features: - name: review_sents dtype: string - name: summaries sequence: string splits: - name: train num_bytes: 741270 num_examples: 51 download_size: 757398 dataset_size: 741270 --- # Dataset Card for "opinosis" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: http://kavita-ganesan.com/opinosis-opinion-dataset/ - Repository: https://github.com/kavgan/opinosis-summarization - Paper: [Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions](https://aclanthology.org/C10-1039/) - Point of Contact: [Kavita Ganesan](mailto:kavita@opinosis.ai) - Size of downloaded dataset files: 0.75 MB - Size of the generated dataset: 0.74 MB - Total amount of disk used: 1.50 MB ### Dataset Summary The Opinosis Opinion Dataset consists of sentences extracted from reviews for 51 topics. Topics and opinions are obtained from Tripadvisor, Edmunds.com and Amazon.com. ### 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 #### default - Size of downloaded dataset files: 0.75 MB - Size of the generated dataset: 0.74 MB - Total amount of disk used: 1.50 MB An example of 'train' looks as follows. ``` { "review_sents": "This is a fake topic. \nThe topics have multiple sentence inputs. \n", "summaries": ["This is a gold summary for topic 1. \nSentences in gold summaries are separated by newlines.", "This is another gold summary for topic 1. \nSentences in gold summaries are separated by newlines."] } ``` ### Data Fields The data fields are the same among all splits. #### default - `review_sents`: a `string` feature. - `summaries`: a `list` of `string` features. ### Data Splits \| name \|train\| \|-------\|----:\| \|default\| 51\| ## 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 The license for this dataset is Apache License 2.0 and can be found [here](https://github.com/kavgan/opinosis-summarization/blob/master/LICENSE). ### Citation Information ``` @inproceedings{ganesan2010opinosis, title={Opinosis: a graph-based approach to abstractive summarization of highly redundant opinions}, author={Ganesan, Kavita and Zhai, ChengXiang and Han, Jiawei}, booktitle={Proceedings of the 23rd International Conference on Computational Linguistics}, pages={340--348}, year={2010}, organization={Association for Computational Linguistics} } ``` ### Contributions Thanks to [@thomwolf](https://github.com/thomwolf), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.
CyberHarem/leila_fireemblem	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of leila (Fire Emblem) This is the dataset of leila (Fire Emblem), containing 15 images and their tags. The core tags of this character are `red_hair, short_hair, breasts, red_eyes, mole, hair_over_one_eye, mole_under_mouth, bangs, medium_breasts, shiny_hair, lips`, 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 \| 15 \| 17.24 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/leila_fireemblem/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 15 \| 10.22 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/leila_fireemblem/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 29 \| 18.53 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/leila_fireemblem/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 15 \| 15.68 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/leila_fireemblem/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 29 \| 24.63 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/leila_fireemblem/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/leila_fireemblem', 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 \| 15 \| ![](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, cape, holding, solo, belt, looking_at_viewer, smile, elbow_gloves, thighhighs, mask, parted_lips, shiny, bracelet, full_body, purple_bodysuit, bare_shoulders, cleavage, fingerless_gloves, high_heel_boots, knife, simple_background, thigh_boots, weapon \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| cape \| holding \| solo \| belt \| looking_at_viewer \| smile \| elbow_gloves \| thighhighs \| mask \| parted_lips \| shiny \| bracelet \| full_body \| purple_bodysuit \| bare_shoulders \| cleavage \| fingerless_gloves \| high_heel_boots \| knife \| simple_background \| thigh_boots \| weapon \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:-------\|:----------\|:-------\|:-------\|:--------------------\|:--------\|:---------------\|:-------------\|:-------\|:--------------\|:--------\|:-----------\|:------------\|:------------------\|:-----------------\|:-----------\|:--------------------\|:------------------\|:--------\|:--------------------\|:--------------\|:---------\| \| 0 \| 15 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \|
lissadesu/codeqa_v2	--- dataset_info: features: - name: labNo dtype: float64 - name: taskNo dtype: float64 - name: questioner dtype: string - name: question dtype: string - name: code dtype: string - name: startLine dtype: float64 - name: endLine dtype: float64 - name: questionType dtype: string - name: answer dtype: string - name: src dtype: string - name: code_processed dtype: string - name: id dtype: string - name: raw_code dtype: string - name: raw_comment dtype: string - name: comment dtype: string - name: q_code dtype: string splits: - name: train num_bytes: 46842820 num_examples: 35360 download_size: 17749500 dataset_size: 46842820 --- # Dataset Card for "codeqa_v2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
freshpearYoon/train_free_45	--- dataset_info: features: - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 9604567144 num_examples: 10000 download_size: 1352498488 dataset_size: 9604567144 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_ChaoticNeutrals__RP_Vision_7B	--- pretty_name: Evaluation run of ChaoticNeutrals/RP_Vision_7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [ChaoticNeutrals/RP_Vision_7B](https://huggingface.co/ChaoticNeutrals/RP_Vision_7B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_ChaoticNeutrals__RP_Vision_7B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-23T05:58:51.196010](https://huggingface.co/datasets/open-llm-leaderboard/details_ChaoticNeutrals__RP_Vision_7B/blob/main/results_2024-03-23T05-58-51.196010.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\": 0.6501517888097911,\n\ \ \"acc_stderr\": 0.032048221712222776,\n \"acc_norm\": 0.6507990701154603,\n\ \ \"acc_norm_stderr\": 0.03270238816915129,\n \"mc1\": 0.5263157894736842,\n\ \ \"mc1_stderr\": 0.017479241161975457,\n \"mc2\": 0.6850422329465207,\n\ \ \"mc2_stderr\": 0.015032479220010228\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6877133105802048,\n \"acc_stderr\": 0.013542598541688067,\n\ \ \"acc_norm\": 0.7064846416382252,\n \"acc_norm_stderr\": 0.013307250444941108\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.7117108145787692,\n\ \ \"acc_stderr\": 0.004520406331084043,\n \"acc_norm\": 0.8781119298944433,\n\ \ \"acc_norm_stderr\": 0.0032648787375868854\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252605,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252605\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6666666666666666,\n\ \ \"acc_stderr\": 0.04072314811876837,\n \"acc_norm\": 0.6666666666666666,\n\ \ \"acc_norm_stderr\": 0.04072314811876837\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.7105263157894737,\n \"acc_stderr\": 0.03690677986137283,\n\ \ \"acc_norm\": 0.7105263157894737,\n \"acc_norm_stderr\": 0.03690677986137283\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|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-clinical_knowledge\|5\"\ : {\n \"acc\": 0.7132075471698113,\n \"acc_stderr\": 0.027834912527544067,\n\ \ \"acc_norm\": 0.7132075471698113,\n \"acc_norm_stderr\": 0.027834912527544067\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7430555555555556,\n\ \ \"acc_stderr\": 0.03653946969442099,\n \"acc_norm\": 0.7430555555555556,\n\ \ \"acc_norm_stderr\": 0.03653946969442099\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.46,\n \"acc_stderr\": 0.05009082659620333,\n \ \ \"acc_norm\": 0.46,\n \"acc_norm_stderr\": 0.05009082659620333\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.55,\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\": 0.27,\n \"acc_stderr\": 0.044619604333847394,\n \ \ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.044619604333847394\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.653179190751445,\n\ \ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.653179190751445,\n\ \ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.3627450980392157,\n \"acc_stderr\": 0.04784060704105654,\n\ \ \"acc_norm\": 0.3627450980392157,\n \"acc_norm_stderr\": 0.04784060704105654\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.78,\n \"acc_stderr\": 0.04163331998932262,\n \"acc_norm\": 0.78,\n\ \ \"acc_norm_stderr\": 0.04163331998932262\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.6042553191489362,\n \"acc_stderr\": 0.03196758697835362,\n\ \ \"acc_norm\": 0.6042553191489362,\n \"acc_norm_stderr\": 0.03196758697835362\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.5087719298245614,\n\ \ \"acc_stderr\": 0.04702880432049615,\n \"acc_norm\": 0.5087719298245614,\n\ \ \"acc_norm_stderr\": 0.04702880432049615\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.5517241379310345,\n \"acc_stderr\": 0.04144311810878151,\n\ \ \"acc_norm\": 0.5517241379310345,\n \"acc_norm_stderr\": 0.04144311810878151\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.4126984126984127,\n \"acc_stderr\": 0.02535574126305527,\n \"\ acc_norm\": 0.4126984126984127,\n \"acc_norm_stderr\": 0.02535574126305527\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.4444444444444444,\n\ \ \"acc_stderr\": 0.044444444444444495,\n \"acc_norm\": 0.4444444444444444,\n\ \ \"acc_norm_stderr\": 0.044444444444444495\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\": 0.7870967741935484,\n\ \ \"acc_stderr\": 0.023287665127268545,\n \"acc_norm\": 0.7870967741935484,\n\ \ \"acc_norm_stderr\": 0.023287665127268545\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.4975369458128079,\n \"acc_stderr\": 0.03517945038691063,\n\ \ \"acc_norm\": 0.4975369458128079,\n \"acc_norm_stderr\": 0.03517945038691063\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.67,\n \"acc_stderr\": 0.04725815626252609,\n \"acc_norm\"\ : 0.67,\n \"acc_norm_stderr\": 0.04725815626252609\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7757575757575758,\n \"acc_stderr\": 0.032568666616811015,\n\ \ \"acc_norm\": 0.7757575757575758,\n \"acc_norm_stderr\": 0.032568666616811015\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7929292929292929,\n \"acc_stderr\": 0.028869778460267042,\n \"\ acc_norm\": 0.7929292929292929,\n \"acc_norm_stderr\": 0.028869778460267042\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8963730569948186,\n \"acc_stderr\": 0.02199531196364424,\n\ \ \"acc_norm\": 0.8963730569948186,\n \"acc_norm_stderr\": 0.02199531196364424\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6820512820512821,\n \"acc_stderr\": 0.02361088430892786,\n \ \ \"acc_norm\": 0.6820512820512821,\n \"acc_norm_stderr\": 0.02361088430892786\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.34814814814814815,\n \"acc_stderr\": 0.029045600290616248,\n \ \ \"acc_norm\": 0.34814814814814815,\n \"acc_norm_stderr\": 0.029045600290616248\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6974789915966386,\n \"acc_stderr\": 0.02983796238829193,\n \ \ \"acc_norm\": 0.6974789915966386,\n \"acc_norm_stderr\": 0.02983796238829193\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.36423841059602646,\n \"acc_stderr\": 0.03929111781242742,\n \"\ acc_norm\": 0.36423841059602646,\n \"acc_norm_stderr\": 0.03929111781242742\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8385321100917431,\n \"acc_stderr\": 0.01577623925616323,\n \"\ acc_norm\": 0.8385321100917431,\n \"acc_norm_stderr\": 0.01577623925616323\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.5324074074074074,\n \"acc_stderr\": 0.03402801581358966,\n \"\ acc_norm\": 0.5324074074074074,\n \"acc_norm_stderr\": 0.03402801581358966\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8382352941176471,\n \"acc_stderr\": 0.025845017986926917,\n \"\ acc_norm\": 0.8382352941176471,\n \"acc_norm_stderr\": 0.025845017986926917\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8059071729957806,\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\": 0.695067264573991,\n\ \ \"acc_stderr\": 0.030898610882477515,\n \"acc_norm\": 0.695067264573991,\n\ \ \"acc_norm_stderr\": 0.030898610882477515\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7862595419847328,\n \"acc_stderr\": 0.0359546161177469,\n\ \ \"acc_norm\": 0.7862595419847328,\n \"acc_norm_stderr\": 0.0359546161177469\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.743801652892562,\n \"acc_stderr\": 0.03984979653302871,\n \"acc_norm\"\ : 0.743801652892562,\n \"acc_norm_stderr\": 0.03984979653302871\n },\n\ \ \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7962962962962963,\n\ \ \"acc_stderr\": 0.03893542518824847,\n \"acc_norm\": 0.7962962962962963,\n\ \ \"acc_norm_stderr\": 0.03893542518824847\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7668711656441718,\n \"acc_stderr\": 0.0332201579577674,\n\ \ \"acc_norm\": 0.7668711656441718,\n \"acc_norm_stderr\": 0.0332201579577674\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.48214285714285715,\n\ \ \"acc_stderr\": 0.047427623612430116,\n \"acc_norm\": 0.48214285714285715,\n\ \ \"acc_norm_stderr\": 0.047427623612430116\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7961165048543689,\n \"acc_stderr\": 0.03989139859531771,\n\ \ \"acc_norm\": 0.7961165048543689,\n \"acc_norm_stderr\": 0.03989139859531771\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8803418803418803,\n\ \ \"acc_stderr\": 0.021262719400406964,\n \"acc_norm\": 0.8803418803418803,\n\ \ \"acc_norm_stderr\": 0.021262719400406964\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8263090676883781,\n\ \ \"acc_stderr\": 0.013547415658662257,\n \"acc_norm\": 0.8263090676883781,\n\ \ \"acc_norm_stderr\": 0.013547415658662257\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7369942196531792,\n \"acc_stderr\": 0.023703099525258165,\n\ \ \"acc_norm\": 0.7369942196531792,\n \"acc_norm_stderr\": 0.023703099525258165\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.47039106145251397,\n\ \ \"acc_stderr\": 0.016693154927383557,\n \"acc_norm\": 0.47039106145251397,\n\ \ \"acc_norm_stderr\": 0.016693154927383557\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.738562091503268,\n \"acc_stderr\": 0.025160998214292456,\n\ \ \"acc_norm\": 0.738562091503268,\n \"acc_norm_stderr\": 0.025160998214292456\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7202572347266881,\n\ \ \"acc_stderr\": 0.02549425935069491,\n \"acc_norm\": 0.7202572347266881,\n\ \ \"acc_norm_stderr\": 0.02549425935069491\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7283950617283951,\n \"acc_stderr\": 0.024748624490537368,\n\ \ \"acc_norm\": 0.7283950617283951,\n \"acc_norm_stderr\": 0.024748624490537368\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.48936170212765956,\n \"acc_stderr\": 0.029820747191422473,\n \ \ \"acc_norm\": 0.48936170212765956,\n \"acc_norm_stderr\": 0.029820747191422473\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.4654498044328553,\n\ \ \"acc_stderr\": 0.0127397115540457,\n \"acc_norm\": 0.4654498044328553,\n\ \ \"acc_norm_stderr\": 0.0127397115540457\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6911764705882353,\n \"acc_stderr\": 0.02806499816704009,\n\ \ \"acc_norm\": 0.6911764705882353,\n \"acc_norm_stderr\": 0.02806499816704009\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6470588235294118,\n \"acc_stderr\": 0.01933314202079716,\n \ \ \"acc_norm\": 0.6470588235294118,\n \"acc_norm_stderr\": 0.01933314202079716\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6727272727272727,\n\ \ \"acc_stderr\": 0.0449429086625209,\n \"acc_norm\": 0.6727272727272727,\n\ \ \"acc_norm_stderr\": 0.0449429086625209\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.710204081632653,\n \"acc_stderr\": 0.02904308868330433,\n\ \ \"acc_norm\": 0.710204081632653,\n \"acc_norm_stderr\": 0.02904308868330433\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8407960199004975,\n\ \ \"acc_stderr\": 0.02587064676616913,\n \"acc_norm\": 0.8407960199004975,\n\ \ \"acc_norm_stderr\": 0.02587064676616913\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.87,\n \"acc_stderr\": 0.033799766898963086,\n \ \ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.033799766898963086\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5120481927710844,\n\ \ \"acc_stderr\": 0.038913644958358175,\n \"acc_norm\": 0.5120481927710844,\n\ \ \"acc_norm_stderr\": 0.038913644958358175\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.847953216374269,\n \"acc_stderr\": 0.027539122889061452,\n\ \ \"acc_norm\": 0.847953216374269,\n \"acc_norm_stderr\": 0.027539122889061452\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.5263157894736842,\n\ \ \"mc1_stderr\": 0.017479241161975457,\n \"mc2\": 0.6850422329465207,\n\ \ \"mc2_stderr\": 0.015032479220010228\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8263614838200474,\n \"acc_stderr\": 0.010646116480330996\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.6209249431387415,\n \ \ \"acc_stderr\": 0.013363630295088363\n }\n}\n```" repo_url: https://huggingface.co/ChaoticNeutrals/RP_Vision_7B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|arc:challenge\|25_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-03-23T05-58-51.196010.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|gsm8k\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hellaswag\|10_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-23T05-58-51.196010.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-03-23T05-58-51.196010.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '/details_harness\|winogrande\|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-03-23T05-58-51.196010.parquet' - config_name: results data_files: - split: 2024_03_23T05_58_51.196010 path: - results_2024-03-23T05-58-51.196010.parquet - split: latest path: - results_2024-03-23T05-58-51.196010.parquet --- # Dataset Card for Evaluation run of ChaoticNeutrals/RP_Vision_7B <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [ChaoticNeutrals/RP_Vision_7B](https://huggingface.co/ChaoticNeutrals/RP_Vision_7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_ChaoticNeutrals__RP_Vision_7B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-23T05:58:51.196010](https://huggingface.co/datasets/open-llm-leaderboard/details_ChaoticNeutrals__RP_Vision_7B/blob/main/results_2024-03-23T05-58-51.196010.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": 0.6501517888097911, "acc_stderr": 0.032048221712222776, "acc_norm": 0.6507990701154603, "acc_norm_stderr": 0.03270238816915129, "mc1": 0.5263157894736842, "mc1_stderr": 0.017479241161975457, "mc2": 0.6850422329465207, "mc2_stderr": 0.015032479220010228 }, "harness\|arc:challenge\|25": { "acc": 0.6877133105802048, "acc_stderr": 0.013542598541688067, "acc_norm": 0.7064846416382252, "acc_norm_stderr": 0.013307250444941108 }, "harness\|hellaswag\|10": { "acc": 0.7117108145787692, "acc_stderr": 0.004520406331084043, "acc_norm": 0.8781119298944433, "acc_norm_stderr": 0.0032648787375868854 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6666666666666666, "acc_stderr": 0.04072314811876837, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.04072314811876837 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.7105263157894737, "acc_stderr": 0.03690677986137283, "acc_norm": 0.7105263157894737, "acc_norm_stderr": 0.03690677986137283 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.58, "acc_stderr": 0.04960449637488583, "acc_norm": 0.58, "acc_norm_stderr": 0.04960449637488583 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.7132075471698113, "acc_stderr": 0.027834912527544067, "acc_norm": 0.7132075471698113, "acc_norm_stderr": 0.027834912527544067 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7430555555555556, "acc_stderr": 0.03653946969442099, "acc_norm": 0.7430555555555556, "acc_norm_stderr": 0.03653946969442099 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.55, "acc_stderr": 0.05, "acc_norm": 0.55, "acc_norm_stderr": 0.05 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.653179190751445, "acc_stderr": 0.036291466701596636, "acc_norm": 0.653179190751445, "acc_norm_stderr": 0.036291466701596636 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.3627450980392157, "acc_stderr": 0.04784060704105654, "acc_norm": 0.3627450980392157, "acc_norm_stderr": 0.04784060704105654 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.78, "acc_stderr": 0.04163331998932262, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932262 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.6042553191489362, "acc_stderr": 0.03196758697835362, "acc_norm": 0.6042553191489362, "acc_norm_stderr": 0.03196758697835362 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.5087719298245614, "acc_stderr": 0.04702880432049615, "acc_norm": 0.5087719298245614, "acc_norm_stderr": 0.04702880432049615 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.5517241379310345, "acc_stderr": 0.04144311810878151, "acc_norm": 0.5517241379310345, "acc_norm_stderr": 0.04144311810878151 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.4126984126984127, "acc_stderr": 0.02535574126305527, "acc_norm": 0.4126984126984127, "acc_norm_stderr": 0.02535574126305527 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.4444444444444444, "acc_stderr": 0.044444444444444495, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.044444444444444495 }, "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": 0.7870967741935484, "acc_stderr": 0.023287665127268545, "acc_norm": 0.7870967741935484, "acc_norm_stderr": 0.023287665127268545 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.4975369458128079, "acc_stderr": 0.03517945038691063, "acc_norm": 0.4975369458128079, "acc_norm_stderr": 0.03517945038691063 }, "harness\|hendrycksTest-high_school_computer_science\|5": { "acc": 0.67, "acc_stderr": 0.04725815626252609, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252609 }, "harness\|hendrycksTest-high_school_european_history\|5": { "acc": 0.7757575757575758, "acc_stderr": 0.032568666616811015, "acc_norm": 0.7757575757575758, "acc_norm_stderr": 0.032568666616811015 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7929292929292929, "acc_stderr": 0.028869778460267042, "acc_norm": 0.7929292929292929, "acc_norm_stderr": 0.028869778460267042 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8963730569948186, "acc_stderr": 0.02199531196364424, "acc_norm": 0.8963730569948186, "acc_norm_stderr": 0.02199531196364424 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6820512820512821, "acc_stderr": 0.02361088430892786, "acc_norm": 0.6820512820512821, "acc_norm_stderr": 0.02361088430892786 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.34814814814814815, "acc_stderr": 0.029045600290616248, "acc_norm": 0.34814814814814815, "acc_norm_stderr": 0.029045600290616248 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6974789915966386, "acc_stderr": 0.02983796238829193, "acc_norm": 0.6974789915966386, "acc_norm_stderr": 0.02983796238829193 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.36423841059602646, "acc_stderr": 0.03929111781242742, "acc_norm": 0.36423841059602646, "acc_norm_stderr": 0.03929111781242742 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8385321100917431, "acc_stderr": 0.01577623925616323, "acc_norm": 0.8385321100917431, "acc_norm_stderr": 0.01577623925616323 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5324074074074074, "acc_stderr": 0.03402801581358966, "acc_norm": 0.5324074074074074, "acc_norm_stderr": 0.03402801581358966 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8382352941176471, "acc_stderr": 0.025845017986926917, "acc_norm": 0.8382352941176471, "acc_norm_stderr": 0.025845017986926917 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8059071729957806, "acc_stderr": 0.025744902532290916, "acc_norm": 0.8059071729957806, "acc_norm_stderr": 0.025744902532290916 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.695067264573991, "acc_stderr": 0.030898610882477515, "acc_norm": 0.695067264573991, "acc_norm_stderr": 0.030898610882477515 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7862595419847328, "acc_stderr": 0.0359546161177469, "acc_norm": 0.7862595419847328, "acc_norm_stderr": 0.0359546161177469 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.743801652892562, "acc_stderr": 0.03984979653302871, "acc_norm": 0.743801652892562, "acc_norm_stderr": 0.03984979653302871 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7962962962962963, "acc_stderr": 0.03893542518824847, "acc_norm": 0.7962962962962963, "acc_norm_stderr": 0.03893542518824847 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7668711656441718, "acc_stderr": 0.0332201579577674, "acc_norm": 0.7668711656441718, "acc_norm_stderr": 0.0332201579577674 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.48214285714285715, "acc_stderr": 0.047427623612430116, "acc_norm": 0.48214285714285715, "acc_norm_stderr": 0.047427623612430116 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7961165048543689, "acc_stderr": 0.03989139859531771, "acc_norm": 0.7961165048543689, "acc_norm_stderr": 0.03989139859531771 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8803418803418803, "acc_stderr": 0.021262719400406964, "acc_norm": 0.8803418803418803, "acc_norm_stderr": 0.021262719400406964 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8263090676883781, "acc_stderr": 0.013547415658662257, "acc_norm": 0.8263090676883781, "acc_norm_stderr": 0.013547415658662257 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7369942196531792, "acc_stderr": 0.023703099525258165, "acc_norm": 0.7369942196531792, "acc_norm_stderr": 0.023703099525258165 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.47039106145251397, "acc_stderr": 0.016693154927383557, "acc_norm": 0.47039106145251397, "acc_norm_stderr": 0.016693154927383557 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.738562091503268, "acc_stderr": 0.025160998214292456, "acc_norm": 0.738562091503268, "acc_norm_stderr": 0.025160998214292456 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7202572347266881, "acc_stderr": 0.02549425935069491, "acc_norm": 0.7202572347266881, "acc_norm_stderr": 0.02549425935069491 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7283950617283951, "acc_stderr": 0.024748624490537368, "acc_norm": 0.7283950617283951, "acc_norm_stderr": 0.024748624490537368 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.48936170212765956, "acc_stderr": 0.029820747191422473, "acc_norm": 0.48936170212765956, "acc_norm_stderr": 0.029820747191422473 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4654498044328553, "acc_stderr": 0.0127397115540457, "acc_norm": 0.4654498044328553, "acc_norm_stderr": 0.0127397115540457 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6911764705882353, "acc_stderr": 0.02806499816704009, "acc_norm": 0.6911764705882353, "acc_norm_stderr": 0.02806499816704009 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6470588235294118, "acc_stderr": 0.01933314202079716, "acc_norm": 0.6470588235294118, "acc_norm_stderr": 0.01933314202079716 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6727272727272727, "acc_stderr": 0.0449429086625209, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.0449429086625209 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.710204081632653, "acc_stderr": 0.02904308868330433, "acc_norm": 0.710204081632653, "acc_norm_stderr": 0.02904308868330433 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8407960199004975, "acc_stderr": 0.02587064676616913, "acc_norm": 0.8407960199004975, "acc_norm_stderr": 0.02587064676616913 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.87, "acc_stderr": 0.033799766898963086, "acc_norm": 0.87, "acc_norm_stderr": 0.033799766898963086 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5120481927710844, "acc_stderr": 0.038913644958358175, "acc_norm": 0.5120481927710844, "acc_norm_stderr": 0.038913644958358175 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.847953216374269, "acc_stderr": 0.027539122889061452, "acc_norm": 0.847953216374269, "acc_norm_stderr": 0.027539122889061452 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.5263157894736842, "mc1_stderr": 0.017479241161975457, "mc2": 0.6850422329465207, "mc2_stderr": 0.015032479220010228 }, "harness\|winogrande\|5": { "acc": 0.8263614838200474, "acc_stderr": 0.010646116480330996 }, "harness\|gsm8k\|5": { "acc": 0.6209249431387415, "acc_stderr": 0.013363630295088363 } } ``` ## 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]
FalconX80/nisoridataset-1k	--- dataset_info: features: - name: Prompt dtype: string - name: Answer dtype: string - name: text dtype: string splits: - name: train num_bytes: 279807 num_examples: 1000 download_size: 16815 dataset_size: 279807 configs: - config_name: default data_files: - split: train path: data/train-* ---
tororoin/pid-f	--- dataset_info: features: - name: document dtype: int64 - name: full_text dtype: string - name: tokens sequence: string - name: trailing_whitespace sequence: bool - name: labels sequence: string splits: - name: train num_bytes: 92523591 num_examples: 6807 download_size: 25505349 dataset_size: 92523591 configs: - config_name: default data_files: - split: train path: data/train-* ---
AdapterOcean/augmentatio-standardized_cluster_9_alpaca	--- dataset_info: features: - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 3406053 num_examples: 1482 download_size: 1387156 dataset_size: 3406053 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "augmentatio-standardized_cluster_9_alpaca" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Rosenberg/weibo_ner	--- license: mit ---
jlbaker361/actstu-runway-50	--- dataset_info: features: - name: image dtype: image - name: prompt dtype: string - name: seed dtype: int64 - name: steps dtype: int64 splits: - name: train num_bytes: 14154155.0 num_examples: 28 download_size: 14155865 dataset_size: 14154155.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
didi0di/Kakao_ChatData	--- dataset_info: features: - name: req dtype: string - name: res dtype: string splits: - name: train num_bytes: 8479418 num_examples: 73384 download_size: 5633370 dataset_size: 8479418 --- # Dataset Card for "Kakao_ChatData" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_mlabonne__NeuralPipe-7B-ties	--- pretty_name: Evaluation run of mlabonne/NeuralPipe-7B-ties dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mlabonne/NeuralPipe-7B-ties](https://huggingface.co/mlabonne/NeuralPipe-7B-ties)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_mlabonne__NeuralPipe-7B-ties\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-29T18:23:14.168913](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__NeuralPipe-7B-ties/blob/main/results_2023-12-29T18-23-14.168913.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\": 0.6463521388608168,\n\ \ \"acc_stderr\": 0.03211851750269888,\n \"acc_norm\": 0.6467147686147078,\n\ \ \"acc_norm_stderr\": 0.032775359620950996,\n \"mc1\": 0.44430844553243576,\n\ \ \"mc1_stderr\": 0.01739458625074317,\n \"mc2\": 0.6137333376102074,\n\ \ \"mc2_stderr\": 0.015322517797295732\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6407849829351536,\n \"acc_stderr\": 0.014020224155839157,\n\ \ \"acc_norm\": 0.6791808873720137,\n \"acc_norm_stderr\": 0.013640943091946533\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6729735112527385,\n\ \ \"acc_stderr\": 0.004681682605347881,\n \"acc_norm\": 0.8603863772156941,\n\ \ \"acc_norm_stderr\": 0.0034587739347195527\n },\n \"harness\|hendrycksTest-abstract_algebra\|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-anatomy\|5\": {\n \"acc\": 0.6148148148148148,\n\ \ \"acc_stderr\": 0.04203921040156279,\n \"acc_norm\": 0.6148148148148148,\n\ \ \"acc_norm_stderr\": 0.04203921040156279\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.7302631578947368,\n \"acc_stderr\": 0.03611780560284898,\n\ \ \"acc_norm\": 0.7302631578947368,\n \"acc_norm_stderr\": 0.03611780560284898\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\": 0.690566037735849,\n \"acc_stderr\": 0.028450154794118637,\n\ \ \"acc_norm\": 0.690566037735849,\n \"acc_norm_stderr\": 0.028450154794118637\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7777777777777778,\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\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"\ acc\": 0.46,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\"\ : 0.46,\n \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6416184971098265,\n\ \ \"acc_stderr\": 0.036563436533531585,\n \"acc_norm\": 0.6416184971098265,\n\ \ \"acc_norm_stderr\": 0.036563436533531585\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.4019607843137255,\n \"acc_stderr\": 0.04878608714466996,\n\ \ \"acc_norm\": 0.4019607843137255,\n \"acc_norm_stderr\": 0.04878608714466996\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.76,\n \"acc_stderr\": 0.042923469599092816,\n \"acc_norm\": 0.76,\n\ \ \"acc_norm_stderr\": 0.042923469599092816\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5872340425531914,\n \"acc_stderr\": 0.03218471141400351,\n\ \ \"acc_norm\": 0.5872340425531914,\n \"acc_norm_stderr\": 0.03218471141400351\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.5175438596491229,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.5175438596491229,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\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\"\ : 0.42063492063492064,\n \"acc_stderr\": 0.025424835086924,\n \"acc_norm\"\ : 0.42063492063492064,\n \"acc_norm_stderr\": 0.025424835086924\n },\n\ \ \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.4523809523809524,\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\": 0.36,\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\": 0.7677419354838709,\n\ \ \"acc_stderr\": 0.024022256130308235,\n \"acc_norm\": 0.7677419354838709,\n\ \ \"acc_norm_stderr\": 0.024022256130308235\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.4876847290640394,\n \"acc_stderr\": 0.035169204442208966,\n\ \ \"acc_norm\": 0.4876847290640394,\n \"acc_norm_stderr\": 0.035169204442208966\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\"\ : 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7636363636363637,\n \"acc_stderr\": 0.03317505930009181,\n\ \ \"acc_norm\": 0.7636363636363637,\n \"acc_norm_stderr\": 0.03317505930009181\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7878787878787878,\n \"acc_stderr\": 0.029126522834586815,\n \"\ acc_norm\": 0.7878787878787878,\n \"acc_norm_stderr\": 0.029126522834586815\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.9015544041450777,\n \"acc_stderr\": 0.021500249576033456,\n\ \ \"acc_norm\": 0.9015544041450777,\n \"acc_norm_stderr\": 0.021500249576033456\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6461538461538462,\n \"acc_stderr\": 0.02424378399406216,\n \ \ \"acc_norm\": 0.6461538461538462,\n \"acc_norm_stderr\": 0.02424378399406216\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.34074074074074073,\n \"acc_stderr\": 0.028897748741131154,\n \ \ \"acc_norm\": 0.34074074074074073,\n \"acc_norm_stderr\": 0.028897748741131154\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.6974789915966386,\n \"acc_stderr\": 0.029837962388291932,\n\ \ \"acc_norm\": 0.6974789915966386,\n \"acc_norm_stderr\": 0.029837962388291932\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.304635761589404,\n \"acc_stderr\": 0.03757949922943343,\n \"acc_norm\"\ : 0.304635761589404,\n \"acc_norm_stderr\": 0.03757949922943343\n },\n\ \ \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\": 0.8440366972477065,\n\ \ \"acc_stderr\": 0.01555580271359017,\n \"acc_norm\": 0.8440366972477065,\n\ \ \"acc_norm_stderr\": 0.01555580271359017\n },\n \"harness\|hendrycksTest-high_school_statistics\|5\"\ : {\n \"acc\": 0.5231481481481481,\n \"acc_stderr\": 0.03406315360711507,\n\ \ \"acc_norm\": 0.5231481481481481,\n \"acc_norm_stderr\": 0.03406315360711507\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8235294117647058,\n \"acc_stderr\": 0.02675640153807897,\n \"\ acc_norm\": 0.8235294117647058,\n \"acc_norm_stderr\": 0.02675640153807897\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.8185654008438819,\n \"acc_stderr\": 0.025085961144579665,\n \ \ \"acc_norm\": 0.8185654008438819,\n \"acc_norm_stderr\": 0.025085961144579665\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.6816143497757847,\n\ \ \"acc_stderr\": 0.03126580522513713,\n \"acc_norm\": 0.6816143497757847,\n\ \ \"acc_norm_stderr\": 0.03126580522513713\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7862595419847328,\n \"acc_stderr\": 0.0359546161177469,\n\ \ \"acc_norm\": 0.7862595419847328,\n \"acc_norm_stderr\": 0.0359546161177469\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\": 0.7962962962962963,\n\ \ \"acc_stderr\": 0.03893542518824847,\n \"acc_norm\": 0.7962962962962963,\n\ \ \"acc_norm_stderr\": 0.03893542518824847\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.7668711656441718,\n \"acc_stderr\": 0.0332201579577674,\n\ \ \"acc_norm\": 0.7668711656441718,\n \"acc_norm_stderr\": 0.0332201579577674\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.4642857142857143,\n\ \ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.4642857142857143,\n\ \ \"acc_norm_stderr\": 0.04733667890053756\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\": 0.8547008547008547,\n\ \ \"acc_stderr\": 0.023086635086841407,\n \"acc_norm\": 0.8547008547008547,\n\ \ \"acc_norm_stderr\": 0.023086635086841407\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8301404853128991,\n\ \ \"acc_stderr\": 0.013428186370608304,\n \"acc_norm\": 0.8301404853128991,\n\ \ \"acc_norm_stderr\": 0.013428186370608304\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7283236994219653,\n \"acc_stderr\": 0.02394851290546835,\n\ \ \"acc_norm\": 0.7283236994219653,\n \"acc_norm_stderr\": 0.02394851290546835\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.37318435754189944,\n\ \ \"acc_stderr\": 0.016175692013381964,\n \"acc_norm\": 0.37318435754189944,\n\ \ \"acc_norm_stderr\": 0.016175692013381964\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.738562091503268,\n \"acc_stderr\": 0.025160998214292456,\n\ \ \"acc_norm\": 0.738562091503268,\n \"acc_norm_stderr\": 0.025160998214292456\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7170418006430869,\n\ \ \"acc_stderr\": 0.02558306248998481,\n \"acc_norm\": 0.7170418006430869,\n\ \ \"acc_norm_stderr\": 0.02558306248998481\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.7314814814814815,\n \"acc_stderr\": 0.024659685185967284,\n\ \ \"acc_norm\": 0.7314814814814815,\n \"acc_norm_stderr\": 0.024659685185967284\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.5,\n \"acc_stderr\": 0.029827499313594685,\n \"acc_norm\"\ : 0.5,\n \"acc_norm_stderr\": 0.029827499313594685\n },\n \"harness\|hendrycksTest-professional_law\|5\"\ : {\n \"acc\": 0.4667535853976532,\n \"acc_stderr\": 0.012741974333897229,\n\ \ \"acc_norm\": 0.4667535853976532,\n \"acc_norm_stderr\": 0.012741974333897229\n\ \ },\n \"harness\|hendrycksTest-professional_medicine\|5\": {\n \"acc\"\ : 0.6875,\n \"acc_stderr\": 0.02815637344037142,\n \"acc_norm\": 0.6875,\n\ \ \"acc_norm_stderr\": 0.02815637344037142\n },\n \"harness\|hendrycksTest-professional_psychology\|5\"\ : {\n \"acc\": 0.6666666666666666,\n \"acc_stderr\": 0.019070985589687495,\n\ \ \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.019070985589687495\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6727272727272727,\n\ \ \"acc_stderr\": 0.0449429086625209,\n \"acc_norm\": 0.6727272727272727,\n\ \ \"acc_norm_stderr\": 0.0449429086625209\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7346938775510204,\n \"acc_stderr\": 0.028263889943784593,\n\ \ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.028263889943784593\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8407960199004975,\n\ \ \"acc_stderr\": 0.025870646766169136,\n \"acc_norm\": 0.8407960199004975,\n\ \ \"acc_norm_stderr\": 0.025870646766169136\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.86,\n \"acc_stderr\": 0.0348735088019777,\n \ \ \"acc_norm\": 0.86,\n \"acc_norm_stderr\": 0.0348735088019777\n },\n\ \ \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.5542168674698795,\n\ \ \"acc_stderr\": 0.03869543323472101,\n \"acc_norm\": 0.5542168674698795,\n\ \ \"acc_norm_stderr\": 0.03869543323472101\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\": 0.44430844553243576,\n\ \ \"mc1_stderr\": 0.01739458625074317,\n \"mc2\": 0.6137333376102074,\n\ \ \"mc2_stderr\": 0.015322517797295732\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8018942383583267,\n \"acc_stderr\": 0.011201862744487048\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.6952236542835482,\n \ \ \"acc_stderr\": 0.012679297549515427\n }\n}\n```" repo_url: https://huggingface.co/mlabonne/NeuralPipe-7B-ties leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|arc:challenge\|25_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-12-29T18-23-14.168913.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|gsm8k\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hellaswag\|10_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-29T18-23-14.168913.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-management\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|truthfulqa:mc\|0_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-12-29T18-23-14.168913.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '/details_harness\|winogrande\|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-12-29T18-23-14.168913.parquet' - config_name: results data_files: - split: 2023_12_29T18_23_14.168913 path: - results_2023-12-29T18-23-14.168913.parquet - split: latest path: - results_2023-12-29T18-23-14.168913.parquet --- # Dataset Card for Evaluation run of mlabonne/NeuralPipe-7B-ties <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [mlabonne/NeuralPipe-7B-ties](https://huggingface.co/mlabonne/NeuralPipe-7B-ties) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_mlabonne__NeuralPipe-7B-ties", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-29T18:23:14.168913](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__NeuralPipe-7B-ties/blob/main/results_2023-12-29T18-23-14.168913.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": 0.6463521388608168, "acc_stderr": 0.03211851750269888, "acc_norm": 0.6467147686147078, "acc_norm_stderr": 0.032775359620950996, "mc1": 0.44430844553243576, "mc1_stderr": 0.01739458625074317, "mc2": 0.6137333376102074, "mc2_stderr": 0.015322517797295732 }, "harness\|arc:challenge\|25": { "acc": 0.6407849829351536, "acc_stderr": 0.014020224155839157, "acc_norm": 0.6791808873720137, "acc_norm_stderr": 0.013640943091946533 }, "harness\|hellaswag\|10": { "acc": 0.6729735112527385, "acc_stderr": 0.004681682605347881, "acc_norm": 0.8603863772156941, "acc_norm_stderr": 0.0034587739347195527 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6148148148148148, "acc_stderr": 0.04203921040156279, "acc_norm": 0.6148148148148148, "acc_norm_stderr": 0.04203921040156279 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.7302631578947368, "acc_stderr": 0.03611780560284898, "acc_norm": 0.7302631578947368, "acc_norm_stderr": 0.03611780560284898 }, "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": 0.690566037735849, "acc_stderr": 0.028450154794118637, "acc_norm": 0.690566037735849, "acc_norm_stderr": 0.028450154794118637 }, "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": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6416184971098265, "acc_stderr": 0.036563436533531585, "acc_norm": 0.6416184971098265, "acc_norm_stderr": 0.036563436533531585 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.4019607843137255, "acc_stderr": 0.04878608714466996, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.04878608714466996 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.76, "acc_stderr": 0.042923469599092816, "acc_norm": 0.76, "acc_norm_stderr": 0.042923469599092816 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5872340425531914, "acc_stderr": 0.03218471141400351, "acc_norm": 0.5872340425531914, "acc_norm_stderr": 0.03218471141400351 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.5175438596491229, "acc_stderr": 0.04700708033551038, "acc_norm": 0.5175438596491229, "acc_norm_stderr": 0.04700708033551038 }, "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": 0.42063492063492064, "acc_stderr": 0.025424835086924, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.025424835086924 }, "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": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7677419354838709, "acc_stderr": 0.024022256130308235, "acc_norm": 0.7677419354838709, "acc_norm_stderr": 0.024022256130308235 }, "harness\|hendrycksTest-high_school_chemistry\|5": { "acc": 0.4876847290640394, "acc_stderr": 0.035169204442208966, "acc_norm": 0.4876847290640394, "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": 0.7636363636363637, "acc_stderr": 0.03317505930009181, "acc_norm": 0.7636363636363637, "acc_norm_stderr": 0.03317505930009181 }, "harness\|hendrycksTest-high_school_geography\|5": { "acc": 0.7878787878787878, "acc_stderr": 0.029126522834586815, "acc_norm": 0.7878787878787878, "acc_norm_stderr": 0.029126522834586815 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.9015544041450777, "acc_stderr": 0.021500249576033456, "acc_norm": 0.9015544041450777, "acc_norm_stderr": 0.021500249576033456 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6461538461538462, "acc_stderr": 0.02424378399406216, "acc_norm": 0.6461538461538462, "acc_norm_stderr": 0.02424378399406216 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.34074074074074073, "acc_stderr": 0.028897748741131154, "acc_norm": 0.34074074074074073, "acc_norm_stderr": 0.028897748741131154 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.6974789915966386, "acc_stderr": 0.029837962388291932, "acc_norm": 0.6974789915966386, "acc_norm_stderr": 0.029837962388291932 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.304635761589404, "acc_stderr": 0.03757949922943343, "acc_norm": 0.304635761589404, "acc_norm_stderr": 0.03757949922943343 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8440366972477065, "acc_stderr": 0.01555580271359017, "acc_norm": 0.8440366972477065, "acc_norm_stderr": 0.01555580271359017 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.5231481481481481, "acc_stderr": 0.03406315360711507, "acc_norm": 0.5231481481481481, "acc_norm_stderr": 0.03406315360711507 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8235294117647058, "acc_stderr": 0.02675640153807897, "acc_norm": 0.8235294117647058, "acc_norm_stderr": 0.02675640153807897 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.8185654008438819, "acc_stderr": 0.025085961144579665, "acc_norm": 0.8185654008438819, "acc_norm_stderr": 0.025085961144579665 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.6816143497757847, "acc_stderr": 0.03126580522513713, "acc_norm": 0.6816143497757847, "acc_norm_stderr": 0.03126580522513713 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7862595419847328, "acc_stderr": 0.0359546161177469, "acc_norm": 0.7862595419847328, "acc_norm_stderr": 0.0359546161177469 }, "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": 0.7962962962962963, "acc_stderr": 0.03893542518824847, "acc_norm": 0.7962962962962963, "acc_norm_stderr": 0.03893542518824847 }, "harness\|hendrycksTest-logical_fallacies\|5": { "acc": 0.7668711656441718, "acc_stderr": 0.0332201579577674, "acc_norm": 0.7668711656441718, "acc_norm_stderr": 0.0332201579577674 }, "harness\|hendrycksTest-machine_learning\|5": { "acc": 0.4642857142857143, "acc_stderr": 0.04733667890053756, "acc_norm": 0.4642857142857143, "acc_norm_stderr": 0.04733667890053756 }, "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": 0.8547008547008547, "acc_stderr": 0.023086635086841407, "acc_norm": 0.8547008547008547, "acc_norm_stderr": 0.023086635086841407 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8301404853128991, "acc_stderr": 0.013428186370608304, "acc_norm": 0.8301404853128991, "acc_norm_stderr": 0.013428186370608304 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7283236994219653, "acc_stderr": 0.02394851290546835, "acc_norm": 0.7283236994219653, "acc_norm_stderr": 0.02394851290546835 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.37318435754189944, "acc_stderr": 0.016175692013381964, "acc_norm": 0.37318435754189944, "acc_norm_stderr": 0.016175692013381964 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.738562091503268, "acc_stderr": 0.025160998214292456, "acc_norm": 0.738562091503268, "acc_norm_stderr": 0.025160998214292456 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7170418006430869, "acc_stderr": 0.02558306248998481, "acc_norm": 0.7170418006430869, "acc_norm_stderr": 0.02558306248998481 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.7314814814814815, "acc_stderr": 0.024659685185967284, "acc_norm": 0.7314814814814815, "acc_norm_stderr": 0.024659685185967284 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.5, "acc_stderr": 0.029827499313594685, "acc_norm": 0.5, "acc_norm_stderr": 0.029827499313594685 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.4667535853976532, "acc_stderr": 0.012741974333897229, "acc_norm": 0.4667535853976532, "acc_norm_stderr": 0.012741974333897229 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6875, "acc_stderr": 0.02815637344037142, "acc_norm": 0.6875, "acc_norm_stderr": 0.02815637344037142 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6666666666666666, "acc_stderr": 0.019070985589687495, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.019070985589687495 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6727272727272727, "acc_stderr": 0.0449429086625209, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.0449429086625209 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7346938775510204, "acc_stderr": 0.028263889943784593, "acc_norm": 0.7346938775510204, "acc_norm_stderr": 0.028263889943784593 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8407960199004975, "acc_stderr": 0.025870646766169136, "acc_norm": 0.8407960199004975, "acc_norm_stderr": 0.025870646766169136 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.86, "acc_stderr": 0.0348735088019777, "acc_norm": 0.86, "acc_norm_stderr": 0.0348735088019777 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5542168674698795, "acc_stderr": 0.03869543323472101, "acc_norm": 0.5542168674698795, "acc_norm_stderr": 0.03869543323472101 }, "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": 0.44430844553243576, "mc1_stderr": 0.01739458625074317, "mc2": 0.6137333376102074, "mc2_stderr": 0.015322517797295732 }, "harness\|winogrande\|5": { "acc": 0.8018942383583267, "acc_stderr": 0.011201862744487048 }, "harness\|gsm8k\|5": { "acc": 0.6952236542835482, "acc_stderr": 0.012679297549515427 } } ``` ## 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 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It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). 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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]
argilla/kto-mix-13k	--- language: - en license: mit size_categories: - 1K<n<10K configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: prompt dtype: string - name: completion list: - name: content dtype: string - name: role dtype: string - name: label dtype: bool - name: rating dtype: float64 - name: dataset dtype: string splits: - name: train num_bytes: 44826263 num_examples: 12517 download_size: 18119695 dataset_size: 44826263 tags: - distilabel - synthetic - kto --- # Argilla KTO Mix 13 Dataset > A KTO signal transformed version of the highly loved [Argilla DPO Mix](https://huggingface.co/datasets/argilla/dpo-mix-7k), which is small cocktail combining DPO datasets built by Argilla with [distilabel](https://github.com/argilla-io/distilabel). The goal of this dataset is having a small, high-quality KTO dataset by filtering only highly rated chosen responses. <div> <img src="https://cdn-uploads.huggingface.co/production/uploads/60420dccc15e823a685f2b03/Csd2-zPji7iwIxyz6UFe1.webp"> </div> <p align="center"> <a href="https://github.com/argilla-io/distilabel"> <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/> </a> </p> ## Why KTO? The [KTO paper](https://arxiv.org/abs/2402.01306) states: - KTO matches or exceeds DPO performance at scales from 1B to 30B parameters.1 That is, taking a preference dataset of n DPO pairs and breaking it up into 2n examples for KTO can yield better generations, despite the model ostensibly learning from a weaker signal. - KTO can handle extreme data imbalances, matching DPO performance while using up to 90% fewer desirable examples (i.e., examples of good generations). Its success thus cannot be ascribed to the alignment data being sourced from a preference dataset. - When the pretrained model is sufficiently good, one can skip supervised finetuning and go straight to KTO without a loss in generation quality. In contrast, we find that without doing SFT first, DPO-aligned models are significantly worse at all scales. ## Reproduce KTO Transformation [Original DPO dataset: DPO mix 7k](https://huggingface.co/datasets/argilla/dpo-mix-7k) <a target="_blank" href="https://colab.research.google.com/drive/10bMnI3vvG4hEKblUhtLZKu01YSnPhmaF?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> </a>
gmongaras/BERT_Base_Cased_512_GLUE	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* dataset_info: features: - name: sentence dtype: string - name: label dtype: float64 - name: dataset_name dtype: string splits: - name: train num_bytes: 163269248 num_examples: 949728 - name: validation num_bytes: 12111201 num_examples: 69711 - name: test num_bytes: 64264632 num_examples: 425205 download_size: 135600002 dataset_size: 239645081 --- Dataset from: https://huggingface.co/datasets/glue Every split besides the ax split is in this dataset. Lines above 512 characters from the BERT-cased (bert-base-cased) tokenizer are removed
erbacher/personalized-proactive-conversations	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: id dtype: int64 - name: uid dtype: int64 - name: user dtype: string - name: conversation list: - name: assistant dtype: string - name: turn_id dtype: int64 - name: user dtype: string - name: __index_level_0__ dtype: int64 - name: queries list: - name: queries sequence: string - name: turnid dtype: int64 - name: messages list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 302752705 num_examples: 27870 - name: test num_bytes: 2117394 num_examples: 200 download_size: 143529145 dataset_size: 304870099 --- # Dataset Card for "personalized-proactive-conversations" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
abishekmahi/tamil-kavithai	--- license: mit task_categories: - text-generation language: - ta pretty_name: kavithai tags: - art - poem - webdataset ---
CyberHarem/hare_bluearchive	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of hare/小鈎ハレ/晴 (Blue Archive) This is the dataset of hare/小鈎ハレ/晴 (Blue Archive), containing 330 images and their tags. The core tags of this character are `long_hair, grey_hair, halo, green_eyes, ponytail, hair_ornament, cross_hair_ornament`, 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 \| 330 \| 470.16 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/hare_bluearchive/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 1200 \| 330 \| 399.03 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/hare_bluearchive/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 858 \| 840.33 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/hare_bluearchive/resolve/main/dataset-stage3-p480-1200.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/hare_bluearchive', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| Tags \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| 0 \| 22 \| ![](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, simple_background, solo, blush, looking_at_viewer, black_hoodie, hood_down, long_sleeves, white_background, closed_mouth, jacket, upper_body, open_clothes \| \| 1 \| 5 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| 1girl, black_hoodie, holding_can, hood_down, long_sleeves, monster_energy, solo, blush, simple_background, upper_body, closed_mouth, energy_drink, looking_at_viewer, smile, blue_background, jacket, sidelocks \| \| 2 \| 11 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| 1girl, black_scarf, hat, hooded_jacket, official_alternate_costume, simple_background, white_headwear, blush, green_jacket, open_jacket, solo, white_background, long_sleeves, looking_at_viewer, upper_body, hood_down, smile, closed_mouth \| \| 3 \| 6 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| 1girl, black_pantyhose, black_scarf, blush, green_jacket, hat, holding_cup, long_sleeves, looking_at_viewer, official_alternate_costume, open_jacket, solo, white_headwear, hooded_jacket, sitting, smile, open_mouth, shoes \| \| 4 \| 6 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| 1boy, 1girl, blush, hetero, nipples, penis, pussy, sex, solo_focus, mosaic_censoring, navel, spread_legs, vaginal, small_breasts, sweat, collarbone, indoors, lying, nude, open_mouth, pov, white_hair \| \| 5 \| 5 \| ![](samples/5/clu5-sample0.png) \| ![](samples/5/clu5-sample1.png) \| ![](samples/5/clu5-sample2.png) \| ![](samples/5/clu5-sample3.png) \| ![](samples/5/clu5-sample4.png) \| 1girl, alternate_costume, cosplay, looking_at_viewer, midriff, millennium_cheerleader_outfit_(blue_archive), navel, pleated_skirt, solo, white_skirt, bare_shoulders, blush, holding_pom_poms, simple_background, stomach, cleavage, detached_collar, white_background, closed_mouth, medium_breasts, sidelocks, small_breasts, white_hair \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| simple_background \| solo \| blush \| looking_at_viewer \| black_hoodie \| hood_down \| long_sleeves \| white_background \| closed_mouth \| jacket \| upper_body \| open_clothes \| holding_can \| monster_energy \| energy_drink \| smile \| blue_background \| sidelocks \| black_scarf \| hat \| hooded_jacket \| official_alternate_costume \| white_headwear \| green_jacket \| open_jacket \| black_pantyhose \| holding_cup \| sitting \| open_mouth \| shoes \| 1boy \| hetero \| nipples \| penis \| pussy \| sex \| solo_focus \| mosaic_censoring \| navel \| spread_legs \| vaginal \| small_breasts \| sweat \| collarbone \| indoors \| lying \| nude \| pov \| white_hair \| alternate_costume \| cosplay \| midriff \| millennium_cheerleader_outfit_(blue_archive) \| pleated_skirt \| white_skirt \| bare_shoulders \| holding_pom_poms \| stomach \| cleavage \| detached_collar \| medium_breasts \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:--------------------\|:-------\|:--------\|:--------------------\|:---------------\|:------------\|:---------------\|:-------------------\|:---------------\|:---------\|:-------------\|:---------------\|:--------------\|:-----------------\|:---------------\|:--------\|:------------------\|:------------\|:--------------\|:------\|:----------------\|:-----------------------------\|:-----------------\|:---------------\|:--------------\|:------------------\|:--------------\|:----------\|:-------------\|:--------\|:-------\|:---------\|:----------\|:--------\|:--------\|:------\|:-------------\|:-------------------\|:--------\|:--------------\|:----------\|:----------------\|:--------\|:-------------\|:----------\|:--------\|:-------\|:------\|:-------------\|:--------------------\|:----------\|:----------\|:-----------------------------------------------\|:----------------\|:--------------\|:-----------------\|:-------------------\|:----------\|:-----------\|:------------------\|:-----------------\| \| 0 \| 22 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 1 \| 5 \| ![](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 \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 11 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| X \| X \| X \| X \| X \| \| X \| X \| X \| X \| \| X \| \| \| \| \| X \| \| \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 3 \| 6 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| X \| \| X \| X \| X \| \| \| X \| \| \| \| \| \| \| \| \| X \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 4 \| 6 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| X \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| 5 \| 5 \| ![](samples/5/clu5-sample0.png) \| ![](samples/5/clu5-sample1.png) \| ![](samples/5/clu5-sample2.png) \| ![](samples/5/clu5-sample3.png) \| ![](samples/5/clu5-sample4.png) \| X \| X \| X \| X \| X \| \| \| \| X \| X \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| \| \| X \| \| \| \| \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \|
vincentiussgk/pneumonia_TA_split_proper	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: file_path dtype: string - name: label dtype: string - name: image dtype: image splits: - name: train num_bytes: 339951925.0 num_examples: 900 - name: test num_bytes: 78429911.0 num_examples: 225 download_size: 417503439 dataset_size: 418381836.0 --- # Dataset Card for "pneumonia_TA_split_proper" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
EdisonBlack/lora-people	--- license: cc-by-sa-3.0 ---
Nexdata/262_People_5162_Images_Handwriting_OCR_Data_of_Traditional_Chinese_Characters_Taiwan_China	--- license: cc-by-nc-nd-4.0 --- ## Description There are 5,000 images of handwriting data of traditional Chinese characters. Texts in the data were annotated for the line-level quadrilateral bounding box. The data can be used for chinese characters recognition application For more details, please refer to the link: https://www.nexdata.ai/dataset/1190?source=Huggingface ## Data size 5,000 images ## Collecting environment including A4 paper, square paper, lined paper, etc. ## Device cellphone ## Photographic angle eye-level angle ## Data format the image data format is .jpg, the annotation file format is .json ## Annotation content line-level quadrilateral bounding box annotation and transcription for the texts ## Accuracy the error bound of each vertex of quadrilateral bounding box is within 5 pixels, which is a qualified annotation, the accuracy of bounding boxes is not less than 97%; the texts transcription accuracy is not less than 97% # Licensing Information Commercial License
open-llm-leaderboard/details_mncai__mistral-7b-dpo-v5	--- pretty_name: Evaluation run of mncai/mistral-7b-dpo-v5 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mncai/mistral-7b-dpo-v5](https://huggingface.co/mncai/mistral-7b-dpo-v5) 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_mncai__mistral-7b-dpo-v5\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-16T17:06:29.601004](https://huggingface.co/datasets/open-llm-leaderboard/details_mncai__mistral-7b-dpo-v5/blob/main/results_2023-12-16T17-06-29.601004.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\": 0.6444771644137858,\n\ \ \"acc_stderr\": 0.032189712118428256,\n \"acc_norm\": 0.6439145631454195,\n\ \ \"acc_norm_stderr\": 0.03285791543982518,\n \"mc1\": 0.5385556915544676,\n\ \ \"mc1_stderr\": 0.017451384104637452,\n \"mc2\": 0.6686090881936299,\n\ \ \"mc2_stderr\": 0.015322918299770005\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.6911262798634812,\n \"acc_stderr\": 0.013501770929344,\n\ \ \"acc_norm\": 0.7201365187713311,\n \"acc_norm_stderr\": 0.01311904089772592\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.6978689504082852,\n\ \ \"acc_stderr\": 0.004582433109636476,\n \"acc_norm\": 0.8757219677355108,\n\ \ \"acc_norm_stderr\": 0.003292242543637345\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.04153948404742398,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.04153948404742398\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.6907894736842105,\n \"acc_stderr\": 0.037610708698674805,\n\ \ \"acc_norm\": 0.6907894736842105,\n \"acc_norm_stderr\": 0.037610708698674805\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\": 0.6943396226415094,\n \"acc_stderr\": 0.028353298073322666,\n\ \ \"acc_norm\": 0.6943396226415094,\n \"acc_norm_stderr\": 0.028353298073322666\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.7361111111111112,\n\ \ \"acc_stderr\": 0.03685651095897532,\n \"acc_norm\": 0.7361111111111112,\n\ \ \"acc_norm_stderr\": 0.03685651095897532\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\"\ : 0.55,\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\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.6705202312138728,\n\ \ \"acc_stderr\": 0.03583901754736412,\n \"acc_norm\": 0.6705202312138728,\n\ \ \"acc_norm_stderr\": 0.03583901754736412\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.4117647058823529,\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\":\ \ 0.78,\n \"acc_stderr\": 0.04163331998932263,\n \"acc_norm\": 0.78,\n\ \ \"acc_norm_stderr\": 0.04163331998932263\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.5531914893617021,\n \"acc_stderr\": 0.0325005368436584,\n\ \ \"acc_norm\": 0.5531914893617021,\n \"acc_norm_stderr\": 0.0325005368436584\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\": 0.5724137931034483,\n \"acc_stderr\": 0.04122737111370332,\n\ \ \"acc_norm\": 0.5724137931034483,\n \"acc_norm_stderr\": 0.04122737111370332\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.42063492063492064,\n \"acc_stderr\": 0.025424835086923996,\n \"\ acc_norm\": 0.42063492063492064,\n \"acc_norm_stderr\": 0.025424835086923996\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.4365079365079365,\n\ \ \"acc_stderr\": 0.04435932892851466,\n \"acc_norm\": 0.4365079365079365,\n\ \ \"acc_norm_stderr\": 0.04435932892851466\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252604,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252604\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.7935483870967742,\n\ \ \"acc_stderr\": 0.023025899617188716,\n \"acc_norm\": 0.7935483870967742,\n\ \ \"acc_norm_stderr\": 0.023025899617188716\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\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\ : 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.7696969696969697,\n \"acc_stderr\": 0.0328766675860349,\n\ \ \"acc_norm\": 0.7696969696969697,\n \"acc_norm_stderr\": 0.0328766675860349\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.7929292929292929,\n \"acc_stderr\": 0.028869778460267042,\n \"\ acc_norm\": 0.7929292929292929,\n \"acc_norm_stderr\": 0.028869778460267042\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.8808290155440415,\n \"acc_stderr\": 0.02338193534812143,\n\ \ \"acc_norm\": 0.8808290155440415,\n \"acc_norm_stderr\": 0.02338193534812143\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.6487179487179487,\n \"acc_stderr\": 0.024203665177902803,\n\ \ \"acc_norm\": 0.6487179487179487,\n \"acc_norm_stderr\": 0.024203665177902803\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.3037037037037037,\n \"acc_stderr\": 0.028037929969114993,\n \ \ \"acc_norm\": 0.3037037037037037,\n \"acc_norm_stderr\": 0.028037929969114993\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.634453781512605,\n \"acc_stderr\": 0.031282177063684614,\n \ \ \"acc_norm\": 0.634453781512605,\n \"acc_norm_stderr\": 0.031282177063684614\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.31125827814569534,\n \"acc_stderr\": 0.03780445850526732,\n \"\ acc_norm\": 0.31125827814569534,\n \"acc_norm_stderr\": 0.03780445850526732\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.8403669724770643,\n \"acc_stderr\": 0.015703498348461766,\n \"\ acc_norm\": 0.8403669724770643,\n \"acc_norm_stderr\": 0.015703498348461766\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.49537037037037035,\n \"acc_stderr\": 0.03409825519163572,\n \"\ acc_norm\": 0.49537037037037035,\n \"acc_norm_stderr\": 0.03409825519163572\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.8088235294117647,\n \"acc_stderr\": 0.027599174300640766,\n \"\ acc_norm\": 0.8088235294117647,\n \"acc_norm_stderr\": 0.027599174300640766\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.7763713080168776,\n \"acc_stderr\": 0.027123298205229962,\n \ \ \"acc_norm\": 0.7763713080168776,\n \"acc_norm_stderr\": 0.027123298205229962\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.695067264573991,\n\ \ \"acc_stderr\": 0.030898610882477515,\n \"acc_norm\": 0.695067264573991,\n\ \ \"acc_norm_stderr\": 0.030898610882477515\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.7786259541984732,\n \"acc_stderr\": 0.03641297081313729,\n\ \ \"acc_norm\": 0.7786259541984732,\n \"acc_norm_stderr\": 0.03641297081313729\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.768595041322314,\n \"acc_stderr\": 0.038498560987940904,\n \"\ acc_norm\": 0.768595041322314,\n \"acc_norm_stderr\": 0.038498560987940904\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.7592592592592593,\n\ \ \"acc_stderr\": 0.04133119440243839,\n \"acc_norm\": 0.7592592592592593,\n\ \ \"acc_norm_stderr\": 0.04133119440243839\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\": 0.4642857142857143,\n\ \ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.4642857142857143,\n\ \ \"acc_norm_stderr\": 0.04733667890053756\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.7864077669902912,\n \"acc_stderr\": 0.040580420156460344,\n\ \ \"acc_norm\": 0.7864077669902912,\n \"acc_norm_stderr\": 0.040580420156460344\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.8846153846153846,\n\ \ \"acc_stderr\": 0.020930193185179326,\n \"acc_norm\": 0.8846153846153846,\n\ \ \"acc_norm_stderr\": 0.020930193185179326\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.68,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.68,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.8301404853128991,\n\ \ \"acc_stderr\": 0.013428186370608311,\n \"acc_norm\": 0.8301404853128991,\n\ \ \"acc_norm_stderr\": 0.013428186370608311\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.7398843930635838,\n \"acc_stderr\": 0.023618678310069356,\n\ \ \"acc_norm\": 0.7398843930635838,\n \"acc_norm_stderr\": 0.023618678310069356\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.4480446927374302,\n\ \ \"acc_stderr\": 0.016631976628930595,\n \"acc_norm\": 0.4480446927374302,\n\ \ \"acc_norm_stderr\": 0.016631976628930595\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.7189542483660131,\n \"acc_stderr\": 0.025738854797818737,\n\ \ \"acc_norm\": 0.7189542483660131,\n \"acc_norm_stderr\": 0.025738854797818737\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.7138263665594855,\n\ \ \"acc_stderr\": 0.025670259242188933,\n \"acc_norm\": 0.7138263665594855,\n\ \ \"acc_norm_stderr\": 0.025670259242188933\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.75,\n \"acc_stderr\": 0.02409347123262133,\n \ \ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.02409347123262133\n \ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"acc\"\ : 0.4858156028368794,\n \"acc_stderr\": 0.02981549448368206,\n \"\ acc_norm\": 0.4858156028368794,\n \"acc_norm_stderr\": 0.02981549448368206\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.46479791395045633,\n\ \ \"acc_stderr\": 0.012738547371303957,\n \"acc_norm\": 0.46479791395045633,\n\ \ \"acc_norm_stderr\": 0.012738547371303957\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.6544117647058824,\n \"acc_stderr\": 0.02888819310398863,\n\ \ \"acc_norm\": 0.6544117647058824,\n \"acc_norm_stderr\": 0.02888819310398863\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.6617647058823529,\n \"acc_stderr\": 0.01913994374848704,\n \ \ \"acc_norm\": 0.6617647058823529,\n \"acc_norm_stderr\": 0.01913994374848704\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.6545454545454545,\n\ \ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\ \ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.7183673469387755,\n \"acc_stderr\": 0.028795185574291293,\n\ \ \"acc_norm\": 0.7183673469387755,\n \"acc_norm_stderr\": 0.028795185574291293\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.8407960199004975,\n\ \ \"acc_stderr\": 0.025870646766169146,\n \"acc_norm\": 0.8407960199004975,\n\ \ \"acc_norm_stderr\": 0.025870646766169146\n },\n \"harness\|hendrycksTest-us_foreign_policy\|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-virology\|5\": {\n \"acc\": 0.5481927710843374,\n\ \ \"acc_stderr\": 0.03874371556587953,\n \"acc_norm\": 0.5481927710843374,\n\ \ \"acc_norm_stderr\": 0.03874371556587953\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.8245614035087719,\n \"acc_stderr\": 0.029170885500727665,\n\ \ \"acc_norm\": 0.8245614035087719,\n \"acc_norm_stderr\": 0.029170885500727665\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.5385556915544676,\n\ \ \"mc1_stderr\": 0.017451384104637452,\n \"mc2\": 0.6686090881936299,\n\ \ \"mc2_stderr\": 0.015322918299770005\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.8224151539068666,\n \"acc_stderr\": 0.010740676861359237\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.7065959059893859,\n \ \ \"acc_stderr\": 0.012541830815461487\n }\n}\n```" repo_url: https://huggingface.co/mncai/mistral-7b-dpo-v5 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_16T17_06_29.601004 path: - '/details_harness\|arc:challenge\|25_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-12-16T17-06-29.601004.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|gsm8k\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hellaswag\|10_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-16T17-06-29.601004.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-management\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|truthfulqa:mc\|0_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-12-16T17-06-29.601004.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '/details_harness\|winogrande\|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-12-16T17-06-29.601004.parquet' - config_name: results data_files: - split: 2023_12_16T17_06_29.601004 path: - results_2023-12-16T17-06-29.601004.parquet - split: latest path: - results_2023-12-16T17-06-29.601004.parquet --- # Dataset Card for Evaluation run of mncai/mistral-7b-dpo-v5 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [mncai/mistral-7b-dpo-v5](https://huggingface.co/mncai/mistral-7b-dpo-v5) 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_mncai__mistral-7b-dpo-v5", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-16T17:06:29.601004](https://huggingface.co/datasets/open-llm-leaderboard/details_mncai__mistral-7b-dpo-v5/blob/main/results_2023-12-16T17-06-29.601004.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": 0.6444771644137858, "acc_stderr": 0.032189712118428256, "acc_norm": 0.6439145631454195, "acc_norm_stderr": 0.03285791543982518, "mc1": 0.5385556915544676, "mc1_stderr": 0.017451384104637452, "mc2": 0.6686090881936299, "mc2_stderr": 0.015322918299770005 }, "harness\|arc:challenge\|25": { "acc": 0.6911262798634812, "acc_stderr": 0.013501770929344, "acc_norm": 0.7201365187713311, "acc_norm_stderr": 0.01311904089772592 }, "harness\|hellaswag\|10": { "acc": 0.6978689504082852, "acc_stderr": 0.004582433109636476, "acc_norm": 0.8757219677355108, "acc_norm_stderr": 0.003292242543637345 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.6370370370370371, "acc_stderr": 0.04153948404742398, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.04153948404742398 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.6907894736842105, "acc_stderr": 0.037610708698674805, "acc_norm": 0.6907894736842105, "acc_norm_stderr": 0.037610708698674805 }, "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": 0.6943396226415094, "acc_stderr": 0.028353298073322666, "acc_norm": 0.6943396226415094, "acc_norm_stderr": 0.028353298073322666 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.7361111111111112, "acc_stderr": 0.03685651095897532, "acc_norm": 0.7361111111111112, "acc_norm_stderr": 0.03685651095897532 }, "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": 0.55, "acc_stderr": 0.05, "acc_norm": 0.55, "acc_norm_stderr": 0.05 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "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": 0.78, "acc_stderr": 0.04163331998932263, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932263 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.5531914893617021, "acc_stderr": 0.0325005368436584, "acc_norm": 0.5531914893617021, "acc_norm_stderr": 0.0325005368436584 }, "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": 0.5724137931034483, "acc_stderr": 0.04122737111370332, "acc_norm": 0.5724137931034483, "acc_norm_stderr": 0.04122737111370332 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.42063492063492064, "acc_stderr": 0.025424835086923996, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.025424835086923996 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.4365079365079365, "acc_stderr": 0.04435932892851466, "acc_norm": 0.4365079365079365, "acc_norm_stderr": 0.04435932892851466 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.7935483870967742, "acc_stderr": 0.023025899617188716, "acc_norm": 0.7935483870967742, "acc_norm_stderr": 0.023025899617188716 }, "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": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "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": 0.7929292929292929, "acc_stderr": 0.028869778460267042, "acc_norm": 0.7929292929292929, "acc_norm_stderr": 0.028869778460267042 }, "harness\|hendrycksTest-high_school_government_and_politics\|5": { "acc": 0.8808290155440415, "acc_stderr": 0.02338193534812143, "acc_norm": 0.8808290155440415, "acc_norm_stderr": 0.02338193534812143 }, "harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.6487179487179487, "acc_stderr": 0.024203665177902803, "acc_norm": 0.6487179487179487, "acc_norm_stderr": 0.024203665177902803 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.3037037037037037, "acc_stderr": 0.028037929969114993, "acc_norm": 0.3037037037037037, "acc_norm_stderr": 0.028037929969114993 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.634453781512605, "acc_stderr": 0.031282177063684614, "acc_norm": 0.634453781512605, "acc_norm_stderr": 0.031282177063684614 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.31125827814569534, "acc_stderr": 0.03780445850526732, "acc_norm": 0.31125827814569534, "acc_norm_stderr": 0.03780445850526732 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.8403669724770643, "acc_stderr": 0.015703498348461766, "acc_norm": 0.8403669724770643, "acc_norm_stderr": 0.015703498348461766 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.49537037037037035, "acc_stderr": 0.03409825519163572, "acc_norm": 0.49537037037037035, "acc_norm_stderr": 0.03409825519163572 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.8088235294117647, "acc_stderr": 0.027599174300640766, "acc_norm": 0.8088235294117647, "acc_norm_stderr": 0.027599174300640766 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.7763713080168776, "acc_stderr": 0.027123298205229962, "acc_norm": 0.7763713080168776, "acc_norm_stderr": 0.027123298205229962 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.695067264573991, "acc_stderr": 0.030898610882477515, "acc_norm": 0.695067264573991, "acc_norm_stderr": 0.030898610882477515 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.7786259541984732, "acc_stderr": 0.03641297081313729, "acc_norm": 0.7786259541984732, "acc_norm_stderr": 0.03641297081313729 }, "harness\|hendrycksTest-international_law\|5": { "acc": 0.768595041322314, "acc_stderr": 0.038498560987940904, "acc_norm": 0.768595041322314, "acc_norm_stderr": 0.038498560987940904 }, "harness\|hendrycksTest-jurisprudence\|5": { "acc": 0.7592592592592593, "acc_stderr": 0.04133119440243839, "acc_norm": 0.7592592592592593, "acc_norm_stderr": 0.04133119440243839 }, "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": 0.4642857142857143, "acc_stderr": 0.04733667890053756, "acc_norm": 0.4642857142857143, "acc_norm_stderr": 0.04733667890053756 }, "harness\|hendrycksTest-management\|5": { "acc": 0.7864077669902912, "acc_stderr": 0.040580420156460344, "acc_norm": 0.7864077669902912, "acc_norm_stderr": 0.040580420156460344 }, "harness\|hendrycksTest-marketing\|5": { "acc": 0.8846153846153846, "acc_stderr": 0.020930193185179326, "acc_norm": 0.8846153846153846, "acc_norm_stderr": 0.020930193185179326 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.68, "acc_stderr": 0.046882617226215034, "acc_norm": 0.68, "acc_norm_stderr": 0.046882617226215034 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.8301404853128991, "acc_stderr": 0.013428186370608311, "acc_norm": 0.8301404853128991, "acc_norm_stderr": 0.013428186370608311 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.7398843930635838, "acc_stderr": 0.023618678310069356, "acc_norm": 0.7398843930635838, "acc_norm_stderr": 0.023618678310069356 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.4480446927374302, "acc_stderr": 0.016631976628930595, "acc_norm": 0.4480446927374302, "acc_norm_stderr": 0.016631976628930595 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.7189542483660131, "acc_stderr": 0.025738854797818737, "acc_norm": 0.7189542483660131, "acc_norm_stderr": 0.025738854797818737 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.7138263665594855, "acc_stderr": 0.025670259242188933, "acc_norm": 0.7138263665594855, "acc_norm_stderr": 0.025670259242188933 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.75, "acc_stderr": 0.02409347123262133, "acc_norm": 0.75, "acc_norm_stderr": 0.02409347123262133 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.4858156028368794, "acc_stderr": 0.02981549448368206, "acc_norm": 0.4858156028368794, "acc_norm_stderr": 0.02981549448368206 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.46479791395045633, "acc_stderr": 0.012738547371303957, "acc_norm": 0.46479791395045633, "acc_norm_stderr": 0.012738547371303957 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.6544117647058824, "acc_stderr": 0.02888819310398863, "acc_norm": 0.6544117647058824, "acc_norm_stderr": 0.02888819310398863 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.6617647058823529, "acc_stderr": 0.01913994374848704, "acc_norm": 0.6617647058823529, "acc_norm_stderr": 0.01913994374848704 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.6545454545454545, "acc_stderr": 0.04554619617541054, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.04554619617541054 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.7183673469387755, "acc_stderr": 0.028795185574291293, "acc_norm": 0.7183673469387755, "acc_norm_stderr": 0.028795185574291293 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.8407960199004975, "acc_stderr": 0.025870646766169146, "acc_norm": 0.8407960199004975, "acc_norm_stderr": 0.025870646766169146 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.89, "acc_stderr": 0.03144660377352202, "acc_norm": 0.89, "acc_norm_stderr": 0.03144660377352202 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.5481927710843374, "acc_stderr": 0.03874371556587953, "acc_norm": 0.5481927710843374, "acc_norm_stderr": 0.03874371556587953 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.8245614035087719, "acc_stderr": 0.029170885500727665, "acc_norm": 0.8245614035087719, "acc_norm_stderr": 0.029170885500727665 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.5385556915544676, "mc1_stderr": 0.017451384104637452, "mc2": 0.6686090881936299, "mc2_stderr": 0.015322918299770005 }, "harness\|winogrande\|5": { "acc": 0.8224151539068666, "acc_stderr": 0.010740676861359237 }, "harness\|gsm8k\|5": { "acc": 0.7065959059893859, "acc_stderr": 0.012541830815461487 } } ``` ## 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 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It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). 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]
CognitiveLab/hh-rlhf-formatted-10000	--- dataset_info: features: - name: prompt dtype: string - name: chosen dtype: string - name: rejected dtype: string splits: - name: train num_bytes: 14489586 num_examples: 10000 download_size: 7538920 dataset_size: 14489586 configs: - config_name: default data_files: - split: train path: data/train-* ---
nanaaaa/emotion_chinese_english	--- task_categories: - text-classification language: - zh - en ---
bongsoo/kowiki20220620	--- language: - ko license: apache-2.0 --- -kowiki202206 1줄 말뭉치
pszemraj/text2image-multi-prompt	--- language: - en license: apache-2.0 multilinguality: - monolingual source_datasets: - bartman081523/stable-diffusion-discord-prompts - succinctly/midjourney-prompts - Gustavosta/Stable-Diffusion-Prompts pretty_name: multi text2image prompts a dataset collection tags: - text generation configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - config_name: original data_files: - split: train path: original/train-* - split: test path: original/test-* dataset_info: - config_name: default features: - name: text dtype: string - name: src_dataset dtype: string splits: - name: train num_bytes: 262736830 num_examples: 1677221 - name: test num_bytes: 56294291 num_examples: 292876 download_size: 151054782 dataset_size: 319031121 - config_name: original features: - name: text dtype: string - name: src_dataset dtype: string splits: - name: train num_bytes: 741427383 num_examples: 3551734 - name: test num_bytes: 83615440 num_examples: 399393 download_size: 402186258 dataset_size: 825042823 task_categories: - text-generation - feature-extraction --- # text2image multi-prompt(s): a dataset collection - collection of several text2image prompt datasets - data was cleaned/normalized with the goal of removing "model specific APIs" like the "--ar" for Midjourney and so on - data de-duplicated on a basic level: exactly duplicate prompts were dropped (_after cleaning and normalization_) ## updates - Oct 2023: the `default` config has been updated with better deduplication. It was deduplicated with minhash (_params: n-gram size set to 3, deduplication threshold at 0.6, hash function chosen as xxh3 with 32-bit hash bits, and 128 permutations with a batch size of 10,000._) which drops 2+ million rows. - original version is still available under `config_name="original"` ## contents default: ``` DatasetDict({ train: Dataset({ features: ['text', 'src_dataset'], num_rows: 1677221 }) test: Dataset({ features: ['text', 'src_dataset'], num_rows: 292876 }) }) ``` For `original` config: ``` DatasetDict({ train: Dataset({ features: ['text', 'src_dataset'], num_rows: 3551734 }) test: Dataset({ features: ['text', 'src_dataset'], num_rows: 399393 }) }) ``` _NOTE: as the other two datasets did not have a `validation` split, the validation split of `succinctly/midjourney-prompts` was merged into `train`._
joey234/mmlu-high_school_biology-dev	--- dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: negate_openai_prompt struct: - name: content dtype: string - name: role dtype: string splits: - name: dev num_bytes: 3234 num_examples: 5 download_size: 0 dataset_size: 3234 --- # Dataset Card for "mmlu-high_school_biology-dev" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
NLPC-UOM/nllb-top25k-ensi-cleaned	--- license: odc-by task_categories: - translation language: - en - si size_categories: - 10K<n<100K --- ### Licensing Information The dataset is released under the terms of [ODC-BY](https://opendatacommons.org/licenses/by/1-0/). By using this, you are also bound to the respective Terms of Use and License of the original source. ### Citation Information Schwenk et al, CCMatrix: Mining Billions of High-Quality Parallel Sentences on the Web. ACL https://aclanthology.org/2021.acl-long.507/ Hefferman et al, Bitext Mining Using Distilled Sentence Representations for Low-Resource Languages. Arxiv https://arxiv.org/abs/2205.12654, 2022.<br> NLLB Team et al, No Language Left Behind: Scaling Human-Centered Machine Translation, Arxiv https://arxiv.org/abs/2207.04672, 2022. ### Contributions We thank the NLLB Meta AI team for open sourcing the meta data and instructions on how to use it with special thanks to Bapi Akula, Pierre Andrews, Onur Çelebi, Sergey Edunov, Kenneth Heafield, Philipp Koehn, Alex Mourachko, Safiyyah Saleem, Holger Schwenk, and Guillaume Wenzek. We also thank the AllenNLP team at AI2 for hosting and releasing this data, including Akshita Bhagia (for engineering efforts to host the data, and create the huggingface dataset), and Jesse Dodge (for organizing the connection).
maghwa/OpenHermes-2-AR-10K-7	--- dataset_info: features: - name: custom_instruction dtype: 'null' - name: system_prompt dtype: 'null' - name: avatarUrl dtype: 'null' - name: conversations dtype: string - name: topic dtype: 'null' - name: views dtype: float64 - name: model dtype: 'null' - name: id dtype: string - name: hash dtype: 'null' - name: title dtype: 'null' - name: model_name dtype: 'null' - name: idx dtype: 'null' - name: skip_prompt_formatting dtype: 'null' - name: category dtype: 'null' - name: source dtype: string - name: language dtype: 'null' splits: - name: train num_bytes: 25327870 num_examples: 10001 download_size: 9643427 dataset_size: 25327870 configs: - config_name: default data_files: - split: train path: data/train-* ---
tyzhu/lmind_hotpot_train1000_eval500_v1_recite_qa	--- configs: - config_name: default data_files: - split: train_qa path: data/train_qa-* - split: train_recite_qa path: data/train_recite_qa-* - split: eval_qa path: data/eval_qa-* - split: eval_recite_qa path: data/eval_recite_qa-* - split: all_docs path: data/all_docs-* - split: all_docs_eval path: data/all_docs_eval-* - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: inputs dtype: string - name: targets dtype: string - name: answers struct: - name: answer_start sequence: 'null' - name: text sequence: string splits: - name: train_qa num_bytes: 173266 num_examples: 1000 - name: train_recite_qa num_bytes: 1052784 num_examples: 1000 - name: eval_qa num_bytes: 81677 num_examples: 500 - name: eval_recite_qa num_bytes: 542914 num_examples: 500 - name: all_docs num_bytes: 1370698 num_examples: 2959 - name: all_docs_eval num_bytes: 1370509 num_examples: 2959 - name: train num_bytes: 2423482 num_examples: 3959 - name: validation num_bytes: 542914 num_examples: 500 download_size: 4626743 dataset_size: 7558244 --- # Dataset Card for "lmind_hotpot_train1000_eval500_v1_recite_qa" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
giuseppemartino/isaid_sam_predicted	--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: image dtype: image - name: label dtype: image splits: - name: train num_bytes: 6757890501.0 num_examples: 899 - name: validation num_bytes: 152972321.0 num_examples: 17 download_size: 152947587 dataset_size: 6910862822.0 --- # Dataset Card for "isaid_sam_predicted" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
baylitoo/alpacaa	--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: text dtype: string splits: - name: train num_bytes: 888593.1887235106 num_examples: 1000 download_size: 0 dataset_size: 888593.1887235106 --- # Dataset Card for "alpacaa" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
open-llm-leaderboard/details_FelixChao__llama2-13b-math1.2	--- pretty_name: Evaluation run of FelixChao/llama2-13b-math1.2 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [FelixChao/llama2-13b-math1.2](https://huggingface.co/FelixChao/llama2-13b-math1.2)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 3 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_FelixChao__llama2-13b-math1.2\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-17T02:02:50.506714](https://huggingface.co/datasets/open-llm-leaderboard/details_FelixChao__llama2-13b-math1.2/blob/main/results_2023-10-17T02-02-50.506714.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\": 0.08536073825503356,\n\ \ \"em_stderr\": 0.002861499356149465,\n \"f1\": 0.16235318791946293,\n\ \ \"f1_stderr\": 0.003133455634092774,\n \"acc\": 0.4263155280751903,\n\ \ \"acc_stderr\": 0.010451092603365564\n },\n \"harness\|drop\|3\": {\n\ \ \"em\": 0.08536073825503356,\n \"em_stderr\": 0.002861499356149465,\n\ \ \"f1\": 0.16235318791946293,\n \"f1_stderr\": 0.003133455634092774\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.10993176648976498,\n \ \ \"acc_stderr\": 0.008616195587865416\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.7426992896606156,\n \"acc_stderr\": 0.012285989618865713\n\ \ }\n}\n```" repo_url: https://huggingface.co/FelixChao/llama2-13b-math1.2 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|arc:challenge\|25_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-08-18T11:24:31.239858.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_16T16_38_50.665467 path: - '/details_harness\|drop\|3_2023-10-16T16-38-50.665467.parquet' - split: 2023_10_17T02_02_50.506714 path: - '/details_harness\|drop\|3_2023-10-17T02-02-50.506714.parquet' - split: latest path: - '/details_harness\|drop\|3_2023-10-17T02-02-50.506714.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_16T16_38_50.665467 path: - '/details_harness\|gsm8k\|5_2023-10-16T16-38-50.665467.parquet' - split: 2023_10_17T02_02_50.506714 path: - '/details_harness\|gsm8k\|5_2023-10-17T02-02-50.506714.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-10-17T02-02-50.506714.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hellaswag\|10_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-08-18T11:24:31.239858.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-management\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_18T11_24_31.239858 path: - '/details_harness\|truthfulqa:mc\|0_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-08-18T11:24:31.239858.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_16T16_38_50.665467 path: - '/details_harness\|winogrande\|5_2023-10-16T16-38-50.665467.parquet' - split: 2023_10_17T02_02_50.506714 path: - '/details_harness\|winogrande\|5_2023-10-17T02-02-50.506714.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-10-17T02-02-50.506714.parquet' - config_name: results data_files: - split: 2023_08_18T11_24_31.239858 path: - results_2023-08-18T11:24:31.239858.parquet - split: 2023_10_16T16_38_50.665467 path: - results_2023-10-16T16-38-50.665467.parquet - split: 2023_10_17T02_02_50.506714 path: - results_2023-10-17T02-02-50.506714.parquet - split: latest path: - results_2023-10-17T02-02-50.506714.parquet --- # Dataset Card for Evaluation run of FelixChao/llama2-13b-math1.2 ## Dataset Description - Homepage: - Repository: https://huggingface.co/FelixChao/llama2-13b-math1.2 - 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 [FelixChao/llama2-13b-math1.2](https://huggingface.co/FelixChao/llama2-13b-math1.2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 3 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_FelixChao__llama2-13b-math1.2", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-17T02:02:50.506714](https://huggingface.co/datasets/open-llm-leaderboard/details_FelixChao__llama2-13b-math1.2/blob/main/results_2023-10-17T02-02-50.506714.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": 0.08536073825503356, "em_stderr": 0.002861499356149465, "f1": 0.16235318791946293, "f1_stderr": 0.003133455634092774, "acc": 0.4263155280751903, "acc_stderr": 0.010451092603365564 }, "harness\|drop\|3": { "em": 0.08536073825503356, "em_stderr": 0.002861499356149465, "f1": 0.16235318791946293, "f1_stderr": 0.003133455634092774 }, "harness\|gsm8k\|5": { "acc": 0.10993176648976498, "acc_stderr": 0.008616195587865416 }, "harness\|winogrande\|5": { "acc": 0.7426992896606156, "acc_stderr": 0.012285989618865713 } } ``` ### 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]
chathuranga-jayanath/context-5-finmath-times4j-html-mavendoxia-wro4j-guava-supercsv-len-1000-prompt-2	--- dataset_info: features: - name: id dtype: int64 - name: filepath dtype: string - name: start_bug_line dtype: int64 - name: end_bug_line dtype: int64 - name: bug dtype: string - name: fix dtype: string - name: ctx dtype: string splits: - name: train num_bytes: 5510268 num_examples: 5105 - name: validation num_bytes: 672859 num_examples: 637 - name: test num_bytes: 672684 num_examples: 637 download_size: 2623280 dataset_size: 6855811 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
vinny9812/audiobrunogiglio	--- license: openrail ---
TwoAbove/gpt4v-emotion-dataset	--- dataset_info: features: - name: caption dtype: string - name: image dtype: image - name: link dtype: string - name: message_id dtype: string - name: timestamp dtype: string splits: - name: train num_bytes: 51420737.0 num_examples: 48 download_size: 51389687 dataset_size: 51420737.0 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "gpt4v-emotion-dataset" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
tnet-devs/demo_inc	--- license: cc-by-nc-nd-4.0 ---
ID3/comentarios_youtube_validos_similitud	--- dataset_info: features: - name: comentario dtype: string - name: likes dtype: int64 - name: similitud dtype: float64 - name: id dtype: string splits: - name: train num_bytes: 83527097 num_examples: 652388 download_size: 54010613 dataset_size: 83527097 --- # Dataset Card for "comentarios_youtube_validos_similitud" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
lilacai/lilac-OpenOrca	--- tags: - Lilac --- # lilac/OpenOrca This dataset is a [Lilac](http://lilacml.com) processed dataset. Original dataset: [https://huggingface.co/datasets/Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca) To download the dataset to a local directory: ```bash lilac download lilacai/lilac-OpenOrca ``` or from python with: ```py ll.download("lilacai/lilac-OpenOrca") ```
CyberHarem/noah_nikke	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of noah/ノア/诺雅/노아 (Nikke: Goddess of Victory) This is the dataset of noah/ノア/诺雅/노아 (Nikke: Goddess of Victory), containing 23 images and their tags. The core tags of this character are `pink_hair, short_hair, pink_eyes, hair_ornament, bangs, breasts`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages \| Name \| Images \| Size \| Download \| Type \| Description \| \|:-----------------\|---------:\|:----------\|:------------------------------------------------------------------------------------------------------------\|:-----------\|:---------------------------------------------------------------------\| \| raw \| 23 \| 29.38 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/noah_nikke/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 23 \| 13.94 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/noah_nikke/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 64 \| 36.91 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/noah_nikke/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 23 \| 24.46 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/noah_nikke/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 64 \| 55.19 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/noah_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/noah_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 \| 23 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| 1girl, looking_at_viewer, solo, smile, open_mouth, blush, armor, white_background, bodysuit, fingerless_gloves, simple_background \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| looking_at_viewer \| solo \| smile \| open_mouth \| blush \| armor \| white_background \| bodysuit \| fingerless_gloves \| simple_background \| \|----:\|----------:\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------------------------------\|:--------\|:--------------------\|:-------\|:--------\|:-------------\|:--------\|:--------\|:-------------------\|:-----------\|:--------------------\|:--------------------\| \| 0 \| 23 \| ![](samples/0/clu0-sample0.png) \| ![](samples/0/clu0-sample1.png) \| ![](samples/0/clu0-sample2.png) \| ![](samples/0/clu0-sample3.png) \| ![](samples/0/clu0-sample4.png) \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \| X \|
KaiLv/UDR_Go	--- dataset_info: features: - name: idx dtype: int64 - name: question dtype: string - name: target dtype: string - name: len_question dtype: int64 - name: len_target dtype: int64 splits: - name: train num_bytes: 89583705 num_examples: 167137 - name: validation num_bytes: 3547138 num_examples: 7320 - name: test num_bytes: 4244257 num_examples: 8115 - name: debug num_bytes: 53690904 num_examples: 100000 download_size: 66725224 dataset_size: 151066004 --- # Dataset Card for "UDR_Go_new" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Ilia-Iliev/example_captioner	--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 2788504.0 num_examples: 15 - name: validation num_bytes: 914115.0 num_examples: 5 download_size: 3693983 dataset_size: 3702619.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---
open-llm-leaderboard/details_mwitiderrick__open_llama_3b_glaive_v0.1	--- pretty_name: Evaluation run of mwitiderrick/open_llama_3b_glaive_v0.1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mwitiderrick/open_llama_3b_glaive_v0.1](https://huggingface.co/mwitiderrick/open_llama_3b_glaive_v0.1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_mwitiderrick__open_llama_3b_glaive_v0.1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-23T15:34:19.150703](https://huggingface.co/datasets/open-llm-leaderboard/details_mwitiderrick__open_llama_3b_glaive_v0.1/blob/main/results_2023-12-23T15-34-19.150703.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\": 0.2843747535406573,\n\ \ \"acc_stderr\": 0.031689110133124844,\n \"acc_norm\": 0.28633888958645765,\n\ \ \"acc_norm_stderr\": 0.03246963675970039,\n \"mc1\": 0.23623011015911874,\n\ \ \"mc1_stderr\": 0.014869755015871114,\n \"mc2\": 0.3585983664640556,\n\ \ \"mc2_stderr\": 0.013742745779138914\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.3703071672354949,\n \"acc_stderr\": 0.01411129875167495,\n\ \ \"acc_norm\": 0.4069965870307167,\n \"acc_norm_stderr\": 0.014356399418009131\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.4971121290579566,\n\ \ \"acc_stderr\": 0.004989698183207831,\n \"acc_norm\": 0.6744672376020713,\n\ \ \"acc_norm_stderr\": 0.004676159299105414\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.047258156262526045\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.2814814814814815,\n\ \ \"acc_stderr\": 0.03885004245800254,\n \"acc_norm\": 0.2814814814814815,\n\ \ \"acc_norm_stderr\": 0.03885004245800254\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.21052631578947367,\n \"acc_stderr\": 0.03317672787533157,\n\ \ \"acc_norm\": 0.21052631578947367,\n \"acc_norm_stderr\": 0.03317672787533157\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.27,\n\ \ \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\": 0.27,\n \ \ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.29056603773584905,\n \"acc_stderr\": 0.027943219989337156,\n\ \ \"acc_norm\": 0.29056603773584905,\n \"acc_norm_stderr\": 0.027943219989337156\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.2638888888888889,\n\ \ \"acc_stderr\": 0.03685651095897532,\n \"acc_norm\": 0.2638888888888889,\n\ \ \"acc_norm_stderr\": 0.03685651095897532\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816505,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.04229525846816505\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|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_mathematics\|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.044084400227680794,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.044084400227680794\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.3236994219653179,\n\ \ \"acc_stderr\": 0.035676037996391685,\n \"acc_norm\": 0.3236994219653179,\n\ \ \"acc_norm_stderr\": 0.035676037996391685\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.20588235294117646,\n \"acc_stderr\": 0.04023382273617749,\n\ \ \"acc_norm\": 0.20588235294117646,\n \"acc_norm_stderr\": 0.04023382273617749\n\ \ },\n \"harness\|hendrycksTest-computer_security\|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-conceptual_physics\|5\"\ : {\n \"acc\": 0.3148936170212766,\n \"acc_stderr\": 0.030363582197238167,\n\ \ \"acc_norm\": 0.3148936170212766,\n \"acc_norm_stderr\": 0.030363582197238167\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.044346007015849245,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.044346007015849245\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.27586206896551724,\n \"acc_stderr\": 0.037245636197746325,\n\ \ \"acc_norm\": 0.27586206896551724,\n \"acc_norm_stderr\": 0.037245636197746325\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.25396825396825395,\n \"acc_stderr\": 0.022418042891113932,\n \"\ acc_norm\": 0.25396825396825395,\n \"acc_norm_stderr\": 0.022418042891113932\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.20634920634920634,\n\ \ \"acc_stderr\": 0.03619604524124252,\n \"acc_norm\": 0.20634920634920634,\n\ \ \"acc_norm_stderr\": 0.03619604524124252\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\": 0.2645161290322581,\n\ \ \"acc_stderr\": 0.02509189237885928,\n \"acc_norm\": 0.2645161290322581,\n\ \ \"acc_norm_stderr\": 0.02509189237885928\n },\n \"harness\|hendrycksTest-high_school_chemistry\|5\"\ : {\n \"acc\": 0.30049261083743845,\n \"acc_stderr\": 0.03225799476233484,\n\ \ \"acc_norm\": 0.30049261083743845,\n \"acc_norm_stderr\": 0.03225799476233484\n\ \ },\n \"harness\|hendrycksTest-high_school_computer_science\|5\": {\n \ \ \"acc\": 0.15,\n \"acc_stderr\": 0.035887028128263714,\n \"acc_norm\"\ : 0.15,\n \"acc_norm_stderr\": 0.035887028128263714\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.26666666666666666,\n \"acc_stderr\": 0.034531318018854146,\n\ \ \"acc_norm\": 0.26666666666666666,\n \"acc_norm_stderr\": 0.034531318018854146\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.31313131313131315,\n \"acc_stderr\": 0.03304205087813653,\n \"\ acc_norm\": 0.31313131313131315,\n \"acc_norm_stderr\": 0.03304205087813653\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.27461139896373055,\n \"acc_stderr\": 0.03221024508041154,\n\ \ \"acc_norm\": 0.27461139896373055,\n \"acc_norm_stderr\": 0.03221024508041154\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.32564102564102565,\n \"acc_stderr\": 0.02375966576741229,\n\ \ \"acc_norm\": 0.32564102564102565,\n \"acc_norm_stderr\": 0.02375966576741229\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.2518518518518518,\n \"acc_stderr\": 0.02646611753895991,\n \ \ \"acc_norm\": 0.2518518518518518,\n \"acc_norm_stderr\": 0.02646611753895991\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.2773109243697479,\n \"acc_stderr\": 0.029079374539480007,\n\ \ \"acc_norm\": 0.2773109243697479,\n \"acc_norm_stderr\": 0.029079374539480007\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.26490066225165565,\n \"acc_stderr\": 0.03603038545360383,\n \"\ acc_norm\": 0.26490066225165565,\n \"acc_norm_stderr\": 0.03603038545360383\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.27339449541284405,\n \"acc_stderr\": 0.019109299846098275,\n \"\ acc_norm\": 0.27339449541284405,\n \"acc_norm_stderr\": 0.019109299846098275\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\": 0.24019607843137256,\n\ \ \"acc_stderr\": 0.02998373305591361,\n \"acc_norm\": 0.24019607843137256,\n\ \ \"acc_norm_stderr\": 0.02998373305591361\n },\n \"harness\|hendrycksTest-high_school_world_history\|5\"\ : {\n \"acc\": 0.25316455696202533,\n \"acc_stderr\": 0.028304657943035303,\n\ \ \"acc_norm\": 0.25316455696202533,\n \"acc_norm_stderr\": 0.028304657943035303\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.3452914798206278,\n\ \ \"acc_stderr\": 0.03191100192835794,\n \"acc_norm\": 0.3452914798206278,\n\ \ \"acc_norm_stderr\": 0.03191100192835794\n },\n \"harness\|hendrycksTest-human_sexuality\|5\"\ : {\n \"acc\": 0.22137404580152673,\n \"acc_stderr\": 0.03641297081313728,\n\ \ \"acc_norm\": 0.22137404580152673,\n \"acc_norm_stderr\": 0.03641297081313728\n\ \ },\n \"harness\|hendrycksTest-international_law\|5\": {\n \"acc\":\ \ 0.2975206611570248,\n \"acc_stderr\": 0.041733491480834974,\n \"\ acc_norm\": 0.2975206611570248,\n \"acc_norm_stderr\": 0.041733491480834974\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.28703703703703703,\n\ \ \"acc_stderr\": 0.043733130409147614,\n \"acc_norm\": 0.28703703703703703,\n\ \ \"acc_norm_stderr\": 0.043733130409147614\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.26993865030674846,\n \"acc_stderr\": 0.034878251684978906,\n\ \ \"acc_norm\": 0.26993865030674846,\n \"acc_norm_stderr\": 0.034878251684978906\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.26785714285714285,\n\ \ \"acc_stderr\": 0.04203277291467764,\n \"acc_norm\": 0.26785714285714285,\n\ \ \"acc_norm_stderr\": 0.04203277291467764\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.2524271844660194,\n \"acc_stderr\": 0.04301250399690877,\n\ \ \"acc_norm\": 0.2524271844660194,\n \"acc_norm_stderr\": 0.04301250399690877\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.2692307692307692,\n\ \ \"acc_stderr\": 0.02905858830374884,\n \"acc_norm\": 0.2692307692307692,\n\ \ \"acc_norm_stderr\": 0.02905858830374884\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.28991060025542786,\n\ \ \"acc_stderr\": 0.016225017944770957,\n \"acc_norm\": 0.28991060025542786,\n\ \ \"acc_norm_stderr\": 0.016225017944770957\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.25722543352601157,\n \"acc_stderr\": 0.02353292543104428,\n\ \ \"acc_norm\": 0.25722543352601157,\n \"acc_norm_stderr\": 0.02353292543104428\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.24692737430167597,\n\ \ \"acc_stderr\": 0.014422292204808835,\n \"acc_norm\": 0.24692737430167597,\n\ \ \"acc_norm_stderr\": 0.014422292204808835\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.27124183006535946,\n \"acc_stderr\": 0.025457756696667878,\n\ \ \"acc_norm\": 0.27124183006535946,\n \"acc_norm_stderr\": 0.025457756696667878\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.3183279742765273,\n\ \ \"acc_stderr\": 0.026457225067811032,\n \"acc_norm\": 0.3183279742765273,\n\ \ \"acc_norm_stderr\": 0.026457225067811032\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.2839506172839506,\n \"acc_stderr\": 0.025089478523765134,\n\ \ \"acc_norm\": 0.2839506172839506,\n \"acc_norm_stderr\": 0.025089478523765134\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.25177304964539005,\n \"acc_stderr\": 0.025892151156709405,\n \ \ \"acc_norm\": 0.25177304964539005,\n \"acc_norm_stderr\": 0.025892151156709405\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.242503259452412,\n\ \ \"acc_stderr\": 0.01094657096634878,\n \"acc_norm\": 0.242503259452412,\n\ \ \"acc_norm_stderr\": 0.01094657096634878\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.4522058823529412,\n \"acc_stderr\": 0.030233758551596455,\n\ \ \"acc_norm\": 0.4522058823529412,\n \"acc_norm_stderr\": 0.030233758551596455\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.24509803921568626,\n \"acc_stderr\": 0.017401816711427657,\n \ \ \"acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.017401816711427657\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.3,\n\ \ \"acc_stderr\": 0.04389311454644286,\n \"acc_norm\": 0.3,\n \ \ \"acc_norm_stderr\": 0.04389311454644286\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.21224489795918366,\n \"acc_stderr\": 0.026176967197866767,\n\ \ \"acc_norm\": 0.21224489795918366,\n \"acc_norm_stderr\": 0.026176967197866767\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.2537313432835821,\n\ \ \"acc_stderr\": 0.03076944496729601,\n \"acc_norm\": 0.2537313432835821,\n\ \ \"acc_norm_stderr\": 0.03076944496729601\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.2891566265060241,\n\ \ \"acc_stderr\": 0.03529486801511115,\n \"acc_norm\": 0.2891566265060241,\n\ \ \"acc_norm_stderr\": 0.03529486801511115\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.26900584795321636,\n \"acc_stderr\": 0.0340105262010409,\n\ \ \"acc_norm\": 0.26900584795321636,\n \"acc_norm_stderr\": 0.0340105262010409\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.23623011015911874,\n\ \ \"mc1_stderr\": 0.014869755015871114,\n \"mc2\": 0.3585983664640556,\n\ \ \"mc2_stderr\": 0.013742745779138914\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.6471981057616417,\n \"acc_stderr\": 0.013429728101788961\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.019711902956785442,\n \ \ \"acc_stderr\": 0.003828982978735702\n }\n}\n```" repo_url: https://huggingface.co/mwitiderrick/open_llama_3b_glaive_v0.1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|arc:challenge\|25_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2023-12-23T15-34-19.150703.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|gsm8k\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hellaswag\|10_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-management\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-virology\|5_2023-12-23T15-34-19.150703.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-management\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|truthfulqa:mc\|0_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2023-12-23T15-34-19.150703.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '/details_harness\|winogrande\|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2023-12-23T15-34-19.150703.parquet' - config_name: results data_files: - split: 2023_12_23T15_34_19.150703 path: - results_2023-12-23T15-34-19.150703.parquet - split: latest path: - results_2023-12-23T15-34-19.150703.parquet --- # Dataset Card for Evaluation run of mwitiderrick/open_llama_3b_glaive_v0.1 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [mwitiderrick/open_llama_3b_glaive_v0.1](https://huggingface.co/mwitiderrick/open_llama_3b_glaive_v0.1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_mwitiderrick__open_llama_3b_glaive_v0.1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-23T15:34:19.150703](https://huggingface.co/datasets/open-llm-leaderboard/details_mwitiderrick__open_llama_3b_glaive_v0.1/blob/main/results_2023-12-23T15-34-19.150703.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": 0.2843747535406573, "acc_stderr": 0.031689110133124844, "acc_norm": 0.28633888958645765, "acc_norm_stderr": 0.03246963675970039, "mc1": 0.23623011015911874, "mc1_stderr": 0.014869755015871114, "mc2": 0.3585983664640556, "mc2_stderr": 0.013742745779138914 }, "harness\|arc:challenge\|25": { "acc": 0.3703071672354949, "acc_stderr": 0.01411129875167495, "acc_norm": 0.4069965870307167, "acc_norm_stderr": 0.014356399418009131 }, "harness\|hellaswag\|10": { "acc": 0.4971121290579566, "acc_stderr": 0.004989698183207831, "acc_norm": 0.6744672376020713, "acc_norm_stderr": 0.004676159299105414 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.2814814814814815, "acc_stderr": 0.03885004245800254, "acc_norm": 0.2814814814814815, "acc_norm_stderr": 0.03885004245800254 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.21052631578947367, "acc_stderr": 0.03317672787533157, "acc_norm": 0.21052631578947367, "acc_norm_stderr": 0.03317672787533157 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.29056603773584905, "acc_stderr": 0.027943219989337156, "acc_norm": 0.29056603773584905, "acc_norm_stderr": 0.027943219989337156 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.2638888888888889, "acc_stderr": 0.03685651095897532, "acc_norm": 0.2638888888888889, "acc_norm_stderr": 0.03685651095897532 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.23, "acc_stderr": 0.04229525846816505, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816505 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.26, "acc_stderr": 0.044084400227680794, "acc_norm": 0.26, "acc_norm_stderr": 0.044084400227680794 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.3236994219653179, "acc_stderr": 0.035676037996391685, "acc_norm": 0.3236994219653179, "acc_norm_stderr": 0.035676037996391685 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.20588235294117646, "acc_stderr": 0.04023382273617749, "acc_norm": 0.20588235294117646, "acc_norm_stderr": 0.04023382273617749 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.3148936170212766, "acc_stderr": 0.030363582197238167, "acc_norm": 0.3148936170212766, "acc_norm_stderr": 0.030363582197238167 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 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"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": 0.24019607843137256, "acc_stderr": 0.02998373305591361, "acc_norm": 0.24019607843137256, "acc_norm_stderr": 0.02998373305591361 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.25316455696202533, "acc_stderr": 0.028304657943035303, "acc_norm": 0.25316455696202533, "acc_norm_stderr": 0.028304657943035303 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.3452914798206278, "acc_stderr": 0.03191100192835794, "acc_norm": 0.3452914798206278, "acc_norm_stderr": 0.03191100192835794 }, "harness\|hendrycksTest-human_sexuality\|5": { "acc": 0.22137404580152673, "acc_stderr": 0.03641297081313728, "acc_norm": 0.22137404580152673, "acc_norm_stderr": 0.03641297081313728 }, "harness\|hendrycksTest-international_law\|5": { "acc": 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"acc": 0.3183279742765273, "acc_stderr": 0.026457225067811032, "acc_norm": 0.3183279742765273, "acc_norm_stderr": 0.026457225067811032 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.2839506172839506, "acc_stderr": 0.025089478523765134, "acc_norm": 0.2839506172839506, "acc_norm_stderr": 0.025089478523765134 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.25177304964539005, "acc_stderr": 0.025892151156709405, "acc_norm": 0.25177304964539005, "acc_norm_stderr": 0.025892151156709405 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.242503259452412, "acc_stderr": 0.01094657096634878, "acc_norm": 0.242503259452412, "acc_norm_stderr": 0.01094657096634878 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.4522058823529412, "acc_stderr": 0.030233758551596455, "acc_norm": 0.4522058823529412, "acc_norm_stderr": 0.030233758551596455 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.24509803921568626, "acc_stderr": 0.017401816711427657, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.017401816711427657 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.3, "acc_stderr": 0.04389311454644286, "acc_norm": 0.3, "acc_norm_stderr": 0.04389311454644286 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.21224489795918366, "acc_stderr": 0.026176967197866767, "acc_norm": 0.21224489795918366, "acc_norm_stderr": 0.026176967197866767 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.2537313432835821, "acc_stderr": 0.03076944496729601, "acc_norm": 0.2537313432835821, "acc_norm_stderr": 0.03076944496729601 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.2891566265060241, "acc_stderr": 0.03529486801511115, "acc_norm": 0.2891566265060241, "acc_norm_stderr": 0.03529486801511115 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.26900584795321636, "acc_stderr": 0.0340105262010409, "acc_norm": 0.26900584795321636, "acc_norm_stderr": 0.0340105262010409 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.23623011015911874, "mc1_stderr": 0.014869755015871114, "mc2": 0.3585983664640556, "mc2_stderr": 0.013742745779138914 }, "harness\|winogrande\|5": { "acc": 0.6471981057616417, "acc_stderr": 0.013429728101788961 }, "harness\|gsm8k\|5": { "acc": 0.019711902956785442, "acc_stderr": 0.003828982978735702 } } ``` ## 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]: 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mserna/livecell-hf	--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 1016288264.76 num_examples: 4184 download_size: 1003022893 dataset_size: 1016288264.76 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "livecell-hf" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CyberHarem/shichijou_aria_seitokaiyakuindomo	--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Shichijou Aria (Seitokai Yakuindomo) This is the dataset of Shichijou Aria (Seitokai Yakuindomo), containing 891 images and their tags. The core tags of this character are `brown_hair, long_hair, brown_eyes, bow`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages \| Name \| Images \| Size \| Download \| Type \| Description \| \|:-----------------\|---------:\|:-----------\|:-----------------------------------------------------------------------------------------------------------------------------------\|:-----------\|:---------------------------------------------------------------------\| \| raw \| 891 \| 419.53 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/shichijou_aria_seitokaiyakuindomo/resolve/main/dataset-raw.zip) \| Waifuc-Raw \| Raw data with meta information (min edge aligned to 1400 if larger). \| \| 800 \| 891 \| 372.14 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/shichijou_aria_seitokaiyakuindomo/resolve/main/dataset-800.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 800 pixels. \| \| stage3-p480-800 \| 1847 \| 730.95 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/shichijou_aria_seitokaiyakuindomo/resolve/main/dataset-stage3-p480-800.zip) \| IMG+TXT \| 3-stage cropped dataset with the area not less than 480x480 pixels. \| \| 1200 \| 891 \| 419.22 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/shichijou_aria_seitokaiyakuindomo/resolve/main/dataset-1200.zip) \| IMG+TXT \| dataset with the shorter side not exceeding 1200 pixels. \| \| stage3-p480-1200 \| 1847 \| 800.75 MiB \| [Download](https://huggingface.co/datasets/CyberHarem/shichijou_aria_seitokaiyakuindomo/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/shichijou_aria_seitokaiyakuindomo', 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 \| 16 \| ![](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, blazer, school_uniform, solo, smile, closed_eyes \| \| 1 \| 8 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| 1girl, anime_coloring, bowtie, hair_between_eyes, looking_at_viewer, school_uniform, solo, blazer, smile \| \| 2 \| 6 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| 1girl, blazer, bowtie, school_uniform, solo, upper_body, red_bow, smile, hair_between_eyes \| \| 3 \| 9 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| 1girl, blazer, school_uniform, solo, bowtie, smile, upper_body, anime_coloring \| \| 4 \| 12 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| 1girl, blazer, hair_between_eyes, school_uniform, solo, shirt, upper_body, anime_coloring, smile, looking_at_viewer, red_bowtie \| \| 5 \| 20 \| ![](samples/5/clu5-sample0.png) \| ![](samples/5/clu5-sample1.png) \| ![](samples/5/clu5-sample2.png) \| ![](samples/5/clu5-sample3.png) \| ![](samples/5/clu5-sample4.png) \| 1girl, blazer, plaid_skirt, school_uniform, solo, smile \| \| 6 \| 6 \| ![](samples/6/clu6-sample0.png) \| ![](samples/6/clu6-sample1.png) \| ![](samples/6/clu6-sample2.png) \| ![](samples/6/clu6-sample3.png) \| ![](samples/6/clu6-sample4.png) \| 1girl, anime_coloring, dress_shirt, school_uniform, smile, solo, upper_body, bowtie, hair_between_eyes, looking_at_viewer, red_bow, white_shirt \| \| 7 \| 5 \| ![](samples/7/clu7-sample0.png) \| ![](samples/7/clu7-sample1.png) \| ![](samples/7/clu7-sample2.png) \| ![](samples/7/clu7-sample3.png) \| ![](samples/7/clu7-sample4.png) \| 1girl, blazer, collared_shirt, hair_between_eyes, red_bowtie, school_uniform, smile, solo, upper_body, white_shirt, bangs, brown_jacket, closed_mouth, long_sleeves, indoors, looking_at_viewer, wing_collar \| \| 8 \| 5 \| ![](samples/8/clu8-sample0.png) \| ![](samples/8/clu8-sample1.png) \| ![](samples/8/clu8-sample2.png) \| ![](samples/8/clu8-sample3.png) \| ![](samples/8/clu8-sample4.png) \| 1girl, blazer, chair, school_uniform, sitting, solo, red_bowtie, smile, upper_body \| \| 9 \| 9 \| ![](samples/9/clu9-sample0.png) \| ![](samples/9/clu9-sample1.png) \| ![](samples/9/clu9-sample2.png) \| ![](samples/9/clu9-sample3.png) \| ![](samples/9/clu9-sample4.png) \| 1girl, blazer, long_sleeves, plaid_skirt, pleated_skirt, red_bowtie, school_uniform, solo, brown_skirt, indoors, white_shirt, brown_jacket, closed_mouth, collared_shirt, sitting, smile, closed_eyes, folding_chair \| \| 10 \| 6 \| ![](samples/10/clu10-sample0.png) \| ![](samples/10/clu10-sample1.png) \| ![](samples/10/clu10-sample2.png) \| ![](samples/10/clu10-sample3.png) \| ![](samples/10/clu10-sample4.png) \| 2girls, school_uniform, smile, blazer, \|_\| \| \| 11 \| 10 \| ![](samples/11/clu11-sample0.png) \| ![](samples/11/clu11-sample1.png) \| ![](samples/11/clu11-sample2.png) \| ![](samples/11/clu11-sample3.png) \| ![](samples/11/clu11-sample4.png) \| 1girl, solo, \|_\|, simple_background, white_background, upper_body, smile, collarbone, ponytail, hair_between_eyes, shirt \| \| 12 \| 9 \| ![](samples/12/clu12-sample0.png) \| ![](samples/12/clu12-sample1.png) \| ![](samples/12/clu12-sample2.png) \| ![](samples/12/clu12-sample3.png) \| ![](samples/12/clu12-sample4.png) \| 1girl, solo, yukata, ponytail, smile, night_sky \| ### Table Version \| # \| Samples \| Img-1 \| Img-2 \| Img-3 \| Img-4 \| Img-5 \| 1girl \| blazer \| school_uniform \| solo \| smile \| closed_eyes \| anime_coloring \| bowtie \| hair_between_eyes \| looking_at_viewer \| upper_body \| red_bow \| shirt \| red_bowtie \| plaid_skirt \| dress_shirt \| white_shirt \| collared_shirt \| bangs \| brown_jacket \| closed_mouth \| long_sleeves \| indoors \| wing_collar \| chair \| sitting \| pleated_skirt \| brown_skirt \| folding_chair \| 2girls \| \|_\| \| simple_background \| white_background \| collarbone \| ponytail \| yukata \| night_sky \| \|----:\|----------:\|:----------------------------------\|:----------------------------------\|:----------------------------------\|:----------------------------------\|:----------------------------------\|:--------\|:---------\|:-----------------\|:-------\|:--------\|:--------------\|:-----------------\|:---------\|:--------------------\|:--------------------\|:-------------\|:----------\|:--------\|:-------------\|:--------------\|:--------------\|:--------------\|:-----------------\|:--------\|:---------------\|:---------------\|:---------------\|:----------\|:--------------\|:--------\|:----------\|:----------------\|:--------------\|:----------------\|:---------\|:------\|:--------------------\|:-------------------\|:-------------\|:-----------\|:---------\|:------------\| \| 0 \| 16 \| ![](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 \| 8 \| ![](samples/1/clu1-sample0.png) \| ![](samples/1/clu1-sample1.png) \| ![](samples/1/clu1-sample2.png) \| ![](samples/1/clu1-sample3.png) \| ![](samples/1/clu1-sample4.png) \| X \| X \| X \| X \| X \| \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 2 \| 6 \| ![](samples/2/clu2-sample0.png) \| ![](samples/2/clu2-sample1.png) \| ![](samples/2/clu2-sample2.png) \| ![](samples/2/clu2-sample3.png) \| ![](samples/2/clu2-sample4.png) \| X \| X \| X \| X \| X \| \| \| X \| X \| \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 3 \| 9 \| ![](samples/3/clu3-sample0.png) \| ![](samples/3/clu3-sample1.png) \| ![](samples/3/clu3-sample2.png) \| ![](samples/3/clu3-sample3.png) \| ![](samples/3/clu3-sample4.png) \| X \| X \| X \| X \| X \| \| X \| X \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 4 \| 12 \| ![](samples/4/clu4-sample0.png) \| ![](samples/4/clu4-sample1.png) \| ![](samples/4/clu4-sample2.png) \| ![](samples/4/clu4-sample3.png) \| ![](samples/4/clu4-sample4.png) \| X \| X \| X \| X \| X \| \| X \| \| X \| X \| X \| \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 5 \| 20 \| ![](samples/5/clu5-sample0.png) \| ![](samples/5/clu5-sample1.png) \| ![](samples/5/clu5-sample2.png) \| ![](samples/5/clu5-sample3.png) \| ![](samples/5/clu5-sample4.png) \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 6 \| 6 \| ![](samples/6/clu6-sample0.png) \| ![](samples/6/clu6-sample1.png) \| ![](samples/6/clu6-sample2.png) \| ![](samples/6/clu6-sample3.png) \| ![](samples/6/clu6-sample4.png) \| X \| \| X \| X \| X \| \| X \| X \| X \| X \| X \| X \| \| \| \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 7 \| 5 \| ![](samples/7/clu7-sample0.png) \| ![](samples/7/clu7-sample1.png) \| ![](samples/7/clu7-sample2.png) \| ![](samples/7/clu7-sample3.png) \| ![](samples/7/clu7-sample4.png) \| X \| X \| X \| X \| X \| \| \| \| X \| X \| X \| \| \| X \| \| \| X \| X \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| 8 \| 5 \| ![](samples/8/clu8-sample0.png) \| ![](samples/8/clu8-sample1.png) \| ![](samples/8/clu8-sample2.png) \| ![](samples/8/clu8-sample3.png) \| ![](samples/8/clu8-sample4.png) \| X \| X \| X \| X \| X \| \| \| \| \| \| X \| \| \| X \| \| \| \| \| \| \| \| \| \| \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| 9 \| 9 \| ![](samples/9/clu9-sample0.png) \| ![](samples/9/clu9-sample1.png) \| ![](samples/9/clu9-sample2.png) \| ![](samples/9/clu9-sample3.png) \| ![](samples/9/clu9-sample4.png) \| X \| X \| X \| X \| X \| X \| \| \| \| \| \| \| \| X \| X \| \| X \| X \| \| X \| X \| X \| X \| \| \| X \| X \| X \| X \| \| \| \| \| \| \| \| \| \| 10 \| 6 \| ![](samples/10/clu10-sample0.png) \| ![](samples/10/clu10-sample1.png) \| ![](samples/10/clu10-sample2.png) \| ![](samples/10/clu10-sample3.png) \| ![](samples/10/clu10-sample4.png) \| \| X \| X \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| \| \| \| \| \| \| \| 11 \| 10 \| ![](samples/11/clu11-sample0.png) \| ![](samples/11/clu11-sample1.png) \| ![](samples/11/clu11-sample2.png) \| ![](samples/11/clu11-sample3.png) \| ![](samples/11/clu11-sample4.png) \| X \| \| \| X \| X \| \| \| \| X \| \| X \| \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| X \| X \| X \| \| \| \| 12 \| 9 \| ![](samples/12/clu12-sample0.png) \| ![](samples/12/clu12-sample1.png) \| ![](samples/12/clu12-sample2.png) \| ![](samples/12/clu12-sample3.png) \| ![](samples/12/clu12-sample4.png) \| X \| \| \| X \| X \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| X \| X \| X \|
Carlosgg14/piccolo	--- license: openrail ---
darcy01/autotrain-data-hanzbydarcycao	--- language: - zh - en task_categories: - translation --- # AutoTrain Dataset for project: hanzbydarcycao ## Dataset Description This dataset has been automatically processed by AutoTrain for project hanzbydarcycao. ### Languages The BCP-47 code for the dataset's language is zh2en. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "source": "sarashi", "target": "sarashi" }, { "source": "Dojo", "target": "Dojo" } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "source": "Value(dtype='string', id=None)", "target": "Value(dtype='string', id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: \| Split name \| Num samples \| \| ------------ \| ------------------- \| \| train \| 98 \| \| valid \| 25 \|
phanvancongthanh/pubchem_bioassay_standardized	--- dataset_info: features: - name: standardized_smiles dtype: string splits: - name: train num_bytes: 10187907266 num_examples: 210186056 download_size: 4860575313 dataset_size: 10187907266 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "pubchem_bioassay_standardized" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
lhk/test_dataset	--- license: cc-by-2.0 ---
FINNUMBER/FINCH_TRAIN_QA_BQA_400	--- 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: 1612883 num_examples: 400 download_size: 871345 dataset_size: 1612883 configs: - config_name: default data_files: - split: train path: data/train-* ---
open-llm-leaderboard/details_JiheonJeong__v1	--- pretty_name: Evaluation run of JiheonJeong/v1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [JiheonJeong/v1](https://huggingface.co/JiheonJeong/v1) 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_JiheonJeong__v1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-27T19:55:05.428463](https://huggingface.co/datasets/open-llm-leaderboard/details_JiheonJeong__v1/blob/main/results_2024-03-27T19-55-05.428463.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\": 0.42090733682944437,\n\ \ \"acc_stderr\": 0.03455222362037901,\n \"acc_norm\": 0.42437664279794174,\n\ \ \"acc_norm_stderr\": 0.035312936290375636,\n \"mc1\": 0.21909424724602203,\n\ \ \"mc1_stderr\": 0.014480038578757442,\n \"mc2\": 0.33036644378983426,\n\ \ \"mc2_stderr\": 0.01345975351436465\n },\n \"harness\|arc:challenge\|25\"\ : {\n \"acc\": 0.46928327645051193,\n \"acc_stderr\": 0.014583792546304038,\n\ \ \"acc_norm\": 0.4812286689419795,\n \"acc_norm_stderr\": 0.014601090150633964\n\ \ },\n \"harness\|hellaswag\|10\": {\n \"acc\": 0.5300736904999004,\n\ \ \"acc_stderr\": 0.004980747448813311,\n \"acc_norm\": 0.7159928301135232,\n\ \ \"acc_norm_stderr\": 0.0045001864244437985\n },\n \"harness\|hendrycksTest-abstract_algebra\|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness\|hendrycksTest-anatomy\|5\": {\n \"acc\": 0.4666666666666667,\n\ \ \"acc_stderr\": 0.043097329010363554,\n \"acc_norm\": 0.4666666666666667,\n\ \ \"acc_norm_stderr\": 0.043097329010363554\n },\n \"harness\|hendrycksTest-astronomy\|5\"\ : {\n \"acc\": 0.42105263157894735,\n \"acc_stderr\": 0.040179012759817494,\n\ \ \"acc_norm\": 0.42105263157894735,\n \"acc_norm_stderr\": 0.040179012759817494\n\ \ },\n \"harness\|hendrycksTest-business_ethics\|5\": {\n \"acc\": 0.41,\n\ \ \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.41,\n \ \ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness\|hendrycksTest-clinical_knowledge\|5\"\ : {\n \"acc\": 0.47547169811320755,\n \"acc_stderr\": 0.030735822206205615,\n\ \ \"acc_norm\": 0.47547169811320755,\n \"acc_norm_stderr\": 0.030735822206205615\n\ \ },\n \"harness\|hendrycksTest-college_biology\|5\": {\n \"acc\": 0.4583333333333333,\n\ \ \"acc_stderr\": 0.04166666666666665,\n \"acc_norm\": 0.4583333333333333,\n\ \ \"acc_norm_stderr\": 0.04166666666666665\n },\n \"harness\|hendrycksTest-college_chemistry\|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001975,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001975\n \ \ },\n \"harness\|hendrycksTest-college_computer_science\|5\": {\n \"acc\"\ : 0.39,\n \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.39,\n\ \ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness\|hendrycksTest-college_mathematics\|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness\|hendrycksTest-college_medicine\|5\": {\n \"acc\": 0.4393063583815029,\n\ \ \"acc_stderr\": 0.03784271932887467,\n \"acc_norm\": 0.4393063583815029,\n\ \ \"acc_norm_stderr\": 0.03784271932887467\n },\n \"harness\|hendrycksTest-college_physics\|5\"\ : {\n \"acc\": 0.17647058823529413,\n \"acc_stderr\": 0.0379328118530781,\n\ \ \"acc_norm\": 0.17647058823529413,\n \"acc_norm_stderr\": 0.0379328118530781\n\ \ },\n \"harness\|hendrycksTest-computer_security\|5\": {\n \"acc\":\ \ 0.54,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.54,\n\ \ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness\|hendrycksTest-conceptual_physics\|5\"\ : {\n \"acc\": 0.41702127659574467,\n \"acc_stderr\": 0.032232762667117124,\n\ \ \"acc_norm\": 0.41702127659574467,\n \"acc_norm_stderr\": 0.032232762667117124\n\ \ },\n \"harness\|hendrycksTest-econometrics\|5\": {\n \"acc\": 0.30701754385964913,\n\ \ \"acc_stderr\": 0.04339138322579861,\n \"acc_norm\": 0.30701754385964913,\n\ \ \"acc_norm_stderr\": 0.04339138322579861\n },\n \"harness\|hendrycksTest-electrical_engineering\|5\"\ : {\n \"acc\": 0.4206896551724138,\n \"acc_stderr\": 0.0411391498118926,\n\ \ \"acc_norm\": 0.4206896551724138,\n \"acc_norm_stderr\": 0.0411391498118926\n\ \ },\n \"harness\|hendrycksTest-elementary_mathematics\|5\": {\n \"acc\"\ : 0.2777777777777778,\n \"acc_stderr\": 0.023068188848261124,\n \"\ acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.023068188848261124\n\ \ },\n \"harness\|hendrycksTest-formal_logic\|5\": {\n \"acc\": 0.2777777777777778,\n\ \ \"acc_stderr\": 0.040061680838488774,\n \"acc_norm\": 0.2777777777777778,\n\ \ \"acc_norm_stderr\": 0.040061680838488774\n },\n \"harness\|hendrycksTest-global_facts\|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness\|hendrycksTest-high_school_biology\|5\": {\n \"acc\": 0.47096774193548385,\n\ \ \"acc_stderr\": 0.028396016402761005,\n \"acc_norm\": 0.47096774193548385,\n\ \ \"acc_norm_stderr\": 0.028396016402761005\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\": 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\"\ : 0.44,\n \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness\|hendrycksTest-high_school_european_history\|5\"\ : {\n \"acc\": 0.41818181818181815,\n \"acc_stderr\": 0.03851716319398394,\n\ \ \"acc_norm\": 0.41818181818181815,\n \"acc_norm_stderr\": 0.03851716319398394\n\ \ },\n \"harness\|hendrycksTest-high_school_geography\|5\": {\n \"acc\"\ : 0.5202020202020202,\n \"acc_stderr\": 0.03559443565563918,\n \"\ acc_norm\": 0.5202020202020202,\n \"acc_norm_stderr\": 0.03559443565563918\n\ \ },\n \"harness\|hendrycksTest-high_school_government_and_politics\|5\": {\n\ \ \"acc\": 0.5854922279792746,\n \"acc_stderr\": 0.03555300319557669,\n\ \ \"acc_norm\": 0.5854922279792746,\n \"acc_norm_stderr\": 0.03555300319557669\n\ \ },\n \"harness\|hendrycksTest-high_school_macroeconomics\|5\": {\n \ \ \"acc\": 0.41025641025641024,\n \"acc_stderr\": 0.024939313906940784,\n\ \ \"acc_norm\": 0.41025641025641024,\n \"acc_norm_stderr\": 0.024939313906940784\n\ \ },\n \"harness\|hendrycksTest-high_school_mathematics\|5\": {\n \"\ acc\": 0.26666666666666666,\n \"acc_stderr\": 0.02696242432507383,\n \ \ \"acc_norm\": 0.26666666666666666,\n \"acc_norm_stderr\": 0.02696242432507383\n\ \ },\n \"harness\|hendrycksTest-high_school_microeconomics\|5\": {\n \ \ \"acc\": 0.38235294117647056,\n \"acc_stderr\": 0.03156663099215416,\n\ \ \"acc_norm\": 0.38235294117647056,\n \"acc_norm_stderr\": 0.03156663099215416\n\ \ },\n \"harness\|hendrycksTest-high_school_physics\|5\": {\n \"acc\"\ : 0.25165562913907286,\n \"acc_stderr\": 0.03543304234389985,\n \"\ acc_norm\": 0.25165562913907286,\n \"acc_norm_stderr\": 0.03543304234389985\n\ \ },\n \"harness\|hendrycksTest-high_school_psychology\|5\": {\n \"acc\"\ : 0.5669724770642202,\n \"acc_stderr\": 0.021244146569074345,\n \"\ acc_norm\": 0.5669724770642202,\n \"acc_norm_stderr\": 0.021244146569074345\n\ \ },\n \"harness\|hendrycksTest-high_school_statistics\|5\": {\n \"acc\"\ : 0.37037037037037035,\n \"acc_stderr\": 0.03293377139415191,\n \"\ acc_norm\": 0.37037037037037035,\n \"acc_norm_stderr\": 0.03293377139415191\n\ \ },\n \"harness\|hendrycksTest-high_school_us_history\|5\": {\n \"acc\"\ : 0.4411764705882353,\n \"acc_stderr\": 0.034849415144292316,\n \"\ acc_norm\": 0.4411764705882353,\n \"acc_norm_stderr\": 0.034849415144292316\n\ \ },\n \"harness\|hendrycksTest-high_school_world_history\|5\": {\n \"\ acc\": 0.39662447257383965,\n \"acc_stderr\": 0.03184399873811226,\n \ \ \"acc_norm\": 0.39662447257383965,\n \"acc_norm_stderr\": 0.03184399873811226\n\ \ },\n \"harness\|hendrycksTest-human_aging\|5\": {\n \"acc\": 0.4349775784753363,\n\ \ \"acc_stderr\": 0.03327283370271344,\n \"acc_norm\": 0.4349775784753363,\n\ \ \"acc_norm_stderr\": 0.03327283370271344\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\":\ \ 0.6033057851239669,\n \"acc_stderr\": 0.044658697805310094,\n \"\ acc_norm\": 0.6033057851239669,\n \"acc_norm_stderr\": 0.044658697805310094\n\ \ },\n \"harness\|hendrycksTest-jurisprudence\|5\": {\n \"acc\": 0.4074074074074074,\n\ \ \"acc_stderr\": 0.047500773411999854,\n \"acc_norm\": 0.4074074074074074,\n\ \ \"acc_norm_stderr\": 0.047500773411999854\n },\n \"harness\|hendrycksTest-logical_fallacies\|5\"\ : {\n \"acc\": 0.4110429447852761,\n \"acc_stderr\": 0.038656978537853624,\n\ \ \"acc_norm\": 0.4110429447852761,\n \"acc_norm_stderr\": 0.038656978537853624\n\ \ },\n \"harness\|hendrycksTest-machine_learning\|5\": {\n \"acc\": 0.39285714285714285,\n\ \ \"acc_stderr\": 0.04635550135609976,\n \"acc_norm\": 0.39285714285714285,\n\ \ \"acc_norm_stderr\": 0.04635550135609976\n },\n \"harness\|hendrycksTest-management\|5\"\ : {\n \"acc\": 0.5728155339805825,\n \"acc_stderr\": 0.04897957737781168,\n\ \ \"acc_norm\": 0.5728155339805825,\n \"acc_norm_stderr\": 0.04897957737781168\n\ \ },\n \"harness\|hendrycksTest-marketing\|5\": {\n \"acc\": 0.6111111111111112,\n\ \ \"acc_stderr\": 0.03193705726200293,\n \"acc_norm\": 0.6111111111111112,\n\ \ \"acc_norm_stderr\": 0.03193705726200293\n },\n \"harness\|hendrycksTest-medical_genetics\|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness\|hendrycksTest-miscellaneous\|5\": {\n \"acc\": 0.5466155810983397,\n\ \ \"acc_stderr\": 0.017802087135850304,\n \"acc_norm\": 0.5466155810983397,\n\ \ \"acc_norm_stderr\": 0.017802087135850304\n },\n \"harness\|hendrycksTest-moral_disputes\|5\"\ : {\n \"acc\": 0.43641618497109824,\n \"acc_stderr\": 0.02670054542494369,\n\ \ \"acc_norm\": 0.43641618497109824,\n \"acc_norm_stderr\": 0.02670054542494369\n\ \ },\n \"harness\|hendrycksTest-moral_scenarios\|5\": {\n \"acc\": 0.24134078212290502,\n\ \ \"acc_stderr\": 0.014310999547961452,\n \"acc_norm\": 0.24134078212290502,\n\ \ \"acc_norm_stderr\": 0.014310999547961452\n },\n \"harness\|hendrycksTest-nutrition\|5\"\ : {\n \"acc\": 0.46078431372549017,\n \"acc_stderr\": 0.028541722692618874,\n\ \ \"acc_norm\": 0.46078431372549017,\n \"acc_norm_stderr\": 0.028541722692618874\n\ \ },\n \"harness\|hendrycksTest-philosophy\|5\": {\n \"acc\": 0.41479099678456594,\n\ \ \"acc_stderr\": 0.02798268045975956,\n \"acc_norm\": 0.41479099678456594,\n\ \ \"acc_norm_stderr\": 0.02798268045975956\n },\n \"harness\|hendrycksTest-prehistory\|5\"\ : {\n \"acc\": 0.4722222222222222,\n \"acc_stderr\": 0.027777777777777797,\n\ \ \"acc_norm\": 0.4722222222222222,\n \"acc_norm_stderr\": 0.027777777777777797\n\ \ },\n \"harness\|hendrycksTest-professional_accounting\|5\": {\n \"\ acc\": 0.3404255319148936,\n \"acc_stderr\": 0.028267657482650144,\n \ \ \"acc_norm\": 0.3404255319148936,\n \"acc_norm_stderr\": 0.028267657482650144\n\ \ },\n \"harness\|hendrycksTest-professional_law\|5\": {\n \"acc\": 0.3428943937418514,\n\ \ \"acc_stderr\": 0.012123463271585895,\n \"acc_norm\": 0.3428943937418514,\n\ \ \"acc_norm_stderr\": 0.012123463271585895\n },\n \"harness\|hendrycksTest-professional_medicine\|5\"\ : {\n \"acc\": 0.34191176470588236,\n \"acc_stderr\": 0.028814722422254177,\n\ \ \"acc_norm\": 0.34191176470588236,\n \"acc_norm_stderr\": 0.028814722422254177\n\ \ },\n \"harness\|hendrycksTest-professional_psychology\|5\": {\n \"\ acc\": 0.3758169934640523,\n \"acc_stderr\": 0.019594021136577454,\n \ \ \"acc_norm\": 0.3758169934640523,\n \"acc_norm_stderr\": 0.019594021136577454\n\ \ },\n \"harness\|hendrycksTest-public_relations\|5\": {\n \"acc\": 0.4818181818181818,\n\ \ \"acc_stderr\": 0.04785964010794916,\n \"acc_norm\": 0.4818181818181818,\n\ \ \"acc_norm_stderr\": 0.04785964010794916\n },\n \"harness\|hendrycksTest-security_studies\|5\"\ : {\n \"acc\": 0.46122448979591835,\n \"acc_stderr\": 0.031912820526692774,\n\ \ \"acc_norm\": 0.46122448979591835,\n \"acc_norm_stderr\": 0.031912820526692774\n\ \ },\n \"harness\|hendrycksTest-sociology\|5\": {\n \"acc\": 0.417910447761194,\n\ \ \"acc_stderr\": 0.034875586404620636,\n \"acc_norm\": 0.417910447761194,\n\ \ \"acc_norm_stderr\": 0.034875586404620636\n },\n \"harness\|hendrycksTest-us_foreign_policy\|5\"\ : {\n \"acc\": 0.57,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.57,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness\|hendrycksTest-virology\|5\": {\n \"acc\": 0.4578313253012048,\n\ \ \"acc_stderr\": 0.0387862677100236,\n \"acc_norm\": 0.4578313253012048,\n\ \ \"acc_norm_stderr\": 0.0387862677100236\n },\n \"harness\|hendrycksTest-world_religions\|5\"\ : {\n \"acc\": 0.5321637426900585,\n \"acc_stderr\": 0.03826882417660368,\n\ \ \"acc_norm\": 0.5321637426900585,\n \"acc_norm_stderr\": 0.03826882417660368\n\ \ },\n \"harness\|truthfulqa:mc\|0\": {\n \"mc1\": 0.21909424724602203,\n\ \ \"mc1_stderr\": 0.014480038578757442,\n \"mc2\": 0.33036644378983426,\n\ \ \"mc2_stderr\": 0.01345975351436465\n },\n \"harness\|winogrande\|5\"\ : {\n \"acc\": 0.6606156274664562,\n \"acc_stderr\": 0.01330771492894175\n\ \ },\n \"harness\|gsm8k\|5\": {\n \"acc\": 0.17437452615617893,\n \ \ \"acc_stderr\": 0.010451421361976234\n }\n}\n```" repo_url: https://huggingface.co/JiheonJeong/v1 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_27T18_34_04.185928 path: - '/details_harness\|arc:challenge\|25_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|arc:challenge\|25_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|arc:challenge\|25_2024-03-27T19-55-05.428463.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|gsm8k\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|gsm8k\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|gsm8k\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hellaswag\|10_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hellaswag\|10_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hellaswag\|10_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-27T18-34-04.185928.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-international_law\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-management\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-marketing\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-sociology\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-virology\|5_2024-03-27T19-55-05.428463.parquet' - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-abstract_algebra\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-anatomy\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-astronomy\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-business_ethics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-clinical_knowledge\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_biology\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_chemistry\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_computer_science\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_mathematics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_medicine\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-college_physics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-computer_security\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-conceptual_physics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-econometrics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-electrical_engineering\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-elementary_mathematics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-formal_logic\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-global_facts\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_biology\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_chemistry\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_computer_science\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_european_history\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_geography\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_government_and_politics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_macroeconomics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_mathematics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_microeconomics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_physics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_psychology\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_statistics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_us_history\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-high_school_world_history\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_aging\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-human_sexuality\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-international_law\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-jurisprudence\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-logical_fallacies\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-machine_learning\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-management\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-management\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-marketing\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-medical_genetics\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-miscellaneous\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_disputes\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-moral_scenarios\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-nutrition\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-philosophy\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-prehistory\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_accounting\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_law\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_medicine\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-professional_psychology\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-public_relations\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-security_studies\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-sociology\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-us_foreign_policy\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-virology\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|hendrycksTest-world_religions\|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|truthfulqa:mc\|0_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|truthfulqa:mc\|0_2024-03-27T19-55-05.428463.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '/details_harness\|winogrande\|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '/details_harness\|winogrande\|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '/details_harness\|winogrande\|5_2024-03-27T19-55-05.428463.parquet' - config_name: results data_files: - split: 2024_03_27T18_34_04.185928 path: - results_2024-03-27T18-34-04.185928.parquet - split: 2024_03_27T19_55_05.428463 path: - results_2024-03-27T19-55-05.428463.parquet - split: latest path: - results_2024-03-27T19-55-05.428463.parquet --- # Dataset Card for Evaluation run of JiheonJeong/v1 <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [JiheonJeong/v1](https://huggingface.co/JiheonJeong/v1) 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_JiheonJeong__v1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-27T19:55:05.428463](https://huggingface.co/datasets/open-llm-leaderboard/details_JiheonJeong__v1/blob/main/results_2024-03-27T19-55-05.428463.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": 0.42090733682944437, "acc_stderr": 0.03455222362037901, "acc_norm": 0.42437664279794174, "acc_norm_stderr": 0.035312936290375636, "mc1": 0.21909424724602203, "mc1_stderr": 0.014480038578757442, "mc2": 0.33036644378983426, "mc2_stderr": 0.01345975351436465 }, "harness\|arc:challenge\|25": { "acc": 0.46928327645051193, "acc_stderr": 0.014583792546304038, "acc_norm": 0.4812286689419795, "acc_norm_stderr": 0.014601090150633964 }, "harness\|hellaswag\|10": { "acc": 0.5300736904999004, "acc_stderr": 0.004980747448813311, "acc_norm": 0.7159928301135232, "acc_norm_stderr": 0.0045001864244437985 }, "harness\|hendrycksTest-abstract_algebra\|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness\|hendrycksTest-anatomy\|5": { "acc": 0.4666666666666667, "acc_stderr": 0.043097329010363554, "acc_norm": 0.4666666666666667, "acc_norm_stderr": 0.043097329010363554 }, "harness\|hendrycksTest-astronomy\|5": { "acc": 0.42105263157894735, "acc_stderr": 0.040179012759817494, "acc_norm": 0.42105263157894735, "acc_norm_stderr": 0.040179012759817494 }, "harness\|hendrycksTest-business_ethics\|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness\|hendrycksTest-clinical_knowledge\|5": { "acc": 0.47547169811320755, "acc_stderr": 0.030735822206205615, "acc_norm": 0.47547169811320755, "acc_norm_stderr": 0.030735822206205615 }, "harness\|hendrycksTest-college_biology\|5": { "acc": 0.4583333333333333, "acc_stderr": 0.04166666666666665, "acc_norm": 0.4583333333333333, "acc_norm_stderr": 0.04166666666666665 }, "harness\|hendrycksTest-college_chemistry\|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness\|hendrycksTest-college_computer_science\|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness\|hendrycksTest-college_mathematics\|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness\|hendrycksTest-college_medicine\|5": { "acc": 0.4393063583815029, "acc_stderr": 0.03784271932887467, "acc_norm": 0.4393063583815029, "acc_norm_stderr": 0.03784271932887467 }, "harness\|hendrycksTest-college_physics\|5": { "acc": 0.17647058823529413, "acc_stderr": 0.0379328118530781, "acc_norm": 0.17647058823529413, "acc_norm_stderr": 0.0379328118530781 }, "harness\|hendrycksTest-computer_security\|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness\|hendrycksTest-conceptual_physics\|5": { "acc": 0.41702127659574467, "acc_stderr": 0.032232762667117124, "acc_norm": 0.41702127659574467, "acc_norm_stderr": 0.032232762667117124 }, "harness\|hendrycksTest-econometrics\|5": { "acc": 0.30701754385964913, "acc_stderr": 0.04339138322579861, "acc_norm": 0.30701754385964913, "acc_norm_stderr": 0.04339138322579861 }, "harness\|hendrycksTest-electrical_engineering\|5": { "acc": 0.4206896551724138, "acc_stderr": 0.0411391498118926, "acc_norm": 0.4206896551724138, "acc_norm_stderr": 0.0411391498118926 }, "harness\|hendrycksTest-elementary_mathematics\|5": { "acc": 0.2777777777777778, "acc_stderr": 0.023068188848261124, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.023068188848261124 }, "harness\|hendrycksTest-formal_logic\|5": { "acc": 0.2777777777777778, "acc_stderr": 0.040061680838488774, "acc_norm": 0.2777777777777778, "acc_norm_stderr": 0.040061680838488774 }, "harness\|hendrycksTest-global_facts\|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness\|hendrycksTest-high_school_biology\|5": { "acc": 0.47096774193548385, "acc_stderr": 0.028396016402761005, "acc_norm": 0.47096774193548385, 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"harness\|hendrycksTest-high_school_macroeconomics\|5": { "acc": 0.41025641025641024, "acc_stderr": 0.024939313906940784, "acc_norm": 0.41025641025641024, "acc_norm_stderr": 0.024939313906940784 }, "harness\|hendrycksTest-high_school_mathematics\|5": { "acc": 0.26666666666666666, "acc_stderr": 0.02696242432507383, "acc_norm": 0.26666666666666666, "acc_norm_stderr": 0.02696242432507383 }, "harness\|hendrycksTest-high_school_microeconomics\|5": { "acc": 0.38235294117647056, "acc_stderr": 0.03156663099215416, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.03156663099215416 }, "harness\|hendrycksTest-high_school_physics\|5": { "acc": 0.25165562913907286, "acc_stderr": 0.03543304234389985, "acc_norm": 0.25165562913907286, "acc_norm_stderr": 0.03543304234389985 }, "harness\|hendrycksTest-high_school_psychology\|5": { "acc": 0.5669724770642202, "acc_stderr": 0.021244146569074345, "acc_norm": 0.5669724770642202, "acc_norm_stderr": 0.021244146569074345 }, "harness\|hendrycksTest-high_school_statistics\|5": { "acc": 0.37037037037037035, "acc_stderr": 0.03293377139415191, "acc_norm": 0.37037037037037035, "acc_norm_stderr": 0.03293377139415191 }, "harness\|hendrycksTest-high_school_us_history\|5": { "acc": 0.4411764705882353, "acc_stderr": 0.034849415144292316, "acc_norm": 0.4411764705882353, "acc_norm_stderr": 0.034849415144292316 }, "harness\|hendrycksTest-high_school_world_history\|5": { "acc": 0.39662447257383965, "acc_stderr": 0.03184399873811226, "acc_norm": 0.39662447257383965, "acc_norm_stderr": 0.03184399873811226 }, "harness\|hendrycksTest-human_aging\|5": { "acc": 0.4349775784753363, "acc_stderr": 0.03327283370271344, "acc_norm": 0.4349775784753363, "acc_norm_stderr": 0.03327283370271344 }, "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": 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"acc_norm_stderr": 0.03193705726200293 }, "harness\|hendrycksTest-medical_genetics\|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "harness\|hendrycksTest-miscellaneous\|5": { "acc": 0.5466155810983397, "acc_stderr": 0.017802087135850304, "acc_norm": 0.5466155810983397, "acc_norm_stderr": 0.017802087135850304 }, "harness\|hendrycksTest-moral_disputes\|5": { "acc": 0.43641618497109824, "acc_stderr": 0.02670054542494369, "acc_norm": 0.43641618497109824, "acc_norm_stderr": 0.02670054542494369 }, "harness\|hendrycksTest-moral_scenarios\|5": { "acc": 0.24134078212290502, "acc_stderr": 0.014310999547961452, "acc_norm": 0.24134078212290502, "acc_norm_stderr": 0.014310999547961452 }, "harness\|hendrycksTest-nutrition\|5": { "acc": 0.46078431372549017, "acc_stderr": 0.028541722692618874, "acc_norm": 0.46078431372549017, "acc_norm_stderr": 0.028541722692618874 }, "harness\|hendrycksTest-philosophy\|5": { "acc": 0.41479099678456594, "acc_stderr": 0.02798268045975956, "acc_norm": 0.41479099678456594, "acc_norm_stderr": 0.02798268045975956 }, "harness\|hendrycksTest-prehistory\|5": { "acc": 0.4722222222222222, "acc_stderr": 0.027777777777777797, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.027777777777777797 }, "harness\|hendrycksTest-professional_accounting\|5": { "acc": 0.3404255319148936, "acc_stderr": 0.028267657482650144, "acc_norm": 0.3404255319148936, "acc_norm_stderr": 0.028267657482650144 }, "harness\|hendrycksTest-professional_law\|5": { "acc": 0.3428943937418514, "acc_stderr": 0.012123463271585895, "acc_norm": 0.3428943937418514, "acc_norm_stderr": 0.012123463271585895 }, "harness\|hendrycksTest-professional_medicine\|5": { "acc": 0.34191176470588236, "acc_stderr": 0.028814722422254177, "acc_norm": 0.34191176470588236, "acc_norm_stderr": 0.028814722422254177 }, "harness\|hendrycksTest-professional_psychology\|5": { "acc": 0.3758169934640523, "acc_stderr": 0.019594021136577454, "acc_norm": 0.3758169934640523, "acc_norm_stderr": 0.019594021136577454 }, "harness\|hendrycksTest-public_relations\|5": { "acc": 0.4818181818181818, "acc_stderr": 0.04785964010794916, "acc_norm": 0.4818181818181818, "acc_norm_stderr": 0.04785964010794916 }, "harness\|hendrycksTest-security_studies\|5": { "acc": 0.46122448979591835, "acc_stderr": 0.031912820526692774, "acc_norm": 0.46122448979591835, "acc_norm_stderr": 0.031912820526692774 }, "harness\|hendrycksTest-sociology\|5": { "acc": 0.417910447761194, "acc_stderr": 0.034875586404620636, "acc_norm": 0.417910447761194, "acc_norm_stderr": 0.034875586404620636 }, "harness\|hendrycksTest-us_foreign_policy\|5": { "acc": 0.57, "acc_stderr": 0.04975698519562428, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562428 }, "harness\|hendrycksTest-virology\|5": { "acc": 0.4578313253012048, "acc_stderr": 0.0387862677100236, "acc_norm": 0.4578313253012048, "acc_norm_stderr": 0.0387862677100236 }, "harness\|hendrycksTest-world_religions\|5": { "acc": 0.5321637426900585, "acc_stderr": 0.03826882417660368, "acc_norm": 0.5321637426900585, "acc_norm_stderr": 0.03826882417660368 }, "harness\|truthfulqa:mc\|0": { "mc1": 0.21909424724602203, "mc1_stderr": 0.014480038578757442, "mc2": 0.33036644378983426, "mc2_stderr": 0.01345975351436465 }, "harness\|winogrande\|5": { "acc": 0.6606156274664562, "acc_stderr": 0.01330771492894175 }, "harness\|gsm8k\|5": { "acc": 0.17437452615617893, "acc_stderr": 0.010451421361976234 } } ``` ## 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]
gguichard/myriade_noun_aligned_with_wordnet	--- dataset_info: features: - name: tokens sequence: string - name: wn_sens sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 76227656 num_examples: 127112 download_size: 18764458 dataset_size: 76227656 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "myriade_noun_aligned_with_wordnet" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
joey234/mmlu-anatomy-original-neg-prepend	--- dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: neg_prompt dtype: string splits: - name: test num_bytes: 2413 num_examples: 6 download_size: 6038 dataset_size: 2413 --- # Dataset Card for "mmlu-anatomy-original-neg-prepend" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Joi123/bitcoin-tweets-2023	--- language: - en tags: - bitcoin - tweets - tweet - Twitter - btc size_categories: - 100K<n<1M pretty_name: h ---
byebyebye/ukr-wiki-qa-v1	--- dataset_info: features: - name: prompt dtype: string - name: topic dtype: string - name: question dtype: string - name: response dtype: string splits: - name: train num_bytes: 58645347 num_examples: 40567 download_size: 28771700 dataset_size: 58645347 configs: - config_name: default data_files: - split: train path: data/train-* ---
itamarcard/vitrine	--- license: openrail ---

louisbrulenaudet/tax-fr

--- license: apache-2.0 language: - fr multilinguality: - monolingual tags: - instruction-finetuning - legal - tax - llm - fiscal source_datasets: - original pretty_name: >- Instruction fine-tuning Large Language Models for tax practice using quantization and LoRA: a boilerplate task_categories: - text-generation - table-question-answering - summarization - conversational size_categories: - n<1K --- # Instruction fine-tuning Large Language Models for tax practice using quantization and LoRA: a boilerplate This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for tax practice. Fine-tuning is the process of adapting a pre-trained model to perform specific tasks or cater to particular domains. It involves adjusting the model's parameters through a further round of training on task-specific or domain-specific data. While conventional fine-tuning strategies involve supervised learning with labeled data, instruction-based fine-tuning introduces a more structured and interpretable approach. Instruction-based fine-tuning leverages the power of human-provided instructions to guide the model's behavior. These instructions can be in the form of text prompts, prompts with explicit task descriptions, or a combination of both. This approach allows for a more controlled and context-aware interaction with the LLM, making it adaptable to a multitude of specialized tasks. Instruction-based fine-tuning significantly enhances the performance of LLMs in the following ways: - Task-Specific Adaptation: LLMs, when fine-tuned with specific instructions, exhibit remarkable adaptability to diverse tasks. They can switch seamlessly between translation, summarization, and question-answering, guided by the provided instructions. - Reduced Ambiguity: Traditional LLMs might generate ambiguous or contextually inappropriate responses. Instruction-based fine-tuning allows for a clearer and more context-aware generation, reducing the likelihood of nonsensical outputs. - Efficient Knowledge Transfer: Instructions can encapsulate domain-specific knowledge, enabling LLMs to benefit from expert guidance. This knowledge transfer is particularly valuable in fields like tax practice, law, medicine, and more. - Interpretability: Instruction-based fine-tuning also makes LLM behavior more interpretable. Since the instructions are human-readable, it becomes easier to understand and control model outputs. - Adaptive Behavior: LLMs, post instruction-based fine-tuning, exhibit adaptive behavior that is responsive to both explicit task descriptions and implicit cues within the provided text. ## Dataset generation This JSON file is a list of dictionaries, each dictionary contains the following fields: - `instruction`: `str`, describes the task the model should perform. Each of the instructions is unique. - `input`: `str`, optional context or input for the task. - `output`: `str`, the answer to the instruction. We used the following prompt for generating the dataset: ``` Objectif : Élaboration d'un ensemble de 5-10 problématiques ou instructions diverses dans un fichier JSON à destination d'un modèle de langage pour un objectif d'entrainement (fine-tuning) aux fins d'assistance du métier de fiscaliste. Schéma de la liste de dictionnaires souhaitée : [ { "instruction" :"xxx", "input" : "xxx", "output" : "xxx" } ] Exigences à respecter : 1. Élimination de la répétition et utilisation de structures de phrases élaborées. Éviter toute redondance de contenu dans les phrases successives tout en favorisant l'utilisation de structures de phrases complexes qui élargissent la portée de l'expression. 2. Diversité linguistique des instructions. Les directives doivent être formulées de manière variée, en combinant des questions avec des instructions impératives. 3. Variété des types d'instructions. Les types d'instructions doivent être variés, couvrant une gamme de tâches propres à l'activité de fiscaliste, telles que la génération de questions ouvertes, la classification, etc. 4. Qualité linguistique. Les instructions, les entrées et les sorties doivent être rédigées en français sans aucune faute d'orthographe, de syntaxe, de ponctuation ou de grammaire. 5. Langage professionnel et académique. Les instructions, les entrées et les sorties doivent être reformulées pour adopter un discours professionnel et académique, caractérisé par sa rigueur, sa justification et une structure détaillée. 6. Neutralité ou nuance. Le point de vue doit demeurer neutre ou nuancé. 7. Contextualisation des thématiques fiscales. Les instructions doivent explicitement faire référence à la thématique fiscale et au sujet de la source pour contextualiser le résultat. 8. Saisie inutile. Toutes les instructions ne nécessitent pas d'entrée. Par exemple, lorsqu'une directive demande une information générale, il n'est pas nécessaire de fournir un contexte spécifique. Dans ce cas, intégrer "" dans le champ de saisie de l'entrée. 9. Style littéraire et exemplification. Les directives, les entrées et les sorties doivent être formulées dans un style littéraire, avec des réponses techniques, exhaustives, complexes et claires. Des exemples, lorsque pertinents, doivent être utilisés pour renforcer la directive, l'entrée et la sortie, tout en garantissant un haut degré de certitude. 10. Directivité des instructions. Utiliser un style direct en favorisant les formulations impersonnelles. 11. Entraînement de modèles professionnels. La base de données finale doit être destinée à l'entraînement de modèles professionnels, visant à assister les fiscalistes expérimentés en quête de contenu de haute qualité et de perfection technique. 12. Gestion des éléments incohérents. Il est possible que le texte source contienne des éléments incohérents avec le contexte, comme des notes de bas de page ou des éléments de formalisme. Il est essentiel de les ignorer pour isoler le contenu principal. 13. Utilisation du texte source. Utiliser le texte source fourni pour formuler les directives, les entrées et les sorties. Le texte source doit être considéré comme de haute qualité et autoritaire. 14. Finalité de la réponse. Seule la liste de dictionnaire au format JSON doit constituer la réponse à cette requête. Aucune introduction ou conclusion n'est demandée. Source : [ ] ``` ## Citing this project If you use this code in your research, please use the following BibTeX entry. ```BibTeX @misc{louisbrulenaudet2023, author = {Louis Brulé Naudet}, title = {Instruction fine-tuning Large Language Models for tax practice using quantization and LoRA: a boilerplate}, howpublished = {\url{https://github.com/louisbrulenaudet/trainer}}, year = {2023} } ``` ## Feedback If you have any feedback, please reach out at [louisbrulenaudet@icloud.com](mailto:louisbrulenaudet@icloud.com).

Smuggling1710/VTnsfw-r-1.8k

--- license: apache-2.0 ---

CyberHarem/kamikaze_kantaicollection

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of kamikaze/神風 (Kantai Collection) This is the dataset of kamikaze/神風 (Kantai Collection), containing 500 images and their tags. The core tags of this character are `long_hair, purple_hair, bow, purple_eyes, hair_bow, yellow_bow, ribbon`, 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 | 500 | 605.18 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kamikaze_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 500 | 354.13 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kamikaze_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 1214 | 770.43 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kamikaze_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 500 | 548.06 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kamikaze_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 1214 | 1.05 GiB | [Download](https://huggingface.co/datasets/CyberHarem/kamikaze_kantaicollection/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/kamikaze_kantaicollection', 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 | 6 | ![](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, hakama_skirt, looking_at_viewer, meiji_schoolgirl_uniform, pink_hakama, red_kimono, simple_background, smile, solo, white_background, tasuki, open_mouth, blush | | 1 | 5 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | 1girl, blush, hakama_skirt, looking_at_viewer, meiji_schoolgirl_uniform, pink_hakama, solo, red_kimono, tasuki | | 2 | 21 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | 1girl, hakama_skirt, lace-up_boots, meiji_schoolgirl_uniform, pink_hakama, solo, brown_footwear, white_background, red_kimono, simple_background, full_body, tasuki, looking_at_viewer, smile, standing, sitting | | 3 | 5 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | 1girl, hakama_skirt, holding_sword, katana, kimono, meiji_schoolgirl_uniform, pink_hakama, solo, looking_at_viewer, tasuki, unsheathing, open_mouth | | 4 | 5 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | 1girl, brown_footwear, frilled_apron, gift, hair_flower, hakama_skirt, maid_headdress, meiji_schoolgirl_uniform, open_mouth, pink_hakama, red_kimono, solo, tube, wa_maid, white_apron, full_body, lace-up_boots, smile, looking_at_viewer, simple_background, white_background, upper_teeth_only | | 5 | 7 | ![](samples/5/clu5-sample0.png) | ![](samples/5/clu5-sample1.png) | ![](samples/5/clu5-sample2.png) | ![](samples/5/clu5-sample3.png) | ![](samples/5/clu5-sample4.png) | 1girl, frilled_apron, hair_flower, hakama_skirt, looking_at_viewer, maid_headdress, pink_hakama, red_kimono, solo, wa_maid, white_apron, maid_apron, meiji_schoolgirl_uniform, cowboy_shot, heart, open_mouth, white_background, :d, blush, dated, one-hour_drawing_challenge, simple_background | | 6 | 9 | ![](samples/6/clu6-sample0.png) | ![](samples/6/clu6-sample1.png) | ![](samples/6/clu6-sample2.png) | ![](samples/6/clu6-sample3.png) | ![](samples/6/clu6-sample4.png) | 1boy, 1girl, hetero, kimono, nipples, sex, solo_focus, vaginal, blush, open_mouth, penis, censored, small_breasts, navel, cowgirl_position, cum_in_pussy, girl_on_top, hakama_skirt, medium_breasts, meiji_schoolgirl_uniform, open_clothes, pink_hakama | | 7 | 5 | ![](samples/7/clu7-sample0.png) | ![](samples/7/clu7-sample1.png) | ![](samples/7/clu7-sample2.png) | ![](samples/7/clu7-sample3.png) | ![](samples/7/clu7-sample4.png) | 1girl, detached_collar, fake_animal_ears, looking_at_viewer, playboy_bunny, rabbit_ears, solo, strapless_leotard, cowboy_shot, open_mouth, red_leotard, white_background, wrist_cuffs, yellow_ribbon, alternate_costume, black_pantyhose, brown_pantyhose, simple_background, small_breasts, smile, covered_navel, highleg, pink_bowtie, pink_leotard, red_bowtie, yellow_bowtie | | 8 | 6 | ![](samples/8/clu8-sample0.png) | ![](samples/8/clu8-sample1.png) | ![](samples/8/clu8-sample2.png) | ![](samples/8/clu8-sample3.png) | ![](samples/8/clu8-sample4.png) | 1girl, cowboy_shot, school_uniform, solo, white_shirt, alternate_costume, long_sleeves, looking_at_viewer, pleated_skirt, yellow_ribbon, blush, collared_shirt, simple_background, smile, white_background, blue_skirt, hair_ribbon, one-hour_drawing_challenge, twitter_username | | 9 | 8 | ![](samples/9/clu9-sample0.png) | ![](samples/9/clu9-sample1.png) | ![](samples/9/clu9-sample2.png) | ![](samples/9/clu9-sample3.png) | ![](samples/9/clu9-sample4.png) | 1girl, alternate_costume, looking_at_viewer, open_mouth, solo, blush, :d, frills, white_background, white_dress, yellow_ribbon, bare_shoulders, holding, long_sleeves, simple_background | | 10 | 5 | ![](samples/10/clu10-sample0.png) | ![](samples/10/clu10-sample1.png) | ![](samples/10/clu10-sample2.png) | ![](samples/10/clu10-sample3.png) | ![](samples/10/clu10-sample4.png) | 1girl, alternate_costume, pleated_skirt, solo, looking_at_viewer, serafuku, yellow_ribbon, black_skirt, hair_ornament, hair_ribbon, indoors, red_neckerchief, red_skirt, sailor_collar, school_bag | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | hakama_skirt | looking_at_viewer | meiji_schoolgirl_uniform | pink_hakama | red_kimono | simple_background | smile | solo | white_background | tasuki | open_mouth | blush | lace-up_boots | brown_footwear | full_body | standing | sitting | holding_sword | katana | kimono | unsheathing | frilled_apron | gift | hair_flower | maid_headdress | tube | wa_maid | white_apron | upper_teeth_only | maid_apron | cowboy_shot | heart | :d | dated | one-hour_drawing_challenge | 1boy | hetero | nipples | sex | solo_focus | vaginal | penis | censored | small_breasts | navel | cowgirl_position | cum_in_pussy | girl_on_top | medium_breasts | open_clothes | detached_collar | fake_animal_ears | playboy_bunny | rabbit_ears | strapless_leotard | red_leotard | wrist_cuffs | yellow_ribbon | alternate_costume | black_pantyhose | brown_pantyhose | covered_navel | highleg | pink_bowtie | pink_leotard | red_bowtie | yellow_bowtie | school_uniform | white_shirt | long_sleeves | pleated_skirt | collared_shirt | blue_skirt | hair_ribbon | twitter_username | frills | white_dress | bare_shoulders | holding | serafuku | black_skirt | hair_ornament | indoors | red_neckerchief | red_skirt | sailor_collar | school_bag | |----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:---------------|:--------------------|:---------------------------|:--------------|:-------------|:--------------------|:--------|:-------|:-------------------|:---------|:-------------|:--------|:----------------|:-----------------|:------------|:-----------|:----------|:----------------|:---------|:---------|:--------------|:----------------|:-------|:--------------|:-----------------|:-------|:----------|:--------------|:-------------------|:-------------|:--------------|:--------|:-----|:--------|:-----------------------------|:-------|:---------|:----------|:------|:-------------|:----------|:--------|:-----------|:----------------|:--------|:-------------------|:---------------|:--------------|:-----------------|:---------------|:------------------|:-------------------|:----------------|:--------------|:--------------------|:--------------|:--------------|:----------------|:--------------------|:------------------|:------------------|:----------------|:----------|:--------------|:---------------|:-------------|:----------------|:-----------------|:--------------|:---------------|:----------------|:-----------------|:-------------|:--------------|:-------------------|:---------|:--------------|:-----------------|:----------|:-----------|:--------------|:----------------|:----------|:------------------|:------------|:----------------|:-------------| | 0 | 6 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 5 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 2 | 21 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | X | X | X | X | X | X | X | X | X | X | X | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 3 | 5 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | X | X | X | X | X | | | | X | | X | X | | | | | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 4 | 5 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | X | X | X | X | X | X | X | X | X | X | | X | | X | X | X | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 5 | 7 | ![](samples/5/clu5-sample0.png) | ![](samples/5/clu5-sample1.png) | ![](samples/5/clu5-sample2.png) | ![](samples/5/clu5-sample3.png) | ![](samples/5/clu5-sample4.png) | X | X | X | X | X | X | X | | X | X | | X | X | | | | | | | | | | X | | X | X | | X | X | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 6 | 9 | ![](samples/6/clu6-sample0.png) | ![](samples/6/clu6-sample1.png) | ![](samples/6/clu6-sample2.png) | ![](samples/6/clu6-sample3.png) | ![](samples/6/clu6-sample4.png) | X | X | | X | X | | | | | | | X | X | | | | | | | | X | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 7 | 5 | ![](samples/7/clu7-sample0.png) | ![](samples/7/clu7-sample1.png) | ![](samples/7/clu7-sample2.png) | ![](samples/7/clu7-sample3.png) | ![](samples/7/clu7-sample4.png) | X | | X | | | | X | X | X | X | | X | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | X | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | 8 | 6 | ![](samples/8/clu8-sample0.png) | ![](samples/8/clu8-sample1.png) | ![](samples/8/clu8-sample2.png) | ![](samples/8/clu8-sample3.png) | ![](samples/8/clu8-sample4.png) | X | | X | | | | X | X | X | X | | | X | | | | | | | | | | | | | | | | | | | X | | | | X | | | | | | | | | | | | | | | | | | | | | | | X | X | | | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | 9 | 8 | ![](samples/9/clu9-sample0.png) | ![](samples/9/clu9-sample1.png) | ![](samples/9/clu9-sample2.png) | ![](samples/9/clu9-sample3.png) | ![](samples/9/clu9-sample4.png) | X | | X | | | | X | | X | X | | X | X | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | X | X | | | | | | | | | | | X | | | | | | X | X | X | X | | | | | | | | | | 10 | 5 | ![](samples/10/clu10-sample0.png) | ![](samples/10/clu10-sample1.png) | ![](samples/10/clu10-sample2.png) | ![](samples/10/clu10-sample3.png) | ![](samples/10/clu10-sample4.png) | X | | X | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | | | | | | | | | | | | X | | | X | | | | | | X | X | X | X | X | X | X | X |

deberain/ChatGPT-Tweets

--- dataset_info: features: - name: Date dtype: string - name: Tweet dtype: string - name: Url dtype: string - name: User dtype: string - name: UserCreated dtype: string - name: UserVerified dtype: string - name: UserFollowers dtype: string - name: UserFriends dtype: string - name: Retweets dtype: string - name: Likes dtype: string - name: Location dtype: string - name: UserDescription dtype: string splits: - name: train num_bytes: 143971145 num_examples: 305432 download_size: 81419852 dataset_size: 143971145 --- # Dataset Card for "ChatGPT-Tweets" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Back-up/merge-stock-part-1-v2

--- dataset_info: features: - name: title dtype: string - name: url dtype: string - name: date dtype: string - name: view struct: - name: number_of_response dtype: string - name: number_of_view dtype: string - name: content list: - name: date_comment dtype: string - name: res dtype: string - name: d struct: - name: 01/01/2016 dtype: int64 - name: 01/01/2020 dtype: int64 - name: 01/01/2021 dtype: int64 - name: 01/01/2022 dtype: int64 - name: 01/01/2023 dtype: int64 - name: 01/01/2024 dtype: int64 - name: 01/02/2009 dtype: int64 - name: 01/02/2010 dtype: int64 - name: 01/02/2016 dtype: int64 - name: 01/02/2017 dtype: int64 - name: 01/02/2018 dtype: int64 - name: 01/02/2020 dtype: int64 - name: 01/02/2021 dtype: int64 - name: 01/02/2022 dtype: int64 - name: 01/02/2023 dtype: int64 - name: 01/03/2008 dtype: int64 - name: 01/03/2010 dtype: int64 - name: 01/03/2016 dtype: int64 - name: 01/03/2018 dtype: int64 - name: 01/03/2019 dtype: int64 - name: 01/03/2020 dtype: int64 - name: 01/03/2021 dtype: int64 - name: 01/03/2022 dtype: int64 - name: 01/03/2023 dtype: int64 - name: 01/04/2009 dtype: int64 - name: 01/04/2016 dtype: int64 - name: 01/04/2017 dtype: int64 - name: 01/04/2019 dtype: int64 - name: 01/04/2020 dtype: int64 - name: 01/04/2021 dtype: int64 - name: 01/04/2022 dtype: int64 - name: 01/04/2023 dtype: int64 - name: 01/05/2018 dtype: int64 - name: 01/05/2019 dtype: int64 - name: 01/05/2020 dtype: int64 - name: 01/05/2021 dtype: int64 - name: 01/05/2022 dtype: int64 - name: 01/05/2023 dtype: int64 - name: 01/06/2016 dtype: int64 - name: 01/06/2017 dtype: int64 - name: 01/06/2019 dtype: int64 - name: 01/06/2020 dtype: int64 - name: 01/06/2021 dtype: int64 - name: 01/06/2022 dtype: int64 - name: 01/06/2023 dtype: int64 - name: 01/07/2008 dtype: int64 - name: 01/07/2009 dtype: int64 - name: 01/07/2016 dtype: int64 - name: 01/07/2018 dtype: int64 - name: 01/07/2019 dtype: int64 - name: 01/07/2020 dtype: int64 - name: 01/07/2021 dtype: int64 - name: 01/07/2022 dtype: int64 - name: 01/07/2023 dtype: int64 - name: 01/08/2007 dtype: int64 - name: 01/08/2009 dtype: int64 - name: 01/08/2016 dtype: int64 - name: 01/08/2018 dtype: int64 - name: 01/08/2019 dtype: int64 - name: 01/08/2020 dtype: int64 - name: 01/08/2021 dtype: int64 - name: 01/08/2022 dtype: int64 - name: 01/08/2023 dtype: int64 - name: 01/09/2007 dtype: int64 - name: 01/09/2008 dtype: int64 - name: 01/09/2017 dtype: int64 - name: 01/09/2018 dtype: int64 - name: 01/09/2019 dtype: int64 - name: 01/09/2020 dtype: int64 - name: 01/09/2021 dtype: int64 - name: 01/09/2022 dtype: int64 - name: 01/09/2023 dtype: int64 - name: 01/10/2008 dtype: int64 - name: 01/10/2009 dtype: int64 - name: 01/10/2017 dtype: int64 - name: 01/10/2018 dtype: int64 - name: 01/10/2019 dtype: int64 - name: 01/10/2020 dtype: int64 - name: 01/10/2021 dtype: int64 - name: 01/10/2022 dtype: int64 - name: 01/10/2023 dtype: int64 - name: 01/11/2008 dtype: int64 - name: 01/11/2010 dtype: int64 - name: 01/11/2017 dtype: int64 - name: 01/11/2018 dtype: int64 - name: 01/11/2019 dtype: int64 - name: 01/11/2020 dtype: int64 - name: 01/11/2021 dtype: int64 - name: 01/11/2022 dtype: int64 - name: 01/11/2023 dtype: int64 - name: 01/12/2015 dtype: int64 - name: 01/12/2016 dtype: int64 - name: 01/12/2017 dtype: int64 - name: 01/12/2018 dtype: int64 - name: 01/12/2019 dtype: int64 - name: 01/12/2020 dtype: int64 - name: 01/12/2021 dtype: int64 - name: 01/12/2022 dtype: int64 - name: 01/12/2023 dtype: int64 - name: 02/01/2015 dtype: int64 - name: 02/01/2016 dtype: int64 - name: 02/01/2018 dtype: int64 - name: 02/01/2019 dtype: int64 - name: 02/01/2020 dtype: int64 - name: 02/01/2021 dtype: int64 - name: 02/01/2022 dtype: int64 - name: 02/01/2023 dtype: int64 - name: 02/01/2024 dtype: int64 - name: 02/02/2015 dtype: int64 - name: 02/02/2016 dtype: int64 - name: 02/02/2017 dtype: int64 - name: 02/02/2018 dtype: int64 - name: 02/02/2020 dtype: int64 - name: 02/02/2021 dtype: int64 - name: 02/02/2022 dtype: int64 - name: 02/02/2023 dtype: int64 - name: 02/03/2010 dtype: int64 - name: 02/03/2016 dtype: int64 - 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name: 30/10/2020 dtype: int64 - name: 30/10/2021 dtype: int64 - name: 30/10/2022 dtype: int64 - name: 30/10/2023 dtype: int64 - name: 30/11/2015 dtype: int64 - name: 30/11/2016 dtype: int64 - name: 30/11/2017 dtype: int64 - name: 30/11/2018 dtype: int64 - name: 30/11/2019 dtype: int64 - name: 30/11/2020 dtype: int64 - name: 30/11/2021 dtype: int64 - name: 30/11/2022 dtype: int64 - name: 30/11/2023 dtype: int64 - name: 30/12/2008 dtype: int64 - name: 30/12/2009 dtype: int64 - name: 30/12/2015 dtype: int64 - name: 30/12/2016 dtype: int64 - name: 30/12/2018 dtype: int64 - name: 30/12/2019 dtype: int64 - name: 30/12/2020 dtype: int64 - name: 30/12/2021 dtype: int64 - name: 30/12/2022 dtype: int64 - name: 30/12/2023 dtype: int64 - name: 31/01/2009 dtype: int64 - name: 31/01/2018 dtype: int64 - name: 31/01/2019 dtype: int64 - name: 31/01/2020 dtype: int64 - name: 31/01/2021 dtype: int64 - name: 31/01/2022 dtype: int64 - name: 31/01/2023 dtype: int64 - name: 31/03/2009 dtype: int64 - name: 31/03/2012 dtype: int64 - name: 31/03/2016 dtype: int64 - name: 31/03/2017 dtype: int64 - name: 31/03/2019 dtype: int64 - name: 31/03/2020 dtype: int64 - name: 31/03/2021 dtype: int64 - name: 31/03/2022 dtype: int64 - name: 31/03/2023 dtype: int64 - name: 31/05/2016 dtype: int64 - name: 31/05/2017 dtype: int64 - name: 31/05/2018 dtype: int64 - name: 31/05/2019 dtype: int64 - name: 31/05/2020 dtype: int64 - name: 31/05/2021 dtype: int64 - name: 31/05/2022 dtype: int64 - name: 31/05/2023 dtype: int64 - name: 31/07/2008 dtype: int64 - name: 31/07/2016 dtype: int64 - name: 31/07/2017 dtype: int64 - name: 31/07/2018 dtype: int64 - name: 31/07/2019 dtype: int64 - name: 31/07/2020 dtype: int64 - name: 31/07/2021 dtype: int64 - name: 31/07/2022 dtype: int64 - name: 31/07/2023 dtype: int64 - name: 31/08/2009 dtype: int64 - name: 31/08/2017 dtype: int64 - name: 31/08/2018 dtype: int64 - name: 31/08/2019 dtype: int64 - name: 31/08/2020 dtype: int64 - name: 31/08/2021 dtype: int64 - name: 31/08/2022 dtype: int64 - name: 31/08/2023 dtype: int64 - name: 31/10/2008 dtype: int64 - name: 31/10/2017 dtype: int64 - name: 31/10/2018 dtype: int64 - name: 31/10/2019 dtype: int64 - name: 31/10/2020 dtype: int64 - name: 31/10/2021 dtype: int64 - name: 31/10/2022 dtype: int64 - name: 31/10/2023 dtype: int64 - name: 31/12/2007 dtype: int64 - name: 31/12/2015 dtype: int64 - name: 31/12/2017 dtype: int64 - name: 31/12/2018 dtype: int64 - name: 31/12/2019 dtype: int64 - name: 31/12/2020 dtype: int64 - name: 31/12/2021 dtype: int64 - name: 31/12/2022 dtype: int64 - name: 31/12/2023 dtype: int64 splits: - name: train num_bytes: 596396375 num_examples: 5144 download_size: 174754628 dataset_size: 596396375 configs: - config_name: default data_files: - split: train path: data/train-* ---

DataStudio/OCRWordLevelClear_04

--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 32994104944.528 num_examples: 6777332 download_size: 32267197160 dataset_size: 32994104944.528 configs: - config_name: default data_files: - split: train path: data/train-* ---

AdapterOcean/chemistry_dataset_standardized_cluster_0_alpaca

--- dataset_info: features: - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 14675587 num_examples: 5546 download_size: 6391991 dataset_size: 14675587 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "chemistry_dataset_standardized_cluster_0_alpaca" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

amphora/rewrite-se-quant-alp

--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 31370080 num_examples: 11013 download_size: 16594547 dataset_size: 31370080 configs: - config_name: default data_files: - split: train path: data/train-* ---

shape-ai/beaches

--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 1566551.0 num_examples: 1 download_size: 1568255 dataset_size: 1566551.0 --- # Dataset Card for "beaches" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

autoevaluate/autoeval-staging-eval-project-17e9fcc1-7454805

--- type: predictions tags: - autotrain - evaluation datasets: - ag_news eval_info: task: multi_class_classification model: andi611/distilbert-base-uncased-ner-agnews metrics: [] dataset_name: ag_news dataset_config: default dataset_split: test col_mapping: text: text target: label --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Multi-class Text Classification * Model: andi611/distilbert-base-uncased-ner-agnews * Dataset: ag_news To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model.

CognitiveLab/FS_test

--- dataset_info: features: - name: author dtype: string - name: duration dtype: int64 - name: description dtype: string - name: transcript struct: - name: metadata struct: - name: channels dtype: int64 - name: created dtype: string - name: duration dtype: float64 - name: model_info struct: - name: 30089e05-99d1-4376-b32e-c263170674af struct: - name: arch dtype: string - name: name dtype: string - name: version dtype: string - name: models sequence: string - name: request_id dtype: string - name: sha256 dtype: string - name: summary_info struct: - name: input_tokens dtype: int64 - name: model_uuid dtype: string - name: output_tokens dtype: int64 - name: transaction_key dtype: string - name: warnings dtype: 'null' - name: results struct: - name: channels list: - name: alternatives list: - name: confidence dtype: float64 - name: entities dtype: 'null' - name: paragraphs struct: - name: paragraphs list: - name: end dtype: float64 - name: num_words dtype: float64 - name: sentences list: - name: end dtype: float64 - name: start dtype: float64 - name: text dtype: string - name: speaker dtype: int64 - name: start dtype: float64 - name: transcript dtype: string - name: summaries dtype: 'null' - name: topics list: - name: end_word dtype: float64 - name: start_word dtype: float64 - name: text dtype: string - name: topics list: - name: confidence dtype: float64 - name: topic dtype: string - name: transcript dtype: string - name: translations dtype: 'null' - name: words list: - name: confidence dtype: float64 - name: end dtype: float64 - name: punctuated_word dtype: string - name: speaker dtype: int64 - name: speaker_confidence dtype: float64 - name: start dtype: float64 - name: word dtype: string - name: detected_language dtype: string - name: language_confidence dtype: float64 - name: search dtype: 'null' - name: summary struct: - name: result dtype: string - name: short dtype: string - name: utterances dtype: 'null' - name: audio_path dtype: string - name: link dtype: string - name: title dtype: string - name: views dtype: int64 splits: - name: train num_bytes: 62271386 num_examples: 522 download_size: 22172106 dataset_size: 62271386 configs: - config_name: default data_files: - split: train path: data/train-* ---

mask-distilled-one-sec-cv12/chunk_22

--- dataset_info: features: - name: logits sequence: float32 - name: mfcc sequence: sequence: float64 splits: - name: train num_bytes: 1073011700 num_examples: 210725 download_size: 1093912534 dataset_size: 1073011700 --- # Dataset Card for "chunk_22" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Alpaca69B/reviews_appstore_instagram_absa

--- dataset_info: features: - name: title dtype: string - name: content dtype: string - name: category dtype: string - name: aspect dtype: string - name: sentiment dtype: string - name: combined dtype: string - name: text dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1025846.404 num_examples: 346 - name: validation num_bytes: 216435.802 num_examples: 73 - name: test num_bytes: 222365.55 num_examples: 75 download_size: 2608530 dataset_size: 1464647.7559999998 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: validation path: data/validation-* ---

jinaai/fashion-captions-de

--- license: cc-by-4.0 dataset_info: features: - name: text dtype: string - name: image dtype: image splits: - name: train num_bytes: 282285477 num_examples: 10000 - name: test num_bytes: 56612023.875 num_examples: 2001 download_size: 320681179 dataset_size: 338897500.875 task_categories: - text-to-image multilinguality: - monolingual language: - de size_categories: - 1K<n<10K source_datasets: - original pretty_name: Fashion12k DE --- <br><br> <p align="center"> <img src="https://github.com/jina-ai/finetuner/blob/main/docs/_static/finetuner-logo-ani.svg?raw=true" alt="Finetuner logo: Finetuner helps you to create experiments in order to improve embeddings on search tasks. It accompanies you to deliver the last mile of performance-tuning for neural search applications." width="150px"> </p> <p align="center"> <b>The data offered by Jina AI, Finetuner team.</b> </p> ## Summary This dataset is a German-language dataset based on the [Fashion12K](https://github.com/Toloka/Fashion12K_german_queries) dataset, which originally contains both English and German text descriptions for each item. This dataset was used to to finetuner CLIP using the [Finetuner](https://finetuner.jina.ai/) tool. ## Fine-tuning Please refer to our documentation: [Multilingual Text-to-Image Search with MultilingualCLIP](https://finetuner.jina.ai/notebooks/multilingual_text_to_image/) and blog [Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models](https://jina.ai/news/improving-search-quality-non-english-queries-fine-tuned-multilingual-clip-models/) ## Instances Each data point consists of a 'text' and an 'image' field, where the 'text' field describes an item of clothing in German, and the 'image' field contains and image of that item of clothing. ## Fields - 'text': A string describing the item of clothing. - 'image': A `PIL.Image.Image` object containing the image. Note that when accessing the image column: `dataset[0]["image"]` the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. `dataset[0]["image"]` should always be preferred over dataset["image"][0]. ## Splits | | train | test | |------------|-------|------| | # of items | 10000 | 2001 | ## Source Images were sampled from the [Fashion200K dataset](https://github.com/xthan/fashion-200k). ## Annotations Data was annotated using [Toloka](https://toloka.ai/). See their site for more details. ## Licensing Information This work is licensed under a Creative Commons Attribution 4.0 International License. ## Contributors Thanks to contributors from [Jina AI](https://jina.ai) and [Toloka](https://toloka.ai) for adding this dataset.

indicbench/arc_kn

--- dataset_info: - config_name: ARC-Challenge features: - name: answerKey dtype: string - name: choices struct: - name: label sequence: string - name: text sequence: string - name: id dtype: string - name: question dtype: string splits: - name: validation num_bytes: 233068 num_examples: 299 - name: test num_bytes: 904224 num_examples: 1172 download_size: 414164 dataset_size: 1137292 - config_name: default features: - name: _data_files list: - name: filename dtype: string - name: _fingerprint dtype: string - name: _format_columns dtype: 'null' - name: _format_type dtype: 'null' - name: _output_all_columns dtype: bool - name: _split dtype: 'null' splits: - name: validation num_bytes: 54 num_examples: 1 - name: test num_bytes: 54 num_examples: 1 download_size: 6510 dataset_size: 108 configs: - config_name: ARC-Challenge data_files: - split: validation path: ARC-Challenge/validation-* - split: test path: ARC-Challenge/test-* - config_name: default data_files: - split: validation path: data/validation-* - split: test path: data/test-* ---

sobamchan/aclsum

--- license: mit task_categories: - summarization language: - en pretty_name: aclsum size_categories: - n<1K configs: - config_name: abstractive default: true data_files: - split: train path: "abstractive/train.jsonl" - split: validation path: "abstractive/val.jsonl" - split: test path: "abstractive/test.jsonl" - config_name: extractive data_files: - split: train path: "extractive/train.jsonl" - split: validation path: "extractive/val.jsonl" - split: test path: "extractive/test.jsonl" --- # ACLSum: A New Dataset for Aspect-based Summarization of Scientific Publications This repository contains data for our paper "ACLSum: A New Dataset for Aspect-based Summarization of Scientific Publications" and a small utility class to work with it. ## HuggingFace datasets You can also use Huggin Face datasets to load ACLSum ([dataset link](https://huggingface.co/datasets/sobamchan/aclsum)). This would be convenient if you want to train transformer models using our dataset. Just do, ```py from datasets import load_dataset dataset = load_dataset("sobamchan/aclsum", "challenge", split="train") ```

mlfoundations/open_lm_example_data

--- license: mit ---

liuyanchen1015/MULTI_VALUE_mrpc_possessives_belong

--- dataset_info: features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: label dtype: int64 - name: idx dtype: int64 - name: value_score dtype: int64 splits: - name: test num_bytes: 212907 num_examples: 741 - name: train num_bytes: 431892 num_examples: 1493 - name: validation num_bytes: 53815 num_examples: 184 download_size: 454461 dataset_size: 698614 --- # Dataset Card for "MULTI_VALUE_mrpc_possessives_belong" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

charsiu/librispeech_full_frame_labels

--- dataset_info: features: - name: chapter_id dtype: int64 - name: file dtype: string - name: frame_labels sequence: string - name: frame_labels_10ms sequence: string - name: id dtype: string - name: speaker_id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 3303356482 num_examples: 281191 download_size: 219671524 dataset_size: 3303356482 --- # Dataset Card for "librispeech_full_frame_labels" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Iceclear/DIV8K_TrainingSet

--- license: apache-2.0 task_categories: - image-to-image size_categories: - 1K<n<10K --- The training set of [DIV8K](https://competitions.codalab.org/competitions/22217#participate). ## Citation ```bibtex @inproceedings{gu2019div8k, title={Div8k: Diverse 8k resolution image dataset}, author={Gu, Shuhang and Lugmayr, Andreas and Danelljan, Martin and Fritsche, Manuel and Lamour, Julien and Timofte, Radu}, booktitle={ICCVW}, year={2019}, } ```

tyzhu/squad_context_v3_train_30_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: 991636 num_examples: 378 - name: validation num_bytes: 113558 num_examples: 60 download_size: 188469 dataset_size: 1105194 --- # Dataset Card for "squad_context_v3_train_30_eval_10" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

CM/codexglue_code2text_javascript

--- dataset_info: features: - name: id dtype: int32 - name: repo dtype: string - name: path dtype: string - name: func_name dtype: string - name: original_string dtype: string - name: language dtype: string - name: code dtype: string - name: code_tokens sequence: string - name: docstring dtype: string - name: docstring_tokens sequence: string - name: sha dtype: string - name: url dtype: string splits: - name: train num_bytes: 160860431 num_examples: 58025 - name: validation num_bytes: 10337344 num_examples: 3885 - name: test num_bytes: 10190713 num_examples: 3291 download_size: 65795549 dataset_size: 181388488 --- # Dataset Card for "codexglue_code2text_javascript" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

galman33/gal_yair_8300_100x100_fixed

--- dataset_info: features: - name: lat dtype: float64 - name: lon dtype: float64 - name: country_code dtype: class_label: names: '0': ad '1': ae '2': al '3': aq '4': ar '5': au '6': bd '7': be '8': bg '9': bm '10': bo '11': br '12': bt '13': bw '14': ca '15': ch '16': cl '17': co '18': cz '19': de '20': dk '21': ec '22': ee '23': es '24': fi '25': fr '26': gb '27': gh '28': gl '29': gr '30': gt '31': hk '32': hr '33': hu '34': id '35': ie '36': il '37': is '38': it '39': ix '40': jp '41': kg '42': kh '43': kr '44': la '45': lk '46': ls '47': lt '48': lu '49': lv '50': me '51': mg '52': mk '53': mn '54': mo '55': mt '56': mx '57': my '58': nl '59': 'no' '60': nz '61': pe '62': ph '63': pl '64': pt '65': ro '66': rs '67': ru '68': se '69': sg '70': si '71': sk '72': sn '73': sz '74': th '75': tn '76': tr '77': tw '78': ua '79': ug '80': us '81': uy '82': za - name: image dtype: image splits: - name: train num_bytes: 142019429.5 num_examples: 8300 download_size: 141877783 dataset_size: 142019429.5 --- # Dataset Card for "gal_yair_8300_100x100_fixed" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

ibupari/hitobrot

--- dataset_info: features: - name: title dtype: string - name: subtitle dtype: string - name: paragraph dtype: string - name: sentences dtype: string splits: - name: train num_bytes: 1324745 num_examples: 1000 download_size: 264663 dataset_size: 1324745 configs: - config_name: default data_files: - split: train path: data/train-* ---

open-llm-leaderboard/details_lgaalves__tinyllama-1.1b-chat-v0.3_platypus

--- pretty_name: Evaluation run of lgaalves/tinyllama-1.1b-chat-v0.3_platypus dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [lgaalves/tinyllama-1.1b-chat-v0.3_platypus](https://huggingface.co/lgaalves/tinyllama-1.1b-chat-v0.3_platypus)\ \ 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_lgaalves__tinyllama-1.1b-chat-v0.3_platypus\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-23T23:05:04.270048](https://huggingface.co/datasets/open-llm-leaderboard/details_lgaalves__tinyllama-1.1b-chat-v0.3_platypus/blob/main/results_2023-10-23T23-05-04.270048.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\": 0.0025167785234899327,\n\ \ \"em_stderr\": 0.0005131152834514911,\n \"f1\": 0.049414848993288615,\n\ \ \"f1_stderr\": 0.0012773102707031435,\n \"acc\": 0.2816590502599073,\n\ \ \"acc_stderr\": 0.00797944490002852\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.0025167785234899327,\n \"em_stderr\": 0.0005131152834514911,\n\ \ \"f1\": 0.049414848993288615,\n \"f1_stderr\": 0.0012773102707031435\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.00530705079605762,\n \ \ \"acc_stderr\": 0.002001305720948044\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.5580110497237569,\n \"acc_stderr\": 0.013957584079108994\n\ \ }\n}\n```" repo_url: https://huggingface.co/lgaalves/tinyllama-1.1b-chat-v0.3_platypus 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_10T14_53_56.428911 path: - '**/details_harness|arc:challenge|25_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-10-10T14-53-56.428911.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_23T23_05_04.270048 path: - '**/details_harness|drop|3_2023-10-23T23-05-04.270048.parquet' - split: latest path: - '**/details_harness|drop|3_2023-10-23T23-05-04.270048.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_23T23_05_04.270048 path: - '**/details_harness|gsm8k|5_2023-10-23T23-05-04.270048.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-10-23T23-05-04.270048.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hellaswag|10_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-management|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-management|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-10-10T14-53-56.428911.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-international_law|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-management|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-marketing|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-sociology|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-virology|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-10-10T14-53-56.428911.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_10_10T14_53_56.428911 path: - '**/details_harness|truthfulqa:mc|0_2023-10-10T14-53-56.428911.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-10-10T14-53-56.428911.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_23T23_05_04.270048 path: - '**/details_harness|winogrande|5_2023-10-23T23-05-04.270048.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-10-23T23-05-04.270048.parquet' - config_name: results data_files: - split: 2023_10_10T14_53_56.428911 path: - results_2023-10-10T14-53-56.428911.parquet - split: 2023_10_23T23_05_04.270048 path: - results_2023-10-23T23-05-04.270048.parquet - split: latest path: - results_2023-10-23T23-05-04.270048.parquet --- # Dataset Card for Evaluation run of lgaalves/tinyllama-1.1b-chat-v0.3_platypus ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/lgaalves/tinyllama-1.1b-chat-v0.3_platypus - **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 [lgaalves/tinyllama-1.1b-chat-v0.3_platypus](https://huggingface.co/lgaalves/tinyllama-1.1b-chat-v0.3_platypus) 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_lgaalves__tinyllama-1.1b-chat-v0.3_platypus", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-23T23:05:04.270048](https://huggingface.co/datasets/open-llm-leaderboard/details_lgaalves__tinyllama-1.1b-chat-v0.3_platypus/blob/main/results_2023-10-23T23-05-04.270048.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": 0.0025167785234899327, "em_stderr": 0.0005131152834514911, "f1": 0.049414848993288615, "f1_stderr": 0.0012773102707031435, "acc": 0.2816590502599073, "acc_stderr": 0.00797944490002852 }, "harness|drop|3": { "em": 0.0025167785234899327, "em_stderr": 0.0005131152834514911, "f1": 0.049414848993288615, "f1_stderr": 0.0012773102707031435 }, "harness|gsm8k|5": { "acc": 0.00530705079605762, "acc_stderr": 0.002001305720948044 }, "harness|winogrande|5": { "acc": 0.5580110497237569, "acc_stderr": 0.013957584079108994 } } ``` ### 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]

CATIE-AQ/wino_x_fr_prompt_coreference

--- language: - fr license: - mit size_categories: - 10K<n<100K tags: - coreference - DFP - french prompts annotations_creators: - found language_creators: - found multilinguality: - monolingual source_datasets: - wino_x --- # wino_x_fr_prompt_coreference ## Summary **wino_x_fr_prompt_coreference** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP). It contains **27,930** rows that can be used for a coreference task. The original data (without prompts) comes from the dataset [wino_x](https://huggingface.co/datasets/demelin/wino_x) by Emelin et al. 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: ``` wino_x = load_dataset('demelin/wino_x','lm_en_fr') sentence = wino_x['test'][i]['context_fr'] option1 = wino_x['test'][i]['option1_fr'] option2 = wino_x['test'][i]['option2_fr'] targets = str(wino_x['test'][i]['answer']).replace("1",wino_x['test'][i]['option1_fr']).replace("2",wino_x['test'][i]['option2_fr']) ``` # Splits - `train` with 27,930 samples - no `valid` split - no `test` split # How to use? ``` from datasets import load_dataset dataset = load_dataset("CATIE-AQ/wino_x_fr_prompt_coreference") ``` # Citation ## Original data > @inproceedings{Emelin2021WinoXMW, title={Wino-X: Multilingual Winograd Schemas for Commonsense Reasoning and Coreference Resolution}, author={Denis Emelin and Rico Sennrich}, booktitle={EMNLP}, year={2021} } ## 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 MIT

mugeakbulut/Kadi_Sicilleri-ds-mini

--- dataset_info: features: - name: DOCNO dtype: int64 - name: ARXIVID_xml dtype: string - name: ARXIVID dtype: string - name: Link dtype: string - name: Title dtype: string - name: Authors dtype: string - name: 'Year ' dtype: int64 - name: Submitted on (gün, ay, yıl olarak submission tarihi) dtype: string - name: Submission history (v1 de dahil olmak üzere hepsi) dtype: string - name: Last revised tarihi dtype: string - name: content dtype: string - name: Comments dtype: string - name: Subject dtype: string - name: Journal reference dtype: string - name: DOI dtype: string - name: Cite as dtype: string - name: 'Unnamed: 16' dtype: float64 - name: 'Unnamed: 17' dtype: float64 - name: 'Unnamed: 18' dtype: float64 - name: 'Unnamed: 19' dtype: float64 - name: 'Unnamed: 20' dtype: string - name: Abstract_no dtype: string - name: 'Unnamed: 22' dtype: string - name: review dtype: string - name: content_length dtype: int64 splits: - name: train num_bytes: 1486810.797385621 num_examples: 413 - name: validation num_bytes: 165601.2026143791 num_examples: 46 download_size: 810073 dataset_size: 1652412.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

freshpearYoon/train_free_9

--- dataset_info: features: - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 9604734776 num_examples: 10000 download_size: 1379496640 dataset_size: 9604734776 configs: - config_name: default data_files: - split: train path: data/train-* ---

autoevaluate/autoeval-staging-eval-project-e1907042-7494833

--- type: predictions tags: - autotrain - evaluation datasets: - clinc_oos eval_info: task: multi_class_classification model: aytugkaya/distilbert-base-uncased-finetuned-clinc metrics: [] dataset_name: clinc_oos dataset_config: small dataset_split: test col_mapping: text: text target: intent --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Multi-class Text Classification * Model: aytugkaya/distilbert-base-uncased-finetuned-clinc * Dataset: clinc_oos To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model.

gggggggg123/sber-golos

--- dataset_info: features: - name: text dtype: string - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 7677527180 num_examples: 7993 - name: validation num_bytes: 761700288 num_examples: 793 - name: test num_bytes: 9599558230 num_examples: 9994 download_size: 3068066823 dataset_size: 18038785698 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---

open-llm-leaderboard/details_RWKV__rwkv-raven-1b5

--- pretty_name: Evaluation run of RWKV/rwkv-raven-1b5 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [RWKV/rwkv-raven-1b5](https://huggingface.co/RWKV/rwkv-raven-1b5) 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_RWKV__rwkv-raven-1b5\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-25T00:45:24.942259](https://huggingface.co/datasets/open-llm-leaderboard/details_RWKV__rwkv-raven-1b5/blob/main/results_2023-10-25T00-45-24.942259.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\": 0.05641778523489933,\n\ \ \"em_stderr\": 0.002362857556122875,\n \"f1\": 0.09820364932885885,\n\ \ \"f1_stderr\": 0.002610921727017063,\n \"acc\": 0.26953433307024466,\n\ \ \"acc_stderr\": 0.007004760840490157\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.05641778523489933,\n \"em_stderr\": 0.002362857556122875,\n\ \ \"f1\": 0.09820364932885885,\n \"f1_stderr\": 0.002610921727017063\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.0,\n \"acc_stderr\"\ : 0.0\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.5390686661404893,\n\ \ \"acc_stderr\": 0.014009521680980314\n }\n}\n```" repo_url: https://huggingface.co/RWKV/rwkv-raven-1b5 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_03T05_21_18.307582 path: - '**/details_harness|arc:challenge|25_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-09-03T05:21:18.307582.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_25T00_45_24.942259 path: - '**/details_harness|drop|3_2023-10-25T00-45-24.942259.parquet' - split: latest path: - '**/details_harness|drop|3_2023-10-25T00-45-24.942259.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_25T00_45_24.942259 path: - '**/details_harness|gsm8k|5_2023-10-25T00-45-24.942259.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-10-25T00-45-24.942259.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hellaswag|10_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-03T05:21:18.307582.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-management|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-virology|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-03T05:21:18.307582.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_03T05_21_18.307582 path: - '**/details_harness|truthfulqa:mc|0_2023-09-03T05:21:18.307582.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-09-03T05:21:18.307582.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_25T00_45_24.942259 path: - '**/details_harness|winogrande|5_2023-10-25T00-45-24.942259.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-10-25T00-45-24.942259.parquet' - config_name: results data_files: - split: 2023_09_03T05_21_18.307582 path: - results_2023-09-03T05:21:18.307582.parquet - split: 2023_10_25T00_45_24.942259 path: - results_2023-10-25T00-45-24.942259.parquet - split: latest path: - results_2023-10-25T00-45-24.942259.parquet --- # Dataset Card for Evaluation run of RWKV/rwkv-raven-1b5 ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/RWKV/rwkv-raven-1b5 - **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 [RWKV/rwkv-raven-1b5](https://huggingface.co/RWKV/rwkv-raven-1b5) 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_RWKV__rwkv-raven-1b5", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-25T00:45:24.942259](https://huggingface.co/datasets/open-llm-leaderboard/details_RWKV__rwkv-raven-1b5/blob/main/results_2023-10-25T00-45-24.942259.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": 0.05641778523489933, "em_stderr": 0.002362857556122875, "f1": 0.09820364932885885, "f1_stderr": 0.002610921727017063, "acc": 0.26953433307024466, "acc_stderr": 0.007004760840490157 }, "harness|drop|3": { "em": 0.05641778523489933, "em_stderr": 0.002362857556122875, "f1": 0.09820364932885885, "f1_stderr": 0.002610921727017063 }, "harness|gsm8k|5": { "acc": 0.0, "acc_stderr": 0.0 }, "harness|winogrande|5": { "acc": 0.5390686661404893, "acc_stderr": 0.014009521680980314 } } ``` ### 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]

autoevaluate/autoeval-eval-futin__feed-top_vi_-7f787f-2245771643

--- type: predictions tags: - autotrain - evaluation datasets: - futin/feed eval_info: task: text_zero_shot_classification model: bigscience/bloom-560m metrics: [] dataset_name: futin/feed dataset_config: top_vi_ dataset_split: test col_mapping: text: text classes: classes target: target --- # Dataset Card for AutoTrain Evaluator This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset: * Task: Zero-Shot Text Classification * Model: bigscience/bloom-560m * Dataset: futin/feed * Config: top_vi_ * Split: test To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator). ## Contributions Thanks to [@futin](https://huggingface.co/futin) for evaluating this model.

AppleHarem/frost_arknights

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of frost (Arknights) This is the dataset of frost (Arknights), containing 74 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 | 74 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 182 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | raw-stage3-eyes | 200 | [Download](dataset-raw-stage3-eyes.zip) | 3-stage cropped (with eye-focus) raw data with meta information. | | 384x512 | 74 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x704 | 74 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x880 | 74 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 182 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 182 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-p512-640 | 142 | [Download](dataset-stage3-p512-640.zip) | 3-stage cropped dataset with the area not less than 512x512 pixels. | | stage3-eyes-640 | 200 | [Download](dataset-stage3-eyes-640.zip) | 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 640 pixels. | | stage3-eyes-800 | 200 | [Download](dataset-stage3-eyes-800.zip) | 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 800 pixels. |

cheafdevo56/InfluentialTriplets

--- dataset_info: features: - name: query struct: - name: abstract dtype: string - name: corpus_id dtype: int64 - name: title dtype: string - name: pos struct: - name: abstract dtype: string - name: corpus_id dtype: int64 - name: title dtype: string - name: neg struct: - name: abstract dtype: string - name: corpus_id dtype: int64 - name: score dtype: int64 - name: title dtype: string splits: - name: train num_bytes: 73286160.22355364 num_examples: 19227 - name: validation num_bytes: 8145447.776446358 num_examples: 2137 download_size: 48583049 dataset_size: 81431608.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

results-sd-v1-5-sd-v2-1-if-v1-0-karlo/cf3a3ead

--- dataset_info: features: - name: result dtype: string - name: id dtype: int64 splits: - name: train num_bytes: 180 num_examples: 10 download_size: 1335 dataset_size: 180 --- # Dataset Card for "cf3a3ead" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

NathanRoll/TalkBank_CA_CORAAL

--- dataset_info: features: - name: audio sequence: float32 - name: __index_level_0__ dtype: string splits: - name: train num_bytes: 9325350278 num_examples: 85 download_size: 9338282164 dataset_size: 9325350278 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "TalkBank_CA_CORAAL" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

nguyenth1312/traditional_clothes

--- dataset_info: features: - name: image dtype: image - name: 'Unnamed: 0' dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 148739545.0 num_examples: 59 download_size: 110961466 dataset_size: 148739545.0 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "traditional_clothes" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Slowblood/guanaco-llama2-1k

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 1654448 num_examples: 1000 download_size: 966693 dataset_size: 1654448 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "guanaco-llama2-1k" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Hev832/nah

--- license: mit ---

huggingartists/gizmo

--- language: - en tags: - huggingartists - lyrics --- # Dataset Card for "huggingartists/gizmo" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [How to use](#how-to-use) - [Dataset Structure](#dataset-structure) - [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) - [About](#about) ## Dataset Description - **Homepage:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - **Repository:** [https://github.com/AlekseyKorshuk/huggingartists](https://github.com/AlekseyKorshuk/huggingartists) - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Size of the generated dataset:** 0.361766 MB <div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/9dd7d13194aa588b336b78bcf05530f0.638x638x1.jpg')"> </div> </div> <a href="https://huggingface.co/huggingartists/gizmo"> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> </a> <div style="text-align: center; font-size: 16px; font-weight: 800">gizmo</div> <a href="https://genius.com/artists/gizmo"> <div style="text-align: center; font-size: 14px;">@gizmo</div> </a> </div> ### Dataset Summary The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available [here](https://huggingface.co/huggingartists/gizmo). ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages en ## How to use How to load this dataset directly with the datasets library: ```python from datasets import load_dataset dataset = load_dataset("huggingartists/gizmo") ``` ## Dataset Structure An example of 'train' looks as follows. ``` This example was too long and was cropped: { "text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..." } ``` ### Data Fields The data fields are the same among all splits. - `text`: a `string` feature. ### Data Splits | train |validation|test| |------:|---------:|---:| |248| -| -| 'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code: ```python from datasets import load_dataset, Dataset, DatasetDict import numpy as np datasets = load_dataset("huggingartists/gizmo") train_percentage = 0.9 validation_percentage = 0.07 test_percentage = 0.03 train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])*train_percentage), int(len(datasets['train']['text'])*(train_percentage + validation_percentage))]) datasets = DatasetDict( { 'train': Dataset.from_dict({'text': list(train)}), 'validation': Dataset.from_dict({'text': list(validation)}), 'test': Dataset.from_dict({'text': list(test)}) } ) ``` ## 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 ``` @InProceedings{huggingartists, author={Aleksey Korshuk} year=2021 } ``` ## About *Built by Aleksey Korshuk* [![Follow](https://img.shields.io/github/followers/AlekseyKorshuk?style=social)](https://github.com/AlekseyKorshuk) [![Follow](https://img.shields.io/twitter/follow/alekseykorshuk?style=social)](https://twitter.com/intent/follow?screen_name=alekseykorshuk) [![Follow](https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram)](https://t.me/joinchat/_CQ04KjcJ-4yZTky) For more details, visit the project repository. [![GitHub stars](https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social)](https://github.com/AlekseyKorshuk/huggingartists)

aliciiavs/sign_language_image_dataset

--- dataset_info: features: - name: image dtype: image - name: label dtype: class_label: names: '0': A '1': B '2': C '3': D '4': E '5': F '6': G '7': H '8': I '9': K '10': L '11': M '12': N '13': O '14': P '15': Q '16': R '17': S '18': T '19': U '20': V '21': W '22': X '23': Y splits: - name: train num_bytes: 1817258226.134 num_examples: 8442 download_size: 1803545459 dataset_size: 1817258226.134 configs: - config_name: default data_files: - split: train path: data/train-* ---

ravithejads/telugu_gpteacher_ft

--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 119244218 num_examples: 87228 download_size: 57558525 dataset_size: 119244218 configs: - config_name: default data_files: - split: train path: data/train-* ---

FreedomIntelligence/sharegpt-arabic

--- license: apache-2.0 --- Arabic ShareGPT data translated by gpt-3.5-turbo. The dataset is used in the research related to [MultilingualSIFT](https://github.com/FreedomIntelligence/MultilingualSIFT).

Ali-C137/Goud-Sum-Instruct-test-v0

--- dataset_info: features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 22447355 num_examples: 9497 download_size: 10247768 dataset_size: 22447355 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "Goud-Sum-Instruct" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

kewu93/sketch_100

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: val path: data/val-* dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 1431746.0 num_examples: 100 - name: val num_bytes: 1431746.0 num_examples: 100 download_size: 2858841 dataset_size: 2863492.0 --- # Dataset Card for "sketch_100" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

opinosis

--- annotations_creators: - crowdsourced language: - en language_creators: - found license: - apache-2.0 multilinguality: - monolingual pretty_name: Opinosis size_categories: - n<1K source_datasets: - original task_categories: - summarization task_ids: [] paperswithcode_id: opinosis tags: - abstractive-summarization dataset_info: features: - name: review_sents dtype: string - name: summaries sequence: string splits: - name: train num_bytes: 741270 num_examples: 51 download_size: 757398 dataset_size: 741270 --- # Dataset Card for "opinosis" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** http://kavita-ganesan.com/opinosis-opinion-dataset/ - **Repository:** https://github.com/kavgan/opinosis-summarization - **Paper:** [Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions](https://aclanthology.org/C10-1039/) - **Point of Contact:** [Kavita Ganesan](mailto:kavita@opinosis.ai) - **Size of downloaded dataset files:** 0.75 MB - **Size of the generated dataset:** 0.74 MB - **Total amount of disk used:** 1.50 MB ### Dataset Summary The Opinosis Opinion Dataset consists of sentences extracted from reviews for 51 topics. Topics and opinions are obtained from Tripadvisor, Edmunds.com and Amazon.com. ### 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 #### default - **Size of downloaded dataset files:** 0.75 MB - **Size of the generated dataset:** 0.74 MB - **Total amount of disk used:** 1.50 MB An example of 'train' looks as follows. ``` { "review_sents": "This is a fake topic. \nThe topics have multiple sentence inputs. \n", "summaries": ["This is a gold summary for topic 1. \nSentences in gold summaries are separated by newlines.", "This is another gold summary for topic 1. \nSentences in gold summaries are separated by newlines."] } ``` ### Data Fields The data fields are the same among all splits. #### default - `review_sents`: a `string` feature. - `summaries`: a `list` of `string` features. ### Data Splits | name |train| |-------|----:| |default| 51| ## 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 The license for this dataset is Apache License 2.0 and can be found [here](https://github.com/kavgan/opinosis-summarization/blob/master/LICENSE). ### Citation Information ``` @inproceedings{ganesan2010opinosis, title={Opinosis: a graph-based approach to abstractive summarization of highly redundant opinions}, author={Ganesan, Kavita and Zhai, ChengXiang and Han, Jiawei}, booktitle={Proceedings of the 23rd International Conference on Computational Linguistics}, pages={340--348}, year={2010}, organization={Association for Computational Linguistics} } ``` ### Contributions Thanks to [@thomwolf](https://github.com/thomwolf), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.

CyberHarem/leila_fireemblem

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of leila (Fire Emblem) This is the dataset of leila (Fire Emblem), containing 15 images and their tags. The core tags of this character are `red_hair, short_hair, breasts, red_eyes, mole, hair_over_one_eye, mole_under_mouth, bangs, medium_breasts, shiny_hair, lips`, 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 | 15 | 17.24 MiB | [Download](https://huggingface.co/datasets/CyberHarem/leila_fireemblem/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 15 | 10.22 MiB | [Download](https://huggingface.co/datasets/CyberHarem/leila_fireemblem/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 29 | 18.53 MiB | [Download](https://huggingface.co/datasets/CyberHarem/leila_fireemblem/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 15 | 15.68 MiB | [Download](https://huggingface.co/datasets/CyberHarem/leila_fireemblem/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 29 | 24.63 MiB | [Download](https://huggingface.co/datasets/CyberHarem/leila_fireemblem/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/leila_fireemblem', 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 | 15 | ![](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, cape, holding, solo, belt, looking_at_viewer, smile, elbow_gloves, thighhighs, mask, parted_lips, shiny, bracelet, full_body, purple_bodysuit, bare_shoulders, cleavage, fingerless_gloves, high_heel_boots, knife, simple_background, thigh_boots, weapon | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | cape | holding | solo | belt | looking_at_viewer | smile | elbow_gloves | thighhighs | mask | parted_lips | shiny | bracelet | full_body | purple_bodysuit | bare_shoulders | cleavage | fingerless_gloves | high_heel_boots | knife | simple_background | thigh_boots | weapon | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:----------|:-------|:-------|:--------------------|:--------|:---------------|:-------------|:-------|:--------------|:--------|:-----------|:------------|:------------------|:-----------------|:-----------|:--------------------|:------------------|:--------|:--------------------|:--------------|:---------| | 0 | 15 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |

lissadesu/codeqa_v2

--- dataset_info: features: - name: labNo dtype: float64 - name: taskNo dtype: float64 - name: questioner dtype: string - name: question dtype: string - name: code dtype: string - name: startLine dtype: float64 - name: endLine dtype: float64 - name: questionType dtype: string - name: answer dtype: string - name: src dtype: string - name: code_processed dtype: string - name: id dtype: string - name: raw_code dtype: string - name: raw_comment dtype: string - name: comment dtype: string - name: q_code dtype: string splits: - name: train num_bytes: 46842820 num_examples: 35360 download_size: 17749500 dataset_size: 46842820 --- # Dataset Card for "codeqa_v2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

freshpearYoon/train_free_45

--- dataset_info: features: - name: input_features sequence: sequence: float32 - name: labels sequence: int64 splits: - name: train num_bytes: 9604567144 num_examples: 10000 download_size: 1352498488 dataset_size: 9604567144 configs: - config_name: default data_files: - split: train path: data/train-* ---

open-llm-leaderboard/details_ChaoticNeutrals__RP_Vision_7B

--- pretty_name: Evaluation run of ChaoticNeutrals/RP_Vision_7B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [ChaoticNeutrals/RP_Vision_7B](https://huggingface.co/ChaoticNeutrals/RP_Vision_7B)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_ChaoticNeutrals__RP_Vision_7B\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-23T05:58:51.196010](https://huggingface.co/datasets/open-llm-leaderboard/details_ChaoticNeutrals__RP_Vision_7B/blob/main/results_2024-03-23T05-58-51.196010.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\": 0.6501517888097911,\n\ \ \"acc_stderr\": 0.032048221712222776,\n \"acc_norm\": 0.6507990701154603,\n\ \ \"acc_norm_stderr\": 0.03270238816915129,\n \"mc1\": 0.5263157894736842,\n\ \ \"mc1_stderr\": 0.017479241161975457,\n \"mc2\": 0.6850422329465207,\n\ \ \"mc2_stderr\": 0.015032479220010228\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6877133105802048,\n \"acc_stderr\": 0.013542598541688067,\n\ \ \"acc_norm\": 0.7064846416382252,\n \"acc_norm_stderr\": 0.013307250444941108\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7117108145787692,\n\ \ \"acc_stderr\": 0.004520406331084043,\n \"acc_norm\": 0.8781119298944433,\n\ \ \"acc_norm_stderr\": 0.0032648787375868854\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252605,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252605\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6666666666666666,\n\ \ \"acc_stderr\": 0.04072314811876837,\n \"acc_norm\": 0.6666666666666666,\n\ \ \"acc_norm_stderr\": 0.04072314811876837\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.7105263157894737,\n \"acc_stderr\": 0.03690677986137283,\n\ \ \"acc_norm\": 0.7105263157894737,\n \"acc_norm_stderr\": 0.03690677986137283\n\ \ },\n \"harness|hendrycksTest-business_ethics|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-clinical_knowledge|5\"\ : {\n \"acc\": 0.7132075471698113,\n \"acc_stderr\": 0.027834912527544067,\n\ \ \"acc_norm\": 0.7132075471698113,\n \"acc_norm_stderr\": 0.027834912527544067\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7430555555555556,\n\ \ \"acc_stderr\": 0.03653946969442099,\n \"acc_norm\": 0.7430555555555556,\n\ \ \"acc_norm_stderr\": 0.03653946969442099\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.46,\n \"acc_stderr\": 0.05009082659620333,\n \ \ \"acc_norm\": 0.46,\n \"acc_norm_stderr\": 0.05009082659620333\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.55,\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\": 0.27,\n \"acc_stderr\": 0.044619604333847394,\n \ \ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.044619604333847394\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.653179190751445,\n\ \ \"acc_stderr\": 0.036291466701596636,\n \"acc_norm\": 0.653179190751445,\n\ \ \"acc_norm_stderr\": 0.036291466701596636\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3627450980392157,\n \"acc_stderr\": 0.04784060704105654,\n\ \ \"acc_norm\": 0.3627450980392157,\n \"acc_norm_stderr\": 0.04784060704105654\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.78,\n \"acc_stderr\": 0.04163331998932262,\n \"acc_norm\": 0.78,\n\ \ \"acc_norm_stderr\": 0.04163331998932262\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.6042553191489362,\n \"acc_stderr\": 0.03196758697835362,\n\ \ \"acc_norm\": 0.6042553191489362,\n \"acc_norm_stderr\": 0.03196758697835362\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5087719298245614,\n\ \ \"acc_stderr\": 0.04702880432049615,\n \"acc_norm\": 0.5087719298245614,\n\ \ \"acc_norm_stderr\": 0.04702880432049615\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.5517241379310345,\n \"acc_stderr\": 0.04144311810878151,\n\ \ \"acc_norm\": 0.5517241379310345,\n \"acc_norm_stderr\": 0.04144311810878151\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.4126984126984127,\n \"acc_stderr\": 0.02535574126305527,\n \"\ acc_norm\": 0.4126984126984127,\n \"acc_norm_stderr\": 0.02535574126305527\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4444444444444444,\n\ \ \"acc_stderr\": 0.044444444444444495,\n \"acc_norm\": 0.4444444444444444,\n\ \ \"acc_norm_stderr\": 0.044444444444444495\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\": 0.7870967741935484,\n\ \ \"acc_stderr\": 0.023287665127268545,\n \"acc_norm\": 0.7870967741935484,\n\ \ \"acc_norm_stderr\": 0.023287665127268545\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.4975369458128079,\n \"acc_stderr\": 0.03517945038691063,\n\ \ \"acc_norm\": 0.4975369458128079,\n \"acc_norm_stderr\": 0.03517945038691063\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.67,\n \"acc_stderr\": 0.04725815626252609,\n \"acc_norm\"\ : 0.67,\n \"acc_norm_stderr\": 0.04725815626252609\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7757575757575758,\n \"acc_stderr\": 0.032568666616811015,\n\ \ \"acc_norm\": 0.7757575757575758,\n \"acc_norm_stderr\": 0.032568666616811015\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7929292929292929,\n \"acc_stderr\": 0.028869778460267042,\n \"\ acc_norm\": 0.7929292929292929,\n \"acc_norm_stderr\": 0.028869778460267042\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8963730569948186,\n \"acc_stderr\": 0.02199531196364424,\n\ \ \"acc_norm\": 0.8963730569948186,\n \"acc_norm_stderr\": 0.02199531196364424\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6820512820512821,\n \"acc_stderr\": 0.02361088430892786,\n \ \ \"acc_norm\": 0.6820512820512821,\n \"acc_norm_stderr\": 0.02361088430892786\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.34814814814814815,\n \"acc_stderr\": 0.029045600290616248,\n \ \ \"acc_norm\": 0.34814814814814815,\n \"acc_norm_stderr\": 0.029045600290616248\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6974789915966386,\n \"acc_stderr\": 0.02983796238829193,\n \ \ \"acc_norm\": 0.6974789915966386,\n \"acc_norm_stderr\": 0.02983796238829193\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.36423841059602646,\n \"acc_stderr\": 0.03929111781242742,\n \"\ acc_norm\": 0.36423841059602646,\n \"acc_norm_stderr\": 0.03929111781242742\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8385321100917431,\n \"acc_stderr\": 0.01577623925616323,\n \"\ acc_norm\": 0.8385321100917431,\n \"acc_norm_stderr\": 0.01577623925616323\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5324074074074074,\n \"acc_stderr\": 0.03402801581358966,\n \"\ acc_norm\": 0.5324074074074074,\n \"acc_norm_stderr\": 0.03402801581358966\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8382352941176471,\n \"acc_stderr\": 0.025845017986926917,\n \"\ acc_norm\": 0.8382352941176471,\n \"acc_norm_stderr\": 0.025845017986926917\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8059071729957806,\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\": 0.695067264573991,\n\ \ \"acc_stderr\": 0.030898610882477515,\n \"acc_norm\": 0.695067264573991,\n\ \ \"acc_norm_stderr\": 0.030898610882477515\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7862595419847328,\n \"acc_stderr\": 0.0359546161177469,\n\ \ \"acc_norm\": 0.7862595419847328,\n \"acc_norm_stderr\": 0.0359546161177469\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.743801652892562,\n \"acc_stderr\": 0.03984979653302871,\n \"acc_norm\"\ : 0.743801652892562,\n \"acc_norm_stderr\": 0.03984979653302871\n },\n\ \ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7962962962962963,\n\ \ \"acc_stderr\": 0.03893542518824847,\n \"acc_norm\": 0.7962962962962963,\n\ \ \"acc_norm_stderr\": 0.03893542518824847\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7668711656441718,\n \"acc_stderr\": 0.0332201579577674,\n\ \ \"acc_norm\": 0.7668711656441718,\n \"acc_norm_stderr\": 0.0332201579577674\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.48214285714285715,\n\ \ \"acc_stderr\": 0.047427623612430116,\n \"acc_norm\": 0.48214285714285715,\n\ \ \"acc_norm_stderr\": 0.047427623612430116\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7961165048543689,\n \"acc_stderr\": 0.03989139859531771,\n\ \ \"acc_norm\": 0.7961165048543689,\n \"acc_norm_stderr\": 0.03989139859531771\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8803418803418803,\n\ \ \"acc_stderr\": 0.021262719400406964,\n \"acc_norm\": 0.8803418803418803,\n\ \ \"acc_norm_stderr\": 0.021262719400406964\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \ \ \"acc_norm\": 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8263090676883781,\n\ \ \"acc_stderr\": 0.013547415658662257,\n \"acc_norm\": 0.8263090676883781,\n\ \ \"acc_norm_stderr\": 0.013547415658662257\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7369942196531792,\n \"acc_stderr\": 0.023703099525258165,\n\ \ \"acc_norm\": 0.7369942196531792,\n \"acc_norm_stderr\": 0.023703099525258165\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.47039106145251397,\n\ \ \"acc_stderr\": 0.016693154927383557,\n \"acc_norm\": 0.47039106145251397,\n\ \ \"acc_norm_stderr\": 0.016693154927383557\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.738562091503268,\n \"acc_stderr\": 0.025160998214292456,\n\ \ \"acc_norm\": 0.738562091503268,\n \"acc_norm_stderr\": 0.025160998214292456\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7202572347266881,\n\ \ \"acc_stderr\": 0.02549425935069491,\n \"acc_norm\": 0.7202572347266881,\n\ \ \"acc_norm_stderr\": 0.02549425935069491\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7283950617283951,\n \"acc_stderr\": 0.024748624490537368,\n\ \ \"acc_norm\": 0.7283950617283951,\n \"acc_norm_stderr\": 0.024748624490537368\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.48936170212765956,\n \"acc_stderr\": 0.029820747191422473,\n \ \ \"acc_norm\": 0.48936170212765956,\n \"acc_norm_stderr\": 0.029820747191422473\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4654498044328553,\n\ \ \"acc_stderr\": 0.0127397115540457,\n \"acc_norm\": 0.4654498044328553,\n\ \ \"acc_norm_stderr\": 0.0127397115540457\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6911764705882353,\n \"acc_stderr\": 0.02806499816704009,\n\ \ \"acc_norm\": 0.6911764705882353,\n \"acc_norm_stderr\": 0.02806499816704009\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6470588235294118,\n \"acc_stderr\": 0.01933314202079716,\n \ \ \"acc_norm\": 0.6470588235294118,\n \"acc_norm_stderr\": 0.01933314202079716\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6727272727272727,\n\ \ \"acc_stderr\": 0.0449429086625209,\n \"acc_norm\": 0.6727272727272727,\n\ \ \"acc_norm_stderr\": 0.0449429086625209\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.710204081632653,\n \"acc_stderr\": 0.02904308868330433,\n\ \ \"acc_norm\": 0.710204081632653,\n \"acc_norm_stderr\": 0.02904308868330433\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8407960199004975,\n\ \ \"acc_stderr\": 0.02587064676616913,\n \"acc_norm\": 0.8407960199004975,\n\ \ \"acc_norm_stderr\": 0.02587064676616913\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.87,\n \"acc_stderr\": 0.033799766898963086,\n \ \ \"acc_norm\": 0.87,\n \"acc_norm_stderr\": 0.033799766898963086\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5120481927710844,\n\ \ \"acc_stderr\": 0.038913644958358175,\n \"acc_norm\": 0.5120481927710844,\n\ \ \"acc_norm_stderr\": 0.038913644958358175\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.847953216374269,\n \"acc_stderr\": 0.027539122889061452,\n\ \ \"acc_norm\": 0.847953216374269,\n \"acc_norm_stderr\": 0.027539122889061452\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.5263157894736842,\n\ \ \"mc1_stderr\": 0.017479241161975457,\n \"mc2\": 0.6850422329465207,\n\ \ \"mc2_stderr\": 0.015032479220010228\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8263614838200474,\n \"acc_stderr\": 0.010646116480330996\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6209249431387415,\n \ \ \"acc_stderr\": 0.013363630295088363\n }\n}\n```" repo_url: https://huggingface.co/ChaoticNeutrals/RP_Vision_7B leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|arc:challenge|25_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-23T05-58-51.196010.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|gsm8k|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hellaswag|10_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-23T05-58-51.196010.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-management|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-23T05-58-51.196010.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|truthfulqa:mc|0_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-23T05-58-51.196010.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_23T05_58_51.196010 path: - '**/details_harness|winogrande|5_2024-03-23T05-58-51.196010.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-23T05-58-51.196010.parquet' - config_name: results data_files: - split: 2024_03_23T05_58_51.196010 path: - results_2024-03-23T05-58-51.196010.parquet - split: latest path: - results_2024-03-23T05-58-51.196010.parquet --- # Dataset Card for Evaluation run of ChaoticNeutrals/RP_Vision_7B  Dataset automatically created during the evaluation run of model [ChaoticNeutrals/RP_Vision_7B](https://huggingface.co/ChaoticNeutrals/RP_Vision_7B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_ChaoticNeutrals__RP_Vision_7B", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-23T05:58:51.196010](https://huggingface.co/datasets/open-llm-leaderboard/details_ChaoticNeutrals__RP_Vision_7B/blob/main/results_2024-03-23T05-58-51.196010.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": 0.6501517888097911, "acc_stderr": 0.032048221712222776, "acc_norm": 0.6507990701154603, "acc_norm_stderr": 0.03270238816915129, "mc1": 0.5263157894736842, "mc1_stderr": 0.017479241161975457, "mc2": 0.6850422329465207, "mc2_stderr": 0.015032479220010228 }, "harness|arc:challenge|25": { "acc": 0.6877133105802048, "acc_stderr": 0.013542598541688067, "acc_norm": 0.7064846416382252, "acc_norm_stderr": 0.013307250444941108 }, "harness|hellaswag|10": { "acc": 0.7117108145787692, "acc_stderr": 0.004520406331084043, "acc_norm": 0.8781119298944433, "acc_norm_stderr": 0.0032648787375868854 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6666666666666666, "acc_stderr": 0.04072314811876837, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.04072314811876837 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7105263157894737, "acc_stderr": 0.03690677986137283, "acc_norm": 0.7105263157894737, "acc_norm_stderr": 0.03690677986137283 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.58, "acc_stderr": 0.04960449637488583, "acc_norm": 0.58, "acc_norm_stderr": 0.04960449637488583 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7132075471698113, "acc_stderr": 0.027834912527544067, "acc_norm": 0.7132075471698113, "acc_norm_stderr": 0.027834912527544067 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7430555555555556, "acc_stderr": 0.03653946969442099, "acc_norm": 0.7430555555555556, "acc_norm_stderr": 0.03653946969442099 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.46, "acc_stderr": 0.05009082659620333, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.55, "acc_stderr": 0.05, "acc_norm": 0.55, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.653179190751445, "acc_stderr": 0.036291466701596636, "acc_norm": 0.653179190751445, "acc_norm_stderr": 0.036291466701596636 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3627450980392157, "acc_stderr": 0.04784060704105654, "acc_norm": 0.3627450980392157, "acc_norm_stderr": 0.04784060704105654 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.78, "acc_stderr": 0.04163331998932262, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932262 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6042553191489362, "acc_stderr": 0.03196758697835362, "acc_norm": 0.6042553191489362, "acc_norm_stderr": 0.03196758697835362 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5087719298245614, "acc_stderr": 0.04702880432049615, "acc_norm": 0.5087719298245614, "acc_norm_stderr": 0.04702880432049615 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5517241379310345, "acc_stderr": 0.04144311810878151, "acc_norm": 0.5517241379310345, "acc_norm_stderr": 0.04144311810878151 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4126984126984127, "acc_stderr": 0.02535574126305527, "acc_norm": 0.4126984126984127, "acc_norm_stderr": 0.02535574126305527 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4444444444444444, "acc_stderr": 0.044444444444444495, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.044444444444444495 }, "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": 0.7870967741935484, "acc_stderr": 0.023287665127268545, "acc_norm": 0.7870967741935484, "acc_norm_stderr": 0.023287665127268545 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4975369458128079, "acc_stderr": 0.03517945038691063, "acc_norm": 0.4975369458128079, "acc_norm_stderr": 0.03517945038691063 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.67, "acc_stderr": 0.04725815626252609, "acc_norm": 0.67, "acc_norm_stderr": 0.04725815626252609 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7757575757575758, "acc_stderr": 0.032568666616811015, "acc_norm": 0.7757575757575758, "acc_norm_stderr": 0.032568666616811015 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7929292929292929, "acc_stderr": 0.028869778460267042, "acc_norm": 0.7929292929292929, "acc_norm_stderr": 0.028869778460267042 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8963730569948186, "acc_stderr": 0.02199531196364424, "acc_norm": 0.8963730569948186, "acc_norm_stderr": 0.02199531196364424 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6820512820512821, "acc_stderr": 0.02361088430892786, "acc_norm": 0.6820512820512821, "acc_norm_stderr": 0.02361088430892786 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.34814814814814815, "acc_stderr": 0.029045600290616248, "acc_norm": 0.34814814814814815, "acc_norm_stderr": 0.029045600290616248 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6974789915966386, "acc_stderr": 0.02983796238829193, "acc_norm": 0.6974789915966386, "acc_norm_stderr": 0.02983796238829193 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.36423841059602646, "acc_stderr": 0.03929111781242742, "acc_norm": 0.36423841059602646, "acc_norm_stderr": 0.03929111781242742 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8385321100917431, "acc_stderr": 0.01577623925616323, "acc_norm": 0.8385321100917431, "acc_norm_stderr": 0.01577623925616323 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5324074074074074, "acc_stderr": 0.03402801581358966, "acc_norm": 0.5324074074074074, "acc_norm_stderr": 0.03402801581358966 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8382352941176471, "acc_stderr": 0.025845017986926917, "acc_norm": 0.8382352941176471, "acc_norm_stderr": 0.025845017986926917 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8059071729957806, "acc_stderr": 0.025744902532290916, "acc_norm": 0.8059071729957806, "acc_norm_stderr": 0.025744902532290916 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.695067264573991, "acc_stderr": 0.030898610882477515, "acc_norm": 0.695067264573991, "acc_norm_stderr": 0.030898610882477515 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7862595419847328, "acc_stderr": 0.0359546161177469, "acc_norm": 0.7862595419847328, "acc_norm_stderr": 0.0359546161177469 }, "harness|hendrycksTest-international_law|5": { "acc": 0.743801652892562, "acc_stderr": 0.03984979653302871, "acc_norm": 0.743801652892562, "acc_norm_stderr": 0.03984979653302871 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7962962962962963, "acc_stderr": 0.03893542518824847, "acc_norm": 0.7962962962962963, "acc_norm_stderr": 0.03893542518824847 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7668711656441718, "acc_stderr": 0.0332201579577674, "acc_norm": 0.7668711656441718, "acc_norm_stderr": 0.0332201579577674 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.48214285714285715, "acc_stderr": 0.047427623612430116, "acc_norm": 0.48214285714285715, "acc_norm_stderr": 0.047427623612430116 }, "harness|hendrycksTest-management|5": { "acc": 0.7961165048543689, "acc_stderr": 0.03989139859531771, "acc_norm": 0.7961165048543689, "acc_norm_stderr": 0.03989139859531771 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8803418803418803, "acc_stderr": 0.021262719400406964, "acc_norm": 0.8803418803418803, "acc_norm_stderr": 0.021262719400406964 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8263090676883781, "acc_stderr": 0.013547415658662257, "acc_norm": 0.8263090676883781, "acc_norm_stderr": 0.013547415658662257 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7369942196531792, "acc_stderr": 0.023703099525258165, "acc_norm": 0.7369942196531792, "acc_norm_stderr": 0.023703099525258165 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.47039106145251397, "acc_stderr": 0.016693154927383557, "acc_norm": 0.47039106145251397, "acc_norm_stderr": 0.016693154927383557 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.738562091503268, "acc_stderr": 0.025160998214292456, "acc_norm": 0.738562091503268, "acc_norm_stderr": 0.025160998214292456 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7202572347266881, "acc_stderr": 0.02549425935069491, "acc_norm": 0.7202572347266881, "acc_norm_stderr": 0.02549425935069491 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7283950617283951, "acc_stderr": 0.024748624490537368, "acc_norm": 0.7283950617283951, "acc_norm_stderr": 0.024748624490537368 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.48936170212765956, "acc_stderr": 0.029820747191422473, "acc_norm": 0.48936170212765956, "acc_norm_stderr": 0.029820747191422473 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4654498044328553, "acc_stderr": 0.0127397115540457, "acc_norm": 0.4654498044328553, "acc_norm_stderr": 0.0127397115540457 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6911764705882353, "acc_stderr": 0.02806499816704009, "acc_norm": 0.6911764705882353, "acc_norm_stderr": 0.02806499816704009 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6470588235294118, "acc_stderr": 0.01933314202079716, "acc_norm": 0.6470588235294118, "acc_norm_stderr": 0.01933314202079716 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6727272727272727, "acc_stderr": 0.0449429086625209, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.0449429086625209 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.710204081632653, "acc_stderr": 0.02904308868330433, "acc_norm": 0.710204081632653, "acc_norm_stderr": 0.02904308868330433 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8407960199004975, "acc_stderr": 0.02587064676616913, "acc_norm": 0.8407960199004975, "acc_norm_stderr": 0.02587064676616913 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.87, "acc_stderr": 0.033799766898963086, "acc_norm": 0.87, "acc_norm_stderr": 0.033799766898963086 }, "harness|hendrycksTest-virology|5": { "acc": 0.5120481927710844, "acc_stderr": 0.038913644958358175, "acc_norm": 0.5120481927710844, "acc_norm_stderr": 0.038913644958358175 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.847953216374269, "acc_stderr": 0.027539122889061452, "acc_norm": 0.847953216374269, "acc_norm_stderr": 0.027539122889061452 }, "harness|truthfulqa:mc|0": { "mc1": 0.5263157894736842, "mc1_stderr": 0.017479241161975457, "mc2": 0.6850422329465207, "mc2_stderr": 0.015032479220010228 }, "harness|winogrande|5": { "acc": 0.8263614838200474, "acc_stderr": 0.010646116480330996 }, "harness|gsm8k|5": { "acc": 0.6209249431387415, "acc_stderr": 0.013363630295088363 } } ``` ## Dataset Details ### Dataset Description  - **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]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

FalconX80/nisoridataset-1k

--- dataset_info: features: - name: Prompt dtype: string - name: Answer dtype: string - name: text dtype: string splits: - name: train num_bytes: 279807 num_examples: 1000 download_size: 16815 dataset_size: 279807 configs: - config_name: default data_files: - split: train path: data/train-* ---

tororoin/pid-f

--- dataset_info: features: - name: document dtype: int64 - name: full_text dtype: string - name: tokens sequence: string - name: trailing_whitespace sequence: bool - name: labels sequence: string splits: - name: train num_bytes: 92523591 num_examples: 6807 download_size: 25505349 dataset_size: 92523591 configs: - config_name: default data_files: - split: train path: data/train-* ---

AdapterOcean/augmentatio-standardized_cluster_9_alpaca

--- dataset_info: features: - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 3406053 num_examples: 1482 download_size: 1387156 dataset_size: 3406053 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "augmentatio-standardized_cluster_9_alpaca" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Rosenberg/weibo_ner

--- license: mit ---

jlbaker361/actstu-runway-50

--- dataset_info: features: - name: image dtype: image - name: prompt dtype: string - name: seed dtype: int64 - name: steps dtype: int64 splits: - name: train num_bytes: 14154155.0 num_examples: 28 download_size: 14155865 dataset_size: 14154155.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

didi0di/Kakao_ChatData

--- dataset_info: features: - name: req dtype: string - name: res dtype: string splits: - name: train num_bytes: 8479418 num_examples: 73384 download_size: 5633370 dataset_size: 8479418 --- # Dataset Card for "Kakao_ChatData" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

open-llm-leaderboard/details_mlabonne__NeuralPipe-7B-ties

--- pretty_name: Evaluation run of mlabonne/NeuralPipe-7B-ties dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mlabonne/NeuralPipe-7B-ties](https://huggingface.co/mlabonne/NeuralPipe-7B-ties)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_mlabonne__NeuralPipe-7B-ties\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-29T18:23:14.168913](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__NeuralPipe-7B-ties/blob/main/results_2023-12-29T18-23-14.168913.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\": 0.6463521388608168,\n\ \ \"acc_stderr\": 0.03211851750269888,\n \"acc_norm\": 0.6467147686147078,\n\ \ \"acc_norm_stderr\": 0.032775359620950996,\n \"mc1\": 0.44430844553243576,\n\ \ \"mc1_stderr\": 0.01739458625074317,\n \"mc2\": 0.6137333376102074,\n\ \ \"mc2_stderr\": 0.015322517797295732\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6407849829351536,\n \"acc_stderr\": 0.014020224155839157,\n\ \ \"acc_norm\": 0.6791808873720137,\n \"acc_norm_stderr\": 0.013640943091946533\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6729735112527385,\n\ \ \"acc_stderr\": 0.004681682605347881,\n \"acc_norm\": 0.8603863772156941,\n\ \ \"acc_norm_stderr\": 0.0034587739347195527\n },\n \"harness|hendrycksTest-abstract_algebra|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-anatomy|5\": {\n \"acc\": 0.6148148148148148,\n\ \ \"acc_stderr\": 0.04203921040156279,\n \"acc_norm\": 0.6148148148148148,\n\ \ \"acc_norm_stderr\": 0.04203921040156279\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.7302631578947368,\n \"acc_stderr\": 0.03611780560284898,\n\ \ \"acc_norm\": 0.7302631578947368,\n \"acc_norm_stderr\": 0.03611780560284898\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\": 0.690566037735849,\n \"acc_stderr\": 0.028450154794118637,\n\ \ \"acc_norm\": 0.690566037735849,\n \"acc_norm_stderr\": 0.028450154794118637\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7777777777777778,\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\": 0.48,\n \"acc_stderr\": 0.050211673156867795,\n \ \ \"acc_norm\": 0.48,\n \"acc_norm_stderr\": 0.050211673156867795\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\ acc\": 0.46,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\"\ : 0.46,\n \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621504,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621504\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6416184971098265,\n\ \ \"acc_stderr\": 0.036563436533531585,\n \"acc_norm\": 0.6416184971098265,\n\ \ \"acc_norm_stderr\": 0.036563436533531585\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.4019607843137255,\n \"acc_stderr\": 0.04878608714466996,\n\ \ \"acc_norm\": 0.4019607843137255,\n \"acc_norm_stderr\": 0.04878608714466996\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.76,\n \"acc_stderr\": 0.042923469599092816,\n \"acc_norm\": 0.76,\n\ \ \"acc_norm_stderr\": 0.042923469599092816\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5872340425531914,\n \"acc_stderr\": 0.03218471141400351,\n\ \ \"acc_norm\": 0.5872340425531914,\n \"acc_norm_stderr\": 0.03218471141400351\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.5175438596491229,\n\ \ \"acc_stderr\": 0.04700708033551038,\n \"acc_norm\": 0.5175438596491229,\n\ \ \"acc_norm_stderr\": 0.04700708033551038\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\"\ : 0.42063492063492064,\n \"acc_stderr\": 0.025424835086924,\n \"acc_norm\"\ : 0.42063492063492064,\n \"acc_norm_stderr\": 0.025424835086924\n },\n\ \ \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4523809523809524,\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\": 0.36,\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\": 0.7677419354838709,\n\ \ \"acc_stderr\": 0.024022256130308235,\n \"acc_norm\": 0.7677419354838709,\n\ \ \"acc_norm_stderr\": 0.024022256130308235\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.4876847290640394,\n \"acc_stderr\": 0.035169204442208966,\n\ \ \"acc_norm\": 0.4876847290640394,\n \"acc_norm_stderr\": 0.035169204442208966\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\"\ : 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7636363636363637,\n \"acc_stderr\": 0.03317505930009181,\n\ \ \"acc_norm\": 0.7636363636363637,\n \"acc_norm_stderr\": 0.03317505930009181\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7878787878787878,\n \"acc_stderr\": 0.029126522834586815,\n \"\ acc_norm\": 0.7878787878787878,\n \"acc_norm_stderr\": 0.029126522834586815\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.9015544041450777,\n \"acc_stderr\": 0.021500249576033456,\n\ \ \"acc_norm\": 0.9015544041450777,\n \"acc_norm_stderr\": 0.021500249576033456\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6461538461538462,\n \"acc_stderr\": 0.02424378399406216,\n \ \ \"acc_norm\": 0.6461538461538462,\n \"acc_norm_stderr\": 0.02424378399406216\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.34074074074074073,\n \"acc_stderr\": 0.028897748741131154,\n \ \ \"acc_norm\": 0.34074074074074073,\n \"acc_norm_stderr\": 0.028897748741131154\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.6974789915966386,\n \"acc_stderr\": 0.029837962388291932,\n\ \ \"acc_norm\": 0.6974789915966386,\n \"acc_norm_stderr\": 0.029837962388291932\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.304635761589404,\n \"acc_stderr\": 0.03757949922943343,\n \"acc_norm\"\ : 0.304635761589404,\n \"acc_norm_stderr\": 0.03757949922943343\n },\n\ \ \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.8440366972477065,\n\ \ \"acc_stderr\": 0.01555580271359017,\n \"acc_norm\": 0.8440366972477065,\n\ \ \"acc_norm_stderr\": 0.01555580271359017\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\ : {\n \"acc\": 0.5231481481481481,\n \"acc_stderr\": 0.03406315360711507,\n\ \ \"acc_norm\": 0.5231481481481481,\n \"acc_norm_stderr\": 0.03406315360711507\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8235294117647058,\n \"acc_stderr\": 0.02675640153807897,\n \"\ acc_norm\": 0.8235294117647058,\n \"acc_norm_stderr\": 0.02675640153807897\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8185654008438819,\n \"acc_stderr\": 0.025085961144579665,\n \ \ \"acc_norm\": 0.8185654008438819,\n \"acc_norm_stderr\": 0.025085961144579665\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6816143497757847,\n\ \ \"acc_stderr\": 0.03126580522513713,\n \"acc_norm\": 0.6816143497757847,\n\ \ \"acc_norm_stderr\": 0.03126580522513713\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7862595419847328,\n \"acc_stderr\": 0.0359546161177469,\n\ \ \"acc_norm\": 0.7862595419847328,\n \"acc_norm_stderr\": 0.0359546161177469\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\": 0.7962962962962963,\n\ \ \"acc_stderr\": 0.03893542518824847,\n \"acc_norm\": 0.7962962962962963,\n\ \ \"acc_norm_stderr\": 0.03893542518824847\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.7668711656441718,\n \"acc_stderr\": 0.0332201579577674,\n\ \ \"acc_norm\": 0.7668711656441718,\n \"acc_norm_stderr\": 0.0332201579577674\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.4642857142857143,\n\ \ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.4642857142857143,\n\ \ \"acc_norm_stderr\": 0.04733667890053756\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\": 0.8547008547008547,\n\ \ \"acc_stderr\": 0.023086635086841407,\n \"acc_norm\": 0.8547008547008547,\n\ \ \"acc_norm_stderr\": 0.023086635086841407\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8301404853128991,\n\ \ \"acc_stderr\": 0.013428186370608304,\n \"acc_norm\": 0.8301404853128991,\n\ \ \"acc_norm_stderr\": 0.013428186370608304\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7283236994219653,\n \"acc_stderr\": 0.02394851290546835,\n\ \ \"acc_norm\": 0.7283236994219653,\n \"acc_norm_stderr\": 0.02394851290546835\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.37318435754189944,\n\ \ \"acc_stderr\": 0.016175692013381964,\n \"acc_norm\": 0.37318435754189944,\n\ \ \"acc_norm_stderr\": 0.016175692013381964\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.738562091503268,\n \"acc_stderr\": 0.025160998214292456,\n\ \ \"acc_norm\": 0.738562091503268,\n \"acc_norm_stderr\": 0.025160998214292456\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7170418006430869,\n\ \ \"acc_stderr\": 0.02558306248998481,\n \"acc_norm\": 0.7170418006430869,\n\ \ \"acc_norm_stderr\": 0.02558306248998481\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7314814814814815,\n \"acc_stderr\": 0.024659685185967284,\n\ \ \"acc_norm\": 0.7314814814814815,\n \"acc_norm_stderr\": 0.024659685185967284\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.5,\n \"acc_stderr\": 0.029827499313594685,\n \"acc_norm\"\ : 0.5,\n \"acc_norm_stderr\": 0.029827499313594685\n },\n \"harness|hendrycksTest-professional_law|5\"\ : {\n \"acc\": 0.4667535853976532,\n \"acc_stderr\": 0.012741974333897229,\n\ \ \"acc_norm\": 0.4667535853976532,\n \"acc_norm_stderr\": 0.012741974333897229\n\ \ },\n \"harness|hendrycksTest-professional_medicine|5\": {\n \"acc\"\ : 0.6875,\n \"acc_stderr\": 0.02815637344037142,\n \"acc_norm\": 0.6875,\n\ \ \"acc_norm_stderr\": 0.02815637344037142\n },\n \"harness|hendrycksTest-professional_psychology|5\"\ : {\n \"acc\": 0.6666666666666666,\n \"acc_stderr\": 0.019070985589687495,\n\ \ \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.019070985589687495\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6727272727272727,\n\ \ \"acc_stderr\": 0.0449429086625209,\n \"acc_norm\": 0.6727272727272727,\n\ \ \"acc_norm_stderr\": 0.0449429086625209\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7346938775510204,\n \"acc_stderr\": 0.028263889943784593,\n\ \ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.028263889943784593\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8407960199004975,\n\ \ \"acc_stderr\": 0.025870646766169136,\n \"acc_norm\": 0.8407960199004975,\n\ \ \"acc_norm_stderr\": 0.025870646766169136\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.86,\n \"acc_stderr\": 0.0348735088019777,\n \ \ \"acc_norm\": 0.86,\n \"acc_norm_stderr\": 0.0348735088019777\n },\n\ \ \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5542168674698795,\n\ \ \"acc_stderr\": 0.03869543323472101,\n \"acc_norm\": 0.5542168674698795,\n\ \ \"acc_norm_stderr\": 0.03869543323472101\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\": 0.44430844553243576,\n\ \ \"mc1_stderr\": 0.01739458625074317,\n \"mc2\": 0.6137333376102074,\n\ \ \"mc2_stderr\": 0.015322517797295732\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8018942383583267,\n \"acc_stderr\": 0.011201862744487048\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.6952236542835482,\n \ \ \"acc_stderr\": 0.012679297549515427\n }\n}\n```" repo_url: https://huggingface.co/mlabonne/NeuralPipe-7B-ties leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|arc:challenge|25_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-29T18-23-14.168913.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|gsm8k|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hellaswag|10_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-29T18-23-14.168913.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-management|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-29T18-23-14.168913.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|truthfulqa:mc|0_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-29T18-23-14.168913.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_29T18_23_14.168913 path: - '**/details_harness|winogrande|5_2023-12-29T18-23-14.168913.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-29T18-23-14.168913.parquet' - config_name: results data_files: - split: 2023_12_29T18_23_14.168913 path: - results_2023-12-29T18-23-14.168913.parquet - split: latest path: - results_2023-12-29T18-23-14.168913.parquet --- # Dataset Card for Evaluation run of mlabonne/NeuralPipe-7B-ties  Dataset automatically created during the evaluation run of model [mlabonne/NeuralPipe-7B-ties](https://huggingface.co/mlabonne/NeuralPipe-7B-ties) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_mlabonne__NeuralPipe-7B-ties", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-29T18:23:14.168913](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__NeuralPipe-7B-ties/blob/main/results_2023-12-29T18-23-14.168913.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": 0.6463521388608168, "acc_stderr": 0.03211851750269888, "acc_norm": 0.6467147686147078, "acc_norm_stderr": 0.032775359620950996, "mc1": 0.44430844553243576, "mc1_stderr": 0.01739458625074317, "mc2": 0.6137333376102074, "mc2_stderr": 0.015322517797295732 }, "harness|arc:challenge|25": { "acc": 0.6407849829351536, "acc_stderr": 0.014020224155839157, "acc_norm": 0.6791808873720137, "acc_norm_stderr": 0.013640943091946533 }, "harness|hellaswag|10": { "acc": 0.6729735112527385, "acc_stderr": 0.004681682605347881, "acc_norm": 0.8603863772156941, "acc_norm_stderr": 0.0034587739347195527 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6148148148148148, "acc_stderr": 0.04203921040156279, "acc_norm": 0.6148148148148148, "acc_norm_stderr": 0.04203921040156279 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7302631578947368, "acc_stderr": 0.03611780560284898, "acc_norm": 0.7302631578947368, "acc_norm_stderr": 0.03611780560284898 }, "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": 0.690566037735849, "acc_stderr": 0.028450154794118637, "acc_norm": 0.690566037735849, "acc_norm_stderr": 0.028450154794118637 }, "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": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6416184971098265, "acc_stderr": 0.036563436533531585, "acc_norm": 0.6416184971098265, "acc_norm_stderr": 0.036563436533531585 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4019607843137255, "acc_stderr": 0.04878608714466996, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.04878608714466996 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.76, "acc_stderr": 0.042923469599092816, "acc_norm": 0.76, "acc_norm_stderr": 0.042923469599092816 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5872340425531914, "acc_stderr": 0.03218471141400351, "acc_norm": 0.5872340425531914, "acc_norm_stderr": 0.03218471141400351 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5175438596491229, "acc_stderr": 0.04700708033551038, "acc_norm": 0.5175438596491229, "acc_norm_stderr": 0.04700708033551038 }, "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": 0.42063492063492064, "acc_stderr": 0.025424835086924, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.025424835086924 }, "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": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7677419354838709, "acc_stderr": 0.024022256130308235, "acc_norm": 0.7677419354838709, "acc_norm_stderr": 0.024022256130308235 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4876847290640394, "acc_stderr": 0.035169204442208966, "acc_norm": 0.4876847290640394, "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": 0.7636363636363637, "acc_stderr": 0.03317505930009181, "acc_norm": 0.7636363636363637, "acc_norm_stderr": 0.03317505930009181 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7878787878787878, "acc_stderr": 0.029126522834586815, "acc_norm": 0.7878787878787878, "acc_norm_stderr": 0.029126522834586815 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9015544041450777, "acc_stderr": 0.021500249576033456, "acc_norm": 0.9015544041450777, "acc_norm_stderr": 0.021500249576033456 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6461538461538462, "acc_stderr": 0.02424378399406216, "acc_norm": 0.6461538461538462, "acc_norm_stderr": 0.02424378399406216 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.34074074074074073, "acc_stderr": 0.028897748741131154, "acc_norm": 0.34074074074074073, "acc_norm_stderr": 0.028897748741131154 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.6974789915966386, "acc_stderr": 0.029837962388291932, "acc_norm": 0.6974789915966386, "acc_norm_stderr": 0.029837962388291932 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.304635761589404, "acc_stderr": 0.03757949922943343, "acc_norm": 0.304635761589404, "acc_norm_stderr": 0.03757949922943343 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8440366972477065, "acc_stderr": 0.01555580271359017, "acc_norm": 0.8440366972477065, "acc_norm_stderr": 0.01555580271359017 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5231481481481481, "acc_stderr": 0.03406315360711507, "acc_norm": 0.5231481481481481, "acc_norm_stderr": 0.03406315360711507 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8235294117647058, "acc_stderr": 0.02675640153807897, "acc_norm": 0.8235294117647058, "acc_norm_stderr": 0.02675640153807897 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8185654008438819, "acc_stderr": 0.025085961144579665, "acc_norm": 0.8185654008438819, "acc_norm_stderr": 0.025085961144579665 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6816143497757847, "acc_stderr": 0.03126580522513713, "acc_norm": 0.6816143497757847, "acc_norm_stderr": 0.03126580522513713 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7862595419847328, "acc_stderr": 0.0359546161177469, "acc_norm": 0.7862595419847328, "acc_norm_stderr": 0.0359546161177469 }, "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": 0.7962962962962963, "acc_stderr": 0.03893542518824847, "acc_norm": 0.7962962962962963, "acc_norm_stderr": 0.03893542518824847 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.7668711656441718, "acc_stderr": 0.0332201579577674, "acc_norm": 0.7668711656441718, "acc_norm_stderr": 0.0332201579577674 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.4642857142857143, "acc_stderr": 0.04733667890053756, "acc_norm": 0.4642857142857143, "acc_norm_stderr": 0.04733667890053756 }, "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": 0.8547008547008547, "acc_stderr": 0.023086635086841407, "acc_norm": 0.8547008547008547, "acc_norm_stderr": 0.023086635086841407 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8301404853128991, "acc_stderr": 0.013428186370608304, "acc_norm": 0.8301404853128991, "acc_norm_stderr": 0.013428186370608304 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7283236994219653, "acc_stderr": 0.02394851290546835, "acc_norm": 0.7283236994219653, "acc_norm_stderr": 0.02394851290546835 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.37318435754189944, "acc_stderr": 0.016175692013381964, "acc_norm": 0.37318435754189944, "acc_norm_stderr": 0.016175692013381964 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.738562091503268, "acc_stderr": 0.025160998214292456, "acc_norm": 0.738562091503268, "acc_norm_stderr": 0.025160998214292456 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7170418006430869, "acc_stderr": 0.02558306248998481, "acc_norm": 0.7170418006430869, "acc_norm_stderr": 0.02558306248998481 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7314814814814815, "acc_stderr": 0.024659685185967284, "acc_norm": 0.7314814814814815, "acc_norm_stderr": 0.024659685185967284 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.5, "acc_stderr": 0.029827499313594685, "acc_norm": 0.5, "acc_norm_stderr": 0.029827499313594685 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.4667535853976532, "acc_stderr": 0.012741974333897229, "acc_norm": 0.4667535853976532, "acc_norm_stderr": 0.012741974333897229 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6875, "acc_stderr": 0.02815637344037142, "acc_norm": 0.6875, "acc_norm_stderr": 0.02815637344037142 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6666666666666666, "acc_stderr": 0.019070985589687495, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.019070985589687495 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6727272727272727, "acc_stderr": 0.0449429086625209, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.0449429086625209 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7346938775510204, "acc_stderr": 0.028263889943784593, "acc_norm": 0.7346938775510204, "acc_norm_stderr": 0.028263889943784593 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8407960199004975, "acc_stderr": 0.025870646766169136, "acc_norm": 0.8407960199004975, "acc_norm_stderr": 0.025870646766169136 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.86, "acc_stderr": 0.0348735088019777, "acc_norm": 0.86, "acc_norm_stderr": 0.0348735088019777 }, "harness|hendrycksTest-virology|5": { "acc": 0.5542168674698795, "acc_stderr": 0.03869543323472101, "acc_norm": 0.5542168674698795, "acc_norm_stderr": 0.03869543323472101 }, "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": 0.44430844553243576, "mc1_stderr": 0.01739458625074317, "mc2": 0.6137333376102074, "mc2_stderr": 0.015322517797295732 }, "harness|winogrande|5": { "acc": 0.8018942383583267, "acc_stderr": 0.011201862744487048 }, "harness|gsm8k|5": { "acc": 0.6952236542835482, "acc_stderr": 0.012679297549515427 } } ``` ## Dataset Details ### Dataset Description  - **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]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

argilla/kto-mix-13k

--- language: - en license: mit size_categories: - 1K<n<10K configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: prompt dtype: string - name: completion list: - name: content dtype: string - name: role dtype: string - name: label dtype: bool - name: rating dtype: float64 - name: dataset dtype: string splits: - name: train num_bytes: 44826263 num_examples: 12517 download_size: 18119695 dataset_size: 44826263 tags: - distilabel - synthetic - kto --- # Argilla KTO Mix 13 Dataset > A KTO signal transformed version of the highly loved [Argilla DPO Mix](https://huggingface.co/datasets/argilla/dpo-mix-7k), which is small cocktail combining DPO datasets built by Argilla with [distilabel](https://github.com/argilla-io/distilabel). The goal of this dataset is having a small, high-quality KTO dataset by filtering only highly rated chosen responses. <div> <img src="https://cdn-uploads.huggingface.co/production/uploads/60420dccc15e823a685f2b03/Csd2-zPji7iwIxyz6UFe1.webp"> </div> <p align="center"> <a href="https://github.com/argilla-io/distilabel"> <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/> </a> </p> ## Why KTO? The [KTO paper](https://arxiv.org/abs/2402.01306) states: - KTO matches or exceeds DPO performance at scales from 1B to 30B parameters.1 That is, taking a preference dataset of n DPO pairs and breaking it up into 2n examples for KTO can yield better generations, despite the model ostensibly learning from a weaker signal. - KTO can handle extreme data imbalances, matching DPO performance while using up to 90% fewer desirable examples (i.e., examples of good generations). Its success thus cannot be ascribed to the alignment data being sourced from a preference dataset. - When the pretrained model is sufficiently good, one can skip supervised finetuning and go straight to KTO without a loss in generation quality. In contrast, we find that without doing SFT first, DPO-aligned models are significantly worse at all scales. ## Reproduce KTO Transformation [Original DPO dataset: DPO mix 7k](https://huggingface.co/datasets/argilla/dpo-mix-7k) <a target="_blank" href="https://colab.research.google.com/drive/10bMnI3vvG4hEKblUhtLZKu01YSnPhmaF?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> </a>

gmongaras/BERT_Base_Cased_512_GLUE

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* dataset_info: features: - name: sentence dtype: string - name: label dtype: float64 - name: dataset_name dtype: string splits: - name: train num_bytes: 163269248 num_examples: 949728 - name: validation num_bytes: 12111201 num_examples: 69711 - name: test num_bytes: 64264632 num_examples: 425205 download_size: 135600002 dataset_size: 239645081 --- Dataset from: https://huggingface.co/datasets/glue Every split besides the ax split is in this dataset. Lines above 512 characters from the BERT-cased (bert-base-cased) tokenizer are removed

erbacher/personalized-proactive-conversations

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: id dtype: int64 - name: uid dtype: int64 - name: user dtype: string - name: conversation list: - name: assistant dtype: string - name: turn_id dtype: int64 - name: user dtype: string - name: __index_level_0__ dtype: int64 - name: queries list: - name: queries sequence: string - name: turnid dtype: int64 - name: messages list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 302752705 num_examples: 27870 - name: test num_bytes: 2117394 num_examples: 200 download_size: 143529145 dataset_size: 304870099 --- # Dataset Card for "personalized-proactive-conversations" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

abishekmahi/tamil-kavithai

--- license: mit task_categories: - text-generation language: - ta pretty_name: kavithai tags: - art - poem - webdataset ---

CyberHarem/hare_bluearchive

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of hare/小鈎ハレ/晴 (Blue Archive) This is the dataset of hare/小鈎ハレ/晴 (Blue Archive), containing 330 images and their tags. The core tags of this character are `long_hair, grey_hair, halo, green_eyes, ponytail, hair_ornament, cross_hair_ornament`, 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 | 330 | 470.16 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hare_bluearchive/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 1200 | 330 | 399.03 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hare_bluearchive/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 858 | 840.33 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hare_bluearchive/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | ### Load Raw Dataset with Waifuc We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code ```python import os import zipfile from huggingface_hub import hf_hub_download from waifuc.source import LocalSource # download raw archive file zip_file = hf_hub_download( repo_id='CyberHarem/hare_bluearchive', repo_type='dataset', filename='dataset-raw.zip', ) # extract files to your directory dataset_dir = 'dataset_dir' os.makedirs(dataset_dir, exist_ok=True) with zipfile.ZipFile(zip_file, 'r') as zf: zf.extractall(dataset_dir) # load the dataset with waifuc source = LocalSource(dataset_dir) for item in source: print(item.image, item.meta['filename'], item.meta['tags']) ``` ## List of Clusters List of tag clustering result, maybe some outfits can be mined here. ### Raw Text Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | 0 | 22 | ![](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, simple_background, solo, blush, looking_at_viewer, black_hoodie, hood_down, long_sleeves, white_background, closed_mouth, jacket, upper_body, open_clothes | | 1 | 5 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | 1girl, black_hoodie, holding_can, hood_down, long_sleeves, monster_energy, solo, blush, simple_background, upper_body, closed_mouth, energy_drink, looking_at_viewer, smile, blue_background, jacket, sidelocks | | 2 | 11 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | 1girl, black_scarf, hat, hooded_jacket, official_alternate_costume, simple_background, white_headwear, blush, green_jacket, open_jacket, solo, white_background, long_sleeves, looking_at_viewer, upper_body, hood_down, smile, closed_mouth | | 3 | 6 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | 1girl, black_pantyhose, black_scarf, blush, green_jacket, hat, holding_cup, long_sleeves, looking_at_viewer, official_alternate_costume, open_jacket, solo, white_headwear, hooded_jacket, sitting, smile, open_mouth, shoes | | 4 | 6 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | 1boy, 1girl, blush, hetero, nipples, penis, pussy, sex, solo_focus, mosaic_censoring, navel, spread_legs, vaginal, small_breasts, sweat, collarbone, indoors, lying, nude, open_mouth, pov, white_hair | | 5 | 5 | ![](samples/5/clu5-sample0.png) | ![](samples/5/clu5-sample1.png) | ![](samples/5/clu5-sample2.png) | ![](samples/5/clu5-sample3.png) | ![](samples/5/clu5-sample4.png) | 1girl, alternate_costume, cosplay, looking_at_viewer, midriff, millennium_cheerleader_outfit_(blue_archive), navel, pleated_skirt, solo, white_skirt, bare_shoulders, blush, holding_pom_poms, simple_background, stomach, cleavage, detached_collar, white_background, closed_mouth, medium_breasts, sidelocks, small_breasts, white_hair | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | simple_background | solo | blush | looking_at_viewer | black_hoodie | hood_down | long_sleeves | white_background | closed_mouth | jacket | upper_body | open_clothes | holding_can | monster_energy | energy_drink | smile | blue_background | sidelocks | black_scarf | hat | hooded_jacket | official_alternate_costume | white_headwear | green_jacket | open_jacket | black_pantyhose | holding_cup | sitting | open_mouth | shoes | 1boy | hetero | nipples | penis | pussy | sex | solo_focus | mosaic_censoring | navel | spread_legs | vaginal | small_breasts | sweat | collarbone | indoors | lying | nude | pov | white_hair | alternate_costume | cosplay | midriff | millennium_cheerleader_outfit_(blue_archive) | pleated_skirt | white_skirt | bare_shoulders | holding_pom_poms | stomach | cleavage | detached_collar | medium_breasts | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------------|:-------|:--------|:--------------------|:---------------|:------------|:---------------|:-------------------|:---------------|:---------|:-------------|:---------------|:--------------|:-----------------|:---------------|:--------|:------------------|:------------|:--------------|:------|:----------------|:-----------------------------|:-----------------|:---------------|:--------------|:------------------|:--------------|:----------|:-------------|:--------|:-------|:---------|:----------|:--------|:--------|:------|:-------------|:-------------------|:--------|:--------------|:----------|:----------------|:--------|:-------------|:----------|:--------|:-------|:------|:-------------|:--------------------|:----------|:----------|:-----------------------------------------------|:----------------|:--------------|:-----------------|:-------------------|:----------|:-----------|:------------------|:-----------------| | 0 | 22 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 1 | 5 | ![](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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 2 | 11 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | X | X | X | X | X | | X | X | X | X | | X | | | | | X | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 3 | 6 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | X | | X | X | X | | | X | | | | | | | | | X | | | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 4 | 6 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | X | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | 5 | 5 | ![](samples/5/clu5-sample0.png) | ![](samples/5/clu5-sample1.png) | ![](samples/5/clu5-sample2.png) | ![](samples/5/clu5-sample3.png) | ![](samples/5/clu5-sample4.png) | X | X | X | X | X | | | | X | X | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | X | | | X | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X |

vincentiussgk/pneumonia_TA_split_proper

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: file_path dtype: string - name: label dtype: string - name: image dtype: image splits: - name: train num_bytes: 339951925.0 num_examples: 900 - name: test num_bytes: 78429911.0 num_examples: 225 download_size: 417503439 dataset_size: 418381836.0 --- # Dataset Card for "pneumonia_TA_split_proper" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

EdisonBlack/lora-people

--- license: cc-by-sa-3.0 ---

Nexdata/262_People_5162_Images_Handwriting_OCR_Data_of_Traditional_Chinese_Characters_Taiwan_China

--- license: cc-by-nc-nd-4.0 --- ## Description There are 5,000 images of handwriting data of traditional Chinese characters. Texts in the data were annotated for the line-level quadrilateral bounding box. The data can be used for chinese characters recognition application For more details, please refer to the link: https://www.nexdata.ai/dataset/1190?source=Huggingface ## Data size 5,000 images ## Collecting environment including A4 paper, square paper, lined paper, etc. ## Device cellphone ## Photographic angle eye-level angle ## Data format the image data format is .jpg, the annotation file format is .json ## Annotation content line-level quadrilateral bounding box annotation and transcription for the texts ## Accuracy the error bound of each vertex of quadrilateral bounding box is within 5 pixels, which is a qualified annotation, the accuracy of bounding boxes is not less than 97%; the texts transcription accuracy is not less than 97% # Licensing Information Commercial License

open-llm-leaderboard/details_mncai__mistral-7b-dpo-v5

--- pretty_name: Evaluation run of mncai/mistral-7b-dpo-v5 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mncai/mistral-7b-dpo-v5](https://huggingface.co/mncai/mistral-7b-dpo-v5) 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_mncai__mistral-7b-dpo-v5\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-16T17:06:29.601004](https://huggingface.co/datasets/open-llm-leaderboard/details_mncai__mistral-7b-dpo-v5/blob/main/results_2023-12-16T17-06-29.601004.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\": 0.6444771644137858,\n\ \ \"acc_stderr\": 0.032189712118428256,\n \"acc_norm\": 0.6439145631454195,\n\ \ \"acc_norm_stderr\": 0.03285791543982518,\n \"mc1\": 0.5385556915544676,\n\ \ \"mc1_stderr\": 0.017451384104637452,\n \"mc2\": 0.6686090881936299,\n\ \ \"mc2_stderr\": 0.015322918299770005\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6911262798634812,\n \"acc_stderr\": 0.013501770929344,\n\ \ \"acc_norm\": 0.7201365187713311,\n \"acc_norm_stderr\": 0.01311904089772592\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6978689504082852,\n\ \ \"acc_stderr\": 0.004582433109636476,\n \"acc_norm\": 0.8757219677355108,\n\ \ \"acc_norm_stderr\": 0.003292242543637345\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.04153948404742398,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.04153948404742398\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.6907894736842105,\n \"acc_stderr\": 0.037610708698674805,\n\ \ \"acc_norm\": 0.6907894736842105,\n \"acc_norm_stderr\": 0.037610708698674805\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\": 0.6943396226415094,\n \"acc_stderr\": 0.028353298073322666,\n\ \ \"acc_norm\": 0.6943396226415094,\n \"acc_norm_stderr\": 0.028353298073322666\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7361111111111112,\n\ \ \"acc_stderr\": 0.03685651095897532,\n \"acc_norm\": 0.7361111111111112,\n\ \ \"acc_norm_stderr\": 0.03685651095897532\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\"\ : 0.55,\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\": 0.29,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6705202312138728,\n\ \ \"acc_stderr\": 0.03583901754736412,\n \"acc_norm\": 0.6705202312138728,\n\ \ \"acc_norm_stderr\": 0.03583901754736412\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.4117647058823529,\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\":\ \ 0.78,\n \"acc_stderr\": 0.04163331998932263,\n \"acc_norm\": 0.78,\n\ \ \"acc_norm_stderr\": 0.04163331998932263\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.5531914893617021,\n \"acc_stderr\": 0.0325005368436584,\n\ \ \"acc_norm\": 0.5531914893617021,\n \"acc_norm_stderr\": 0.0325005368436584\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\": 0.5724137931034483,\n \"acc_stderr\": 0.04122737111370332,\n\ \ \"acc_norm\": 0.5724137931034483,\n \"acc_norm_stderr\": 0.04122737111370332\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.42063492063492064,\n \"acc_stderr\": 0.025424835086923996,\n \"\ acc_norm\": 0.42063492063492064,\n \"acc_norm_stderr\": 0.025424835086923996\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4365079365079365,\n\ \ \"acc_stderr\": 0.04435932892851466,\n \"acc_norm\": 0.4365079365079365,\n\ \ \"acc_norm_stderr\": 0.04435932892851466\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.04725815626252604,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.04725815626252604\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7935483870967742,\n\ \ \"acc_stderr\": 0.023025899617188716,\n \"acc_norm\": 0.7935483870967742,\n\ \ \"acc_norm_stderr\": 0.023025899617188716\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\": 0.7,\n \"acc_stderr\": 0.046056618647183814,\n \"acc_norm\"\ : 0.7,\n \"acc_norm_stderr\": 0.046056618647183814\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.7696969696969697,\n \"acc_stderr\": 0.0328766675860349,\n\ \ \"acc_norm\": 0.7696969696969697,\n \"acc_norm_stderr\": 0.0328766675860349\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.7929292929292929,\n \"acc_stderr\": 0.028869778460267042,\n \"\ acc_norm\": 0.7929292929292929,\n \"acc_norm_stderr\": 0.028869778460267042\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.8808290155440415,\n \"acc_stderr\": 0.02338193534812143,\n\ \ \"acc_norm\": 0.8808290155440415,\n \"acc_norm_stderr\": 0.02338193534812143\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6487179487179487,\n \"acc_stderr\": 0.024203665177902803,\n\ \ \"acc_norm\": 0.6487179487179487,\n \"acc_norm_stderr\": 0.024203665177902803\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.3037037037037037,\n \"acc_stderr\": 0.028037929969114993,\n \ \ \"acc_norm\": 0.3037037037037037,\n \"acc_norm_stderr\": 0.028037929969114993\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.634453781512605,\n \"acc_stderr\": 0.031282177063684614,\n \ \ \"acc_norm\": 0.634453781512605,\n \"acc_norm_stderr\": 0.031282177063684614\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.31125827814569534,\n \"acc_stderr\": 0.03780445850526732,\n \"\ acc_norm\": 0.31125827814569534,\n \"acc_norm_stderr\": 0.03780445850526732\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8403669724770643,\n \"acc_stderr\": 0.015703498348461766,\n \"\ acc_norm\": 0.8403669724770643,\n \"acc_norm_stderr\": 0.015703498348461766\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.49537037037037035,\n \"acc_stderr\": 0.03409825519163572,\n \"\ acc_norm\": 0.49537037037037035,\n \"acc_norm_stderr\": 0.03409825519163572\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8088235294117647,\n \"acc_stderr\": 0.027599174300640766,\n \"\ acc_norm\": 0.8088235294117647,\n \"acc_norm_stderr\": 0.027599174300640766\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7763713080168776,\n \"acc_stderr\": 0.027123298205229962,\n \ \ \"acc_norm\": 0.7763713080168776,\n \"acc_norm_stderr\": 0.027123298205229962\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.695067264573991,\n\ \ \"acc_stderr\": 0.030898610882477515,\n \"acc_norm\": 0.695067264573991,\n\ \ \"acc_norm_stderr\": 0.030898610882477515\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.7786259541984732,\n \"acc_stderr\": 0.03641297081313729,\n\ \ \"acc_norm\": 0.7786259541984732,\n \"acc_norm_stderr\": 0.03641297081313729\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.768595041322314,\n \"acc_stderr\": 0.038498560987940904,\n \"\ acc_norm\": 0.768595041322314,\n \"acc_norm_stderr\": 0.038498560987940904\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7592592592592593,\n\ \ \"acc_stderr\": 0.04133119440243839,\n \"acc_norm\": 0.7592592592592593,\n\ \ \"acc_norm_stderr\": 0.04133119440243839\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\": 0.4642857142857143,\n\ \ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.4642857142857143,\n\ \ \"acc_norm_stderr\": 0.04733667890053756\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7864077669902912,\n \"acc_stderr\": 0.040580420156460344,\n\ \ \"acc_norm\": 0.7864077669902912,\n \"acc_norm_stderr\": 0.040580420156460344\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8846153846153846,\n\ \ \"acc_stderr\": 0.020930193185179326,\n \"acc_norm\": 0.8846153846153846,\n\ \ \"acc_norm_stderr\": 0.020930193185179326\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.68,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.68,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8301404853128991,\n\ \ \"acc_stderr\": 0.013428186370608311,\n \"acc_norm\": 0.8301404853128991,\n\ \ \"acc_norm_stderr\": 0.013428186370608311\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7398843930635838,\n \"acc_stderr\": 0.023618678310069356,\n\ \ \"acc_norm\": 0.7398843930635838,\n \"acc_norm_stderr\": 0.023618678310069356\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.4480446927374302,\n\ \ \"acc_stderr\": 0.016631976628930595,\n \"acc_norm\": 0.4480446927374302,\n\ \ \"acc_norm_stderr\": 0.016631976628930595\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7189542483660131,\n \"acc_stderr\": 0.025738854797818737,\n\ \ \"acc_norm\": 0.7189542483660131,\n \"acc_norm_stderr\": 0.025738854797818737\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7138263665594855,\n\ \ \"acc_stderr\": 0.025670259242188933,\n \"acc_norm\": 0.7138263665594855,\n\ \ \"acc_norm_stderr\": 0.025670259242188933\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.75,\n \"acc_stderr\": 0.02409347123262133,\n \ \ \"acc_norm\": 0.75,\n \"acc_norm_stderr\": 0.02409347123262133\n \ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"acc\"\ : 0.4858156028368794,\n \"acc_stderr\": 0.02981549448368206,\n \"\ acc_norm\": 0.4858156028368794,\n \"acc_norm_stderr\": 0.02981549448368206\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.46479791395045633,\n\ \ \"acc_stderr\": 0.012738547371303957,\n \"acc_norm\": 0.46479791395045633,\n\ \ \"acc_norm_stderr\": 0.012738547371303957\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.6544117647058824,\n \"acc_stderr\": 0.02888819310398863,\n\ \ \"acc_norm\": 0.6544117647058824,\n \"acc_norm_stderr\": 0.02888819310398863\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.6617647058823529,\n \"acc_stderr\": 0.01913994374848704,\n \ \ \"acc_norm\": 0.6617647058823529,\n \"acc_norm_stderr\": 0.01913994374848704\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6545454545454545,\n\ \ \"acc_stderr\": 0.04554619617541054,\n \"acc_norm\": 0.6545454545454545,\n\ \ \"acc_norm_stderr\": 0.04554619617541054\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7183673469387755,\n \"acc_stderr\": 0.028795185574291293,\n\ \ \"acc_norm\": 0.7183673469387755,\n \"acc_norm_stderr\": 0.028795185574291293\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8407960199004975,\n\ \ \"acc_stderr\": 0.025870646766169146,\n \"acc_norm\": 0.8407960199004975,\n\ \ \"acc_norm_stderr\": 0.025870646766169146\n },\n \"harness|hendrycksTest-us_foreign_policy|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-virology|5\": {\n \"acc\": 0.5481927710843374,\n\ \ \"acc_stderr\": 0.03874371556587953,\n \"acc_norm\": 0.5481927710843374,\n\ \ \"acc_norm_stderr\": 0.03874371556587953\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8245614035087719,\n \"acc_stderr\": 0.029170885500727665,\n\ \ \"acc_norm\": 0.8245614035087719,\n \"acc_norm_stderr\": 0.029170885500727665\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.5385556915544676,\n\ \ \"mc1_stderr\": 0.017451384104637452,\n \"mc2\": 0.6686090881936299,\n\ \ \"mc2_stderr\": 0.015322918299770005\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.8224151539068666,\n \"acc_stderr\": 0.010740676861359237\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.7065959059893859,\n \ \ \"acc_stderr\": 0.012541830815461487\n }\n}\n```" repo_url: https://huggingface.co/mncai/mistral-7b-dpo-v5 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_16T17_06_29.601004 path: - '**/details_harness|arc:challenge|25_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-16T17-06-29.601004.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|gsm8k|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hellaswag|10_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-16T17-06-29.601004.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-management|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-16T17-06-29.601004.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|truthfulqa:mc|0_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-16T17-06-29.601004.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_16T17_06_29.601004 path: - '**/details_harness|winogrande|5_2023-12-16T17-06-29.601004.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-16T17-06-29.601004.parquet' - config_name: results data_files: - split: 2023_12_16T17_06_29.601004 path: - results_2023-12-16T17-06-29.601004.parquet - split: latest path: - results_2023-12-16T17-06-29.601004.parquet --- # Dataset Card for Evaluation run of mncai/mistral-7b-dpo-v5  Dataset automatically created during the evaluation run of model [mncai/mistral-7b-dpo-v5](https://huggingface.co/mncai/mistral-7b-dpo-v5) 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_mncai__mistral-7b-dpo-v5", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-16T17:06:29.601004](https://huggingface.co/datasets/open-llm-leaderboard/details_mncai__mistral-7b-dpo-v5/blob/main/results_2023-12-16T17-06-29.601004.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": 0.6444771644137858, "acc_stderr": 0.032189712118428256, "acc_norm": 0.6439145631454195, "acc_norm_stderr": 0.03285791543982518, "mc1": 0.5385556915544676, "mc1_stderr": 0.017451384104637452, "mc2": 0.6686090881936299, "mc2_stderr": 0.015322918299770005 }, "harness|arc:challenge|25": { "acc": 0.6911262798634812, "acc_stderr": 0.013501770929344, "acc_norm": 0.7201365187713311, "acc_norm_stderr": 0.01311904089772592 }, "harness|hellaswag|10": { "acc": 0.6978689504082852, "acc_stderr": 0.004582433109636476, "acc_norm": 0.8757219677355108, "acc_norm_stderr": 0.003292242543637345 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6370370370370371, "acc_stderr": 0.04153948404742398, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.04153948404742398 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6907894736842105, "acc_stderr": 0.037610708698674805, "acc_norm": 0.6907894736842105, "acc_norm_stderr": 0.037610708698674805 }, "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": 0.6943396226415094, "acc_stderr": 0.028353298073322666, "acc_norm": 0.6943396226415094, "acc_norm_stderr": 0.028353298073322666 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7361111111111112, "acc_stderr": 0.03685651095897532, "acc_norm": 0.7361111111111112, "acc_norm_stderr": 0.03685651095897532 }, "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": 0.55, "acc_stderr": 0.05, "acc_norm": 0.55, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.29, "acc_stderr": 0.04560480215720684, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736412, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736412 }, "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": 0.78, "acc_stderr": 0.04163331998932263, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932263 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5531914893617021, "acc_stderr": 0.0325005368436584, "acc_norm": 0.5531914893617021, "acc_norm_stderr": 0.0325005368436584 }, "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": 0.5724137931034483, "acc_stderr": 0.04122737111370332, "acc_norm": 0.5724137931034483, "acc_norm_stderr": 0.04122737111370332 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.42063492063492064, "acc_stderr": 0.025424835086923996, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.025424835086923996 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4365079365079365, "acc_stderr": 0.04435932892851466, "acc_norm": 0.4365079365079365, "acc_norm_stderr": 0.04435932892851466 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7935483870967742, "acc_stderr": 0.023025899617188716, "acc_norm": 0.7935483870967742, "acc_norm_stderr": 0.023025899617188716 }, "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": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "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": 0.7929292929292929, "acc_stderr": 0.028869778460267042, "acc_norm": 0.7929292929292929, "acc_norm_stderr": 0.028869778460267042 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8808290155440415, "acc_stderr": 0.02338193534812143, "acc_norm": 0.8808290155440415, "acc_norm_stderr": 0.02338193534812143 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6487179487179487, "acc_stderr": 0.024203665177902803, "acc_norm": 0.6487179487179487, "acc_norm_stderr": 0.024203665177902803 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3037037037037037, "acc_stderr": 0.028037929969114993, "acc_norm": 0.3037037037037037, "acc_norm_stderr": 0.028037929969114993 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.634453781512605, "acc_stderr": 0.031282177063684614, "acc_norm": 0.634453781512605, "acc_norm_stderr": 0.031282177063684614 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.31125827814569534, "acc_stderr": 0.03780445850526732, "acc_norm": 0.31125827814569534, "acc_norm_stderr": 0.03780445850526732 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8403669724770643, "acc_stderr": 0.015703498348461766, "acc_norm": 0.8403669724770643, "acc_norm_stderr": 0.015703498348461766 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.49537037037037035, "acc_stderr": 0.03409825519163572, "acc_norm": 0.49537037037037035, "acc_norm_stderr": 0.03409825519163572 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8088235294117647, "acc_stderr": 0.027599174300640766, "acc_norm": 0.8088235294117647, "acc_norm_stderr": 0.027599174300640766 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7763713080168776, "acc_stderr": 0.027123298205229962, "acc_norm": 0.7763713080168776, "acc_norm_stderr": 0.027123298205229962 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.695067264573991, "acc_stderr": 0.030898610882477515, "acc_norm": 0.695067264573991, "acc_norm_stderr": 0.030898610882477515 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.7786259541984732, "acc_stderr": 0.03641297081313729, "acc_norm": 0.7786259541984732, "acc_norm_stderr": 0.03641297081313729 }, "harness|hendrycksTest-international_law|5": { "acc": 0.768595041322314, "acc_stderr": 0.038498560987940904, "acc_norm": 0.768595041322314, "acc_norm_stderr": 0.038498560987940904 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.7592592592592593, "acc_stderr": 0.04133119440243839, "acc_norm": 0.7592592592592593, "acc_norm_stderr": 0.04133119440243839 }, "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": 0.4642857142857143, "acc_stderr": 0.04733667890053756, "acc_norm": 0.4642857142857143, "acc_norm_stderr": 0.04733667890053756 }, "harness|hendrycksTest-management|5": { "acc": 0.7864077669902912, "acc_stderr": 0.040580420156460344, "acc_norm": 0.7864077669902912, "acc_norm_stderr": 0.040580420156460344 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8846153846153846, "acc_stderr": 0.020930193185179326, "acc_norm": 0.8846153846153846, "acc_norm_stderr": 0.020930193185179326 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.68, "acc_stderr": 0.046882617226215034, "acc_norm": 0.68, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8301404853128991, "acc_stderr": 0.013428186370608311, "acc_norm": 0.8301404853128991, "acc_norm_stderr": 0.013428186370608311 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7398843930635838, "acc_stderr": 0.023618678310069356, "acc_norm": 0.7398843930635838, "acc_norm_stderr": 0.023618678310069356 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.4480446927374302, "acc_stderr": 0.016631976628930595, "acc_norm": 0.4480446927374302, "acc_norm_stderr": 0.016631976628930595 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7189542483660131, "acc_stderr": 0.025738854797818737, "acc_norm": 0.7189542483660131, "acc_norm_stderr": 0.025738854797818737 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7138263665594855, "acc_stderr": 0.025670259242188933, "acc_norm": 0.7138263665594855, "acc_norm_stderr": 0.025670259242188933 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.75, "acc_stderr": 0.02409347123262133, "acc_norm": 0.75, "acc_norm_stderr": 0.02409347123262133 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.4858156028368794, "acc_stderr": 0.02981549448368206, "acc_norm": 0.4858156028368794, "acc_norm_stderr": 0.02981549448368206 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.46479791395045633, "acc_stderr": 0.012738547371303957, "acc_norm": 0.46479791395045633, "acc_norm_stderr": 0.012738547371303957 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.6544117647058824, "acc_stderr": 0.02888819310398863, "acc_norm": 0.6544117647058824, "acc_norm_stderr": 0.02888819310398863 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.6617647058823529, "acc_stderr": 0.01913994374848704, "acc_norm": 0.6617647058823529, "acc_norm_stderr": 0.01913994374848704 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6545454545454545, "acc_stderr": 0.04554619617541054, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.04554619617541054 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7183673469387755, "acc_stderr": 0.028795185574291293, "acc_norm": 0.7183673469387755, "acc_norm_stderr": 0.028795185574291293 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8407960199004975, "acc_stderr": 0.025870646766169146, "acc_norm": 0.8407960199004975, "acc_norm_stderr": 0.025870646766169146 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.89, "acc_stderr": 0.03144660377352202, "acc_norm": 0.89, "acc_norm_stderr": 0.03144660377352202 }, "harness|hendrycksTest-virology|5": { "acc": 0.5481927710843374, "acc_stderr": 0.03874371556587953, "acc_norm": 0.5481927710843374, "acc_norm_stderr": 0.03874371556587953 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8245614035087719, "acc_stderr": 0.029170885500727665, "acc_norm": 0.8245614035087719, "acc_norm_stderr": 0.029170885500727665 }, "harness|truthfulqa:mc|0": { "mc1": 0.5385556915544676, "mc1_stderr": 0.017451384104637452, "mc2": 0.6686090881936299, "mc2_stderr": 0.015322918299770005 }, "harness|winogrande|5": { "acc": 0.8224151539068666, "acc_stderr": 0.010740676861359237 }, "harness|gsm8k|5": { "acc": 0.7065959059893859, "acc_stderr": 0.012541830815461487 } } ``` ## Dataset Details ### Dataset Description  - **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]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

CognitiveLab/hh-rlhf-formatted-10000

--- dataset_info: features: - name: prompt dtype: string - name: chosen dtype: string - name: rejected dtype: string splits: - name: train num_bytes: 14489586 num_examples: 10000 download_size: 7538920 dataset_size: 14489586 configs: - config_name: default data_files: - split: train path: data/train-* ---

nanaaaa/emotion_chinese_english

--- task_categories: - text-classification language: - zh - en ---

bongsoo/kowiki20220620

--- language: - ko license: apache-2.0 --- -kowiki202206 1줄 말뭉치

pszemraj/text2image-multi-prompt

--- language: - en license: apache-2.0 multilinguality: - monolingual source_datasets: - bartman081523/stable-diffusion-discord-prompts - succinctly/midjourney-prompts - Gustavosta/Stable-Diffusion-Prompts pretty_name: multi text2image prompts a dataset collection tags: - text generation configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - config_name: original data_files: - split: train path: original/train-* - split: test path: original/test-* dataset_info: - config_name: default features: - name: text dtype: string - name: src_dataset dtype: string splits: - name: train num_bytes: 262736830 num_examples: 1677221 - name: test num_bytes: 56294291 num_examples: 292876 download_size: 151054782 dataset_size: 319031121 - config_name: original features: - name: text dtype: string - name: src_dataset dtype: string splits: - name: train num_bytes: 741427383 num_examples: 3551734 - name: test num_bytes: 83615440 num_examples: 399393 download_size: 402186258 dataset_size: 825042823 task_categories: - text-generation - feature-extraction --- # text2image multi-prompt(s): a dataset collection - collection of several text2image prompt datasets - data was cleaned/normalized with the goal of removing "model specific APIs" like the "--ar" for Midjourney and so on - data de-duplicated on a basic level: exactly duplicate prompts were dropped (_after cleaning and normalization_) ## updates - Oct 2023: the `default` config has been updated with better deduplication. It was deduplicated with minhash (_params: n-gram size set to 3, deduplication threshold at 0.6, hash function chosen as xxh3 with 32-bit hash bits, and 128 permutations with a batch size of 10,000._) which drops 2+ million rows. - original version is still available under `config_name="original"` ## contents default: ``` DatasetDict({ train: Dataset({ features: ['text', 'src_dataset'], num_rows: 1677221 }) test: Dataset({ features: ['text', 'src_dataset'], num_rows: 292876 }) }) ``` For `original` config: ``` DatasetDict({ train: Dataset({ features: ['text', 'src_dataset'], num_rows: 3551734 }) test: Dataset({ features: ['text', 'src_dataset'], num_rows: 399393 }) }) ``` _NOTE: as the other two datasets did not have a `validation` split, the validation split of `succinctly/midjourney-prompts` was merged into `train`._

joey234/mmlu-high_school_biology-dev

--- dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: negate_openai_prompt struct: - name: content dtype: string - name: role dtype: string splits: - name: dev num_bytes: 3234 num_examples: 5 download_size: 0 dataset_size: 3234 --- # Dataset Card for "mmlu-high_school_biology-dev" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

NLPC-UOM/nllb-top25k-ensi-cleaned

--- license: odc-by task_categories: - translation language: - en - si size_categories: - 10K<n<100K --- ### Licensing Information The dataset is released under the terms of [ODC-BY](https://opendatacommons.org/licenses/by/1-0/). By using this, you are also bound to the respective Terms of Use and License of the original source. ### Citation Information Schwenk et al, CCMatrix: Mining Billions of High-Quality Parallel Sentences on the Web. ACL https://aclanthology.org/2021.acl-long.507/ Hefferman et al, Bitext Mining Using Distilled Sentence Representations for Low-Resource Languages. Arxiv https://arxiv.org/abs/2205.12654, 2022.<br> NLLB Team et al, No Language Left Behind: Scaling Human-Centered Machine Translation, Arxiv https://arxiv.org/abs/2207.04672, 2022. ### Contributions We thank the NLLB Meta AI team for open sourcing the meta data and instructions on how to use it with special thanks to Bapi Akula, Pierre Andrews, Onur Çelebi, Sergey Edunov, Kenneth Heafield, Philipp Koehn, Alex Mourachko, Safiyyah Saleem, Holger Schwenk, and Guillaume Wenzek. We also thank the AllenNLP team at AI2 for hosting and releasing this data, including Akshita Bhagia (for engineering efforts to host the data, and create the huggingface dataset), and Jesse Dodge (for organizing the connection).

maghwa/OpenHermes-2-AR-10K-7

--- dataset_info: features: - name: custom_instruction dtype: 'null' - name: system_prompt dtype: 'null' - name: avatarUrl dtype: 'null' - name: conversations dtype: string - name: topic dtype: 'null' - name: views dtype: float64 - name: model dtype: 'null' - name: id dtype: string - name: hash dtype: 'null' - name: title dtype: 'null' - name: model_name dtype: 'null' - name: idx dtype: 'null' - name: skip_prompt_formatting dtype: 'null' - name: category dtype: 'null' - name: source dtype: string - name: language dtype: 'null' splits: - name: train num_bytes: 25327870 num_examples: 10001 download_size: 9643427 dataset_size: 25327870 configs: - config_name: default data_files: - split: train path: data/train-* ---

tyzhu/lmind_hotpot_train1000_eval500_v1_recite_qa

--- configs: - config_name: default data_files: - split: train_qa path: data/train_qa-* - split: train_recite_qa path: data/train_recite_qa-* - split: eval_qa path: data/eval_qa-* - split: eval_recite_qa path: data/eval_recite_qa-* - split: all_docs path: data/all_docs-* - split: all_docs_eval path: data/all_docs_eval-* - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: inputs dtype: string - name: targets dtype: string - name: answers struct: - name: answer_start sequence: 'null' - name: text sequence: string splits: - name: train_qa num_bytes: 173266 num_examples: 1000 - name: train_recite_qa num_bytes: 1052784 num_examples: 1000 - name: eval_qa num_bytes: 81677 num_examples: 500 - name: eval_recite_qa num_bytes: 542914 num_examples: 500 - name: all_docs num_bytes: 1370698 num_examples: 2959 - name: all_docs_eval num_bytes: 1370509 num_examples: 2959 - name: train num_bytes: 2423482 num_examples: 3959 - name: validation num_bytes: 542914 num_examples: 500 download_size: 4626743 dataset_size: 7558244 --- # Dataset Card for "lmind_hotpot_train1000_eval500_v1_recite_qa" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

giuseppemartino/isaid_sam_predicted

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* dataset_info: features: - name: image dtype: image - name: label dtype: image splits: - name: train num_bytes: 6757890501.0 num_examples: 899 - name: validation num_bytes: 152972321.0 num_examples: 17 download_size: 152947587 dataset_size: 6910862822.0 --- # Dataset Card for "isaid_sam_predicted" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

baylitoo/alpacaa

--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string - name: text dtype: string splits: - name: train num_bytes: 888593.1887235106 num_examples: 1000 download_size: 0 dataset_size: 888593.1887235106 --- # Dataset Card for "alpacaa" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

open-llm-leaderboard/details_FelixChao__llama2-13b-math1.2

--- pretty_name: Evaluation run of FelixChao/llama2-13b-math1.2 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [FelixChao/llama2-13b-math1.2](https://huggingface.co/FelixChao/llama2-13b-math1.2)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 64 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 3 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_FelixChao__llama2-13b-math1.2\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-10-17T02:02:50.506714](https://huggingface.co/datasets/open-llm-leaderboard/details_FelixChao__llama2-13b-math1.2/blob/main/results_2023-10-17T02-02-50.506714.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\": 0.08536073825503356,\n\ \ \"em_stderr\": 0.002861499356149465,\n \"f1\": 0.16235318791946293,\n\ \ \"f1_stderr\": 0.003133455634092774,\n \"acc\": 0.4263155280751903,\n\ \ \"acc_stderr\": 0.010451092603365564\n },\n \"harness|drop|3\": {\n\ \ \"em\": 0.08536073825503356,\n \"em_stderr\": 0.002861499356149465,\n\ \ \"f1\": 0.16235318791946293,\n \"f1_stderr\": 0.003133455634092774\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.10993176648976498,\n \ \ \"acc_stderr\": 0.008616195587865416\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.7426992896606156,\n \"acc_stderr\": 0.012285989618865713\n\ \ }\n}\n```" repo_url: https://huggingface.co/FelixChao/llama2-13b-math1.2 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|arc:challenge|25_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-08-18T11:24:31.239858.parquet' - config_name: harness_drop_3 data_files: - split: 2023_10_16T16_38_50.665467 path: - '**/details_harness|drop|3_2023-10-16T16-38-50.665467.parquet' - split: 2023_10_17T02_02_50.506714 path: - '**/details_harness|drop|3_2023-10-17T02-02-50.506714.parquet' - split: latest path: - '**/details_harness|drop|3_2023-10-17T02-02-50.506714.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_10_16T16_38_50.665467 path: - '**/details_harness|gsm8k|5_2023-10-16T16-38-50.665467.parquet' - split: 2023_10_17T02_02_50.506714 path: - '**/details_harness|gsm8k|5_2023-10-17T02-02-50.506714.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-10-17T02-02-50.506714.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hellaswag|10_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-management|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-08-18T11:24:31.239858.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-management|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-virology|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-08-18T11:24:31.239858.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_08_18T11_24_31.239858 path: - '**/details_harness|truthfulqa:mc|0_2023-08-18T11:24:31.239858.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-08-18T11:24:31.239858.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_10_16T16_38_50.665467 path: - '**/details_harness|winogrande|5_2023-10-16T16-38-50.665467.parquet' - split: 2023_10_17T02_02_50.506714 path: - '**/details_harness|winogrande|5_2023-10-17T02-02-50.506714.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-10-17T02-02-50.506714.parquet' - config_name: results data_files: - split: 2023_08_18T11_24_31.239858 path: - results_2023-08-18T11:24:31.239858.parquet - split: 2023_10_16T16_38_50.665467 path: - results_2023-10-16T16-38-50.665467.parquet - split: 2023_10_17T02_02_50.506714 path: - results_2023-10-17T02-02-50.506714.parquet - split: latest path: - results_2023-10-17T02-02-50.506714.parquet --- # Dataset Card for Evaluation run of FelixChao/llama2-13b-math1.2 ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/FelixChao/llama2-13b-math1.2 - **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 [FelixChao/llama2-13b-math1.2](https://huggingface.co/FelixChao/llama2-13b-math1.2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 3 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_FelixChao__llama2-13b-math1.2", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-10-17T02:02:50.506714](https://huggingface.co/datasets/open-llm-leaderboard/details_FelixChao__llama2-13b-math1.2/blob/main/results_2023-10-17T02-02-50.506714.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": 0.08536073825503356, "em_stderr": 0.002861499356149465, "f1": 0.16235318791946293, "f1_stderr": 0.003133455634092774, "acc": 0.4263155280751903, "acc_stderr": 0.010451092603365564 }, "harness|drop|3": { "em": 0.08536073825503356, "em_stderr": 0.002861499356149465, "f1": 0.16235318791946293, "f1_stderr": 0.003133455634092774 }, "harness|gsm8k|5": { "acc": 0.10993176648976498, "acc_stderr": 0.008616195587865416 }, "harness|winogrande|5": { "acc": 0.7426992896606156, "acc_stderr": 0.012285989618865713 } } ``` ### 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]

chathuranga-jayanath/context-5-finmath-times4j-html-mavendoxia-wro4j-guava-supercsv-len-1000-prompt-2

--- dataset_info: features: - name: id dtype: int64 - name: filepath dtype: string - name: start_bug_line dtype: int64 - name: end_bug_line dtype: int64 - name: bug dtype: string - name: fix dtype: string - name: ctx dtype: string splits: - name: train num_bytes: 5510268 num_examples: 5105 - name: validation num_bytes: 672859 num_examples: 637 - name: test num_bytes: 672684 num_examples: 637 download_size: 2623280 dataset_size: 6855811 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---

vinny9812/audiobrunogiglio

--- license: openrail ---

TwoAbove/gpt4v-emotion-dataset

--- dataset_info: features: - name: caption dtype: string - name: image dtype: image - name: link dtype: string - name: message_id dtype: string - name: timestamp dtype: string splits: - name: train num_bytes: 51420737.0 num_examples: 48 download_size: 51389687 dataset_size: 51420737.0 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "gpt4v-emotion-dataset" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

tnet-devs/demo_inc

--- license: cc-by-nc-nd-4.0 ---

ID3/comentarios_youtube_validos_similitud

--- dataset_info: features: - name: comentario dtype: string - name: likes dtype: int64 - name: similitud dtype: float64 - name: id dtype: string splits: - name: train num_bytes: 83527097 num_examples: 652388 download_size: 54010613 dataset_size: 83527097 --- # Dataset Card for "comentarios_youtube_validos_similitud" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

lilacai/lilac-OpenOrca

--- tags: - Lilac --- # lilac/OpenOrca This dataset is a [Lilac](http://lilacml.com) processed dataset. Original dataset: [https://huggingface.co/datasets/Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca) To download the dataset to a local directory: ```bash lilac download lilacai/lilac-OpenOrca ``` or from python with: ```py ll.download("lilacai/lilac-OpenOrca") ```

CyberHarem/noah_nikke

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of noah/ノア/诺雅/노아 (Nikke: Goddess of Victory) This is the dataset of noah/ノア/诺雅/노아 (Nikke: Goddess of Victory), containing 23 images and their tags. The core tags of this character are `pink_hair, short_hair, pink_eyes, hair_ornament, bangs, breasts`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages | Name | Images | Size | Download | Type | Description | |:-----------------|---------:|:----------|:------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------| | raw | 23 | 29.38 MiB | [Download](https://huggingface.co/datasets/CyberHarem/noah_nikke/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 23 | 13.94 MiB | [Download](https://huggingface.co/datasets/CyberHarem/noah_nikke/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 64 | 36.91 MiB | [Download](https://huggingface.co/datasets/CyberHarem/noah_nikke/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 23 | 24.46 MiB | [Download](https://huggingface.co/datasets/CyberHarem/noah_nikke/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 64 | 55.19 MiB | [Download](https://huggingface.co/datasets/CyberHarem/noah_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/noah_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 | 23 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | 1girl, looking_at_viewer, solo, smile, open_mouth, blush, armor, white_background, bodysuit, fingerless_gloves, simple_background | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | looking_at_viewer | solo | smile | open_mouth | blush | armor | white_background | bodysuit | fingerless_gloves | simple_background | |----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------------|:-------|:--------|:-------------|:--------|:--------|:-------------------|:-----------|:--------------------|:--------------------| | 0 | 23 | ![](samples/0/clu0-sample0.png) | ![](samples/0/clu0-sample1.png) | ![](samples/0/clu0-sample2.png) | ![](samples/0/clu0-sample3.png) | ![](samples/0/clu0-sample4.png) | X | X | X | X | X | X | X | X | X | X | X |

KaiLv/UDR_Go

--- dataset_info: features: - name: idx dtype: int64 - name: question dtype: string - name: target dtype: string - name: len_question dtype: int64 - name: len_target dtype: int64 splits: - name: train num_bytes: 89583705 num_examples: 167137 - name: validation num_bytes: 3547138 num_examples: 7320 - name: test num_bytes: 4244257 num_examples: 8115 - name: debug num_bytes: 53690904 num_examples: 100000 download_size: 66725224 dataset_size: 151066004 --- # Dataset Card for "UDR_Go_new" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Ilia-Iliev/example_captioner

--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 2788504.0 num_examples: 15 - name: validation num_bytes: 914115.0 num_examples: 5 download_size: 3693983 dataset_size: 3702619.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

open-llm-leaderboard/details_mwitiderrick__open_llama_3b_glaive_v0.1

--- pretty_name: Evaluation run of mwitiderrick/open_llama_3b_glaive_v0.1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [mwitiderrick/open_llama_3b_glaive_v0.1](https://huggingface.co/mwitiderrick/open_llama_3b_glaive_v0.1)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 63 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the aggregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_mwitiderrick__open_llama_3b_glaive_v0.1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2023-12-23T15:34:19.150703](https://huggingface.co/datasets/open-llm-leaderboard/details_mwitiderrick__open_llama_3b_glaive_v0.1/blob/main/results_2023-12-23T15-34-19.150703.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\": 0.2843747535406573,\n\ \ \"acc_stderr\": 0.031689110133124844,\n \"acc_norm\": 0.28633888958645765,\n\ \ \"acc_norm_stderr\": 0.03246963675970039,\n \"mc1\": 0.23623011015911874,\n\ \ \"mc1_stderr\": 0.014869755015871114,\n \"mc2\": 0.3585983664640556,\n\ \ \"mc2_stderr\": 0.013742745779138914\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.3703071672354949,\n \"acc_stderr\": 0.01411129875167495,\n\ \ \"acc_norm\": 0.4069965870307167,\n \"acc_norm_stderr\": 0.014356399418009131\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.4971121290579566,\n\ \ \"acc_stderr\": 0.004989698183207831,\n \"acc_norm\": 0.6744672376020713,\n\ \ \"acc_norm_stderr\": 0.004676159299105414\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \ \ \"acc_norm\": 0.33,\n \"acc_norm_stderr\": 0.047258156262526045\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.2814814814814815,\n\ \ \"acc_stderr\": 0.03885004245800254,\n \"acc_norm\": 0.2814814814814815,\n\ \ \"acc_norm_stderr\": 0.03885004245800254\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.21052631578947367,\n \"acc_stderr\": 0.03317672787533157,\n\ \ \"acc_norm\": 0.21052631578947367,\n \"acc_norm_stderr\": 0.03317672787533157\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.27,\n\ \ \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\": 0.27,\n \ \ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.29056603773584905,\n \"acc_stderr\": 0.027943219989337156,\n\ \ \"acc_norm\": 0.29056603773584905,\n \"acc_norm_stderr\": 0.027943219989337156\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.2638888888888889,\n\ \ \"acc_stderr\": 0.03685651095897532,\n \"acc_norm\": 0.2638888888888889,\n\ \ \"acc_norm_stderr\": 0.03685651095897532\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816505,\n \ \ \"acc_norm\": 0.23,\n \"acc_norm_stderr\": 0.04229525846816505\n \ \ },\n \"harness|hendrycksTest-college_computer_science|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_mathematics|5\"\ : {\n \"acc\": 0.26,\n \"acc_stderr\": 0.044084400227680794,\n \ \ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.044084400227680794\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.3236994219653179,\n\ \ \"acc_stderr\": 0.035676037996391685,\n \"acc_norm\": 0.3236994219653179,\n\ \ \"acc_norm_stderr\": 0.035676037996391685\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.20588235294117646,\n \"acc_stderr\": 0.04023382273617749,\n\ \ \"acc_norm\": 0.20588235294117646,\n \"acc_norm_stderr\": 0.04023382273617749\n\ \ },\n \"harness|hendrycksTest-computer_security|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-conceptual_physics|5\"\ : {\n \"acc\": 0.3148936170212766,\n \"acc_stderr\": 0.030363582197238167,\n\ \ \"acc_norm\": 0.3148936170212766,\n \"acc_norm_stderr\": 0.030363582197238167\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.3333333333333333,\n\ \ \"acc_stderr\": 0.044346007015849245,\n \"acc_norm\": 0.3333333333333333,\n\ \ \"acc_norm_stderr\": 0.044346007015849245\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.27586206896551724,\n \"acc_stderr\": 0.037245636197746325,\n\ \ \"acc_norm\": 0.27586206896551724,\n \"acc_norm_stderr\": 0.037245636197746325\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.25396825396825395,\n \"acc_stderr\": 0.022418042891113932,\n \"\ acc_norm\": 0.25396825396825395,\n \"acc_norm_stderr\": 0.022418042891113932\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.20634920634920634,\n\ \ \"acc_stderr\": 0.03619604524124252,\n \"acc_norm\": 0.20634920634920634,\n\ \ \"acc_norm_stderr\": 0.03619604524124252\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\": 0.2645161290322581,\n\ \ \"acc_stderr\": 0.02509189237885928,\n \"acc_norm\": 0.2645161290322581,\n\ \ \"acc_norm_stderr\": 0.02509189237885928\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.30049261083743845,\n \"acc_stderr\": 0.03225799476233484,\n\ \ \"acc_norm\": 0.30049261083743845,\n \"acc_norm_stderr\": 0.03225799476233484\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.15,\n \"acc_stderr\": 0.035887028128263714,\n \"acc_norm\"\ : 0.15,\n \"acc_norm_stderr\": 0.035887028128263714\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.26666666666666666,\n \"acc_stderr\": 0.034531318018854146,\n\ \ \"acc_norm\": 0.26666666666666666,\n \"acc_norm_stderr\": 0.034531318018854146\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.31313131313131315,\n \"acc_stderr\": 0.03304205087813653,\n \"\ acc_norm\": 0.31313131313131315,\n \"acc_norm_stderr\": 0.03304205087813653\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.27461139896373055,\n \"acc_stderr\": 0.03221024508041154,\n\ \ \"acc_norm\": 0.27461139896373055,\n \"acc_norm_stderr\": 0.03221024508041154\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.32564102564102565,\n \"acc_stderr\": 0.02375966576741229,\n\ \ \"acc_norm\": 0.32564102564102565,\n \"acc_norm_stderr\": 0.02375966576741229\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.2518518518518518,\n \"acc_stderr\": 0.02646611753895991,\n \ \ \"acc_norm\": 0.2518518518518518,\n \"acc_norm_stderr\": 0.02646611753895991\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.2773109243697479,\n \"acc_stderr\": 0.029079374539480007,\n\ \ \"acc_norm\": 0.2773109243697479,\n \"acc_norm_stderr\": 0.029079374539480007\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.26490066225165565,\n \"acc_stderr\": 0.03603038545360383,\n \"\ acc_norm\": 0.26490066225165565,\n \"acc_norm_stderr\": 0.03603038545360383\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.27339449541284405,\n \"acc_stderr\": 0.019109299846098275,\n \"\ acc_norm\": 0.27339449541284405,\n \"acc_norm_stderr\": 0.019109299846098275\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\": 0.24019607843137256,\n\ \ \"acc_stderr\": 0.02998373305591361,\n \"acc_norm\": 0.24019607843137256,\n\ \ \"acc_norm_stderr\": 0.02998373305591361\n },\n \"harness|hendrycksTest-high_school_world_history|5\"\ : {\n \"acc\": 0.25316455696202533,\n \"acc_stderr\": 0.028304657943035303,\n\ \ \"acc_norm\": 0.25316455696202533,\n \"acc_norm_stderr\": 0.028304657943035303\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.3452914798206278,\n\ \ \"acc_stderr\": 0.03191100192835794,\n \"acc_norm\": 0.3452914798206278,\n\ \ \"acc_norm_stderr\": 0.03191100192835794\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.22137404580152673,\n \"acc_stderr\": 0.03641297081313728,\n\ \ \"acc_norm\": 0.22137404580152673,\n \"acc_norm_stderr\": 0.03641297081313728\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.2975206611570248,\n \"acc_stderr\": 0.041733491480834974,\n \"\ acc_norm\": 0.2975206611570248,\n \"acc_norm_stderr\": 0.041733491480834974\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.28703703703703703,\n\ \ \"acc_stderr\": 0.043733130409147614,\n \"acc_norm\": 0.28703703703703703,\n\ \ \"acc_norm_stderr\": 0.043733130409147614\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.26993865030674846,\n \"acc_stderr\": 0.034878251684978906,\n\ \ \"acc_norm\": 0.26993865030674846,\n \"acc_norm_stderr\": 0.034878251684978906\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.26785714285714285,\n\ \ \"acc_stderr\": 0.04203277291467764,\n \"acc_norm\": 0.26785714285714285,\n\ \ \"acc_norm_stderr\": 0.04203277291467764\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.2524271844660194,\n \"acc_stderr\": 0.04301250399690877,\n\ \ \"acc_norm\": 0.2524271844660194,\n \"acc_norm_stderr\": 0.04301250399690877\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.2692307692307692,\n\ \ \"acc_stderr\": 0.02905858830374884,\n \"acc_norm\": 0.2692307692307692,\n\ \ \"acc_norm_stderr\": 0.02905858830374884\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.28991060025542786,\n\ \ \"acc_stderr\": 0.016225017944770957,\n \"acc_norm\": 0.28991060025542786,\n\ \ \"acc_norm_stderr\": 0.016225017944770957\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.25722543352601157,\n \"acc_stderr\": 0.02353292543104428,\n\ \ \"acc_norm\": 0.25722543352601157,\n \"acc_norm_stderr\": 0.02353292543104428\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.24692737430167597,\n\ \ \"acc_stderr\": 0.014422292204808835,\n \"acc_norm\": 0.24692737430167597,\n\ \ \"acc_norm_stderr\": 0.014422292204808835\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.27124183006535946,\n \"acc_stderr\": 0.025457756696667878,\n\ \ \"acc_norm\": 0.27124183006535946,\n \"acc_norm_stderr\": 0.025457756696667878\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.3183279742765273,\n\ \ \"acc_stderr\": 0.026457225067811032,\n \"acc_norm\": 0.3183279742765273,\n\ \ \"acc_norm_stderr\": 0.026457225067811032\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.2839506172839506,\n \"acc_stderr\": 0.025089478523765134,\n\ \ \"acc_norm\": 0.2839506172839506,\n \"acc_norm_stderr\": 0.025089478523765134\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.25177304964539005,\n \"acc_stderr\": 0.025892151156709405,\n \ \ \"acc_norm\": 0.25177304964539005,\n \"acc_norm_stderr\": 0.025892151156709405\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.242503259452412,\n\ \ \"acc_stderr\": 0.01094657096634878,\n \"acc_norm\": 0.242503259452412,\n\ \ \"acc_norm_stderr\": 0.01094657096634878\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.4522058823529412,\n \"acc_stderr\": 0.030233758551596455,\n\ \ \"acc_norm\": 0.4522058823529412,\n \"acc_norm_stderr\": 0.030233758551596455\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.24509803921568626,\n \"acc_stderr\": 0.017401816711427657,\n \ \ \"acc_norm\": 0.24509803921568626,\n \"acc_norm_stderr\": 0.017401816711427657\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.3,\n\ \ \"acc_stderr\": 0.04389311454644286,\n \"acc_norm\": 0.3,\n \ \ \"acc_norm_stderr\": 0.04389311454644286\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.21224489795918366,\n \"acc_stderr\": 0.026176967197866767,\n\ \ \"acc_norm\": 0.21224489795918366,\n \"acc_norm_stderr\": 0.026176967197866767\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.2537313432835821,\n\ \ \"acc_stderr\": 0.03076944496729601,\n \"acc_norm\": 0.2537313432835821,\n\ \ \"acc_norm_stderr\": 0.03076944496729601\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.2891566265060241,\n\ \ \"acc_stderr\": 0.03529486801511115,\n \"acc_norm\": 0.2891566265060241,\n\ \ \"acc_norm_stderr\": 0.03529486801511115\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.26900584795321636,\n \"acc_stderr\": 0.0340105262010409,\n\ \ \"acc_norm\": 0.26900584795321636,\n \"acc_norm_stderr\": 0.0340105262010409\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.23623011015911874,\n\ \ \"mc1_stderr\": 0.014869755015871114,\n \"mc2\": 0.3585983664640556,\n\ \ \"mc2_stderr\": 0.013742745779138914\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.6471981057616417,\n \"acc_stderr\": 0.013429728101788961\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.019711902956785442,\n \ \ \"acc_stderr\": 0.003828982978735702\n }\n}\n```" repo_url: https://huggingface.co/mwitiderrick/open_llama_3b_glaive_v0.1 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|arc:challenge|25_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-12-23T15-34-19.150703.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|gsm8k|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hellaswag|10_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-management|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-12-23T15-34-19.150703.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-management|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-virology|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-12-23T15-34-19.150703.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|truthfulqa:mc|0_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-12-23T15-34-19.150703.parquet' - config_name: harness_winogrande_5 data_files: - split: 2023_12_23T15_34_19.150703 path: - '**/details_harness|winogrande|5_2023-12-23T15-34-19.150703.parquet' - split: latest path: - '**/details_harness|winogrande|5_2023-12-23T15-34-19.150703.parquet' - config_name: results data_files: - split: 2023_12_23T15_34_19.150703 path: - results_2023-12-23T15-34-19.150703.parquet - split: latest path: - results_2023-12-23T15-34-19.150703.parquet --- # Dataset Card for Evaluation run of mwitiderrick/open_llama_3b_glaive_v0.1  Dataset automatically created during the evaluation run of model [mwitiderrick/open_llama_3b_glaive_v0.1](https://huggingface.co/mwitiderrick/open_llama_3b_glaive_v0.1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_mwitiderrick__open_llama_3b_glaive_v0.1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2023-12-23T15:34:19.150703](https://huggingface.co/datasets/open-llm-leaderboard/details_mwitiderrick__open_llama_3b_glaive_v0.1/blob/main/results_2023-12-23T15-34-19.150703.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": 0.2843747535406573, "acc_stderr": 0.031689110133124844, "acc_norm": 0.28633888958645765, "acc_norm_stderr": 0.03246963675970039, "mc1": 0.23623011015911874, "mc1_stderr": 0.014869755015871114, "mc2": 0.3585983664640556, "mc2_stderr": 0.013742745779138914 }, "harness|arc:challenge|25": { "acc": 0.3703071672354949, "acc_stderr": 0.01411129875167495, "acc_norm": 0.4069965870307167, "acc_norm_stderr": 0.014356399418009131 }, "harness|hellaswag|10": { "acc": 0.4971121290579566, "acc_stderr": 0.004989698183207831, "acc_norm": 0.6744672376020713, "acc_norm_stderr": 0.004676159299105414 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.2814814814814815, "acc_stderr": 0.03885004245800254, "acc_norm": 0.2814814814814815, "acc_norm_stderr": 0.03885004245800254 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.21052631578947367, "acc_stderr": 0.03317672787533157, "acc_norm": 0.21052631578947367, "acc_norm_stderr": 0.03317672787533157 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.29056603773584905, "acc_stderr": 0.027943219989337156, "acc_norm": 0.29056603773584905, "acc_norm_stderr": 0.027943219989337156 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2638888888888889, "acc_stderr": 0.03685651095897532, "acc_norm": 0.2638888888888889, "acc_norm_stderr": 0.03685651095897532 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.23, "acc_stderr": 0.04229525846816505, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816505 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.26, "acc_stderr": 0.044084400227680794, "acc_norm": 0.26, "acc_norm_stderr": 0.044084400227680794 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3236994219653179, "acc_stderr": 0.035676037996391685, "acc_norm": 0.3236994219653179, "acc_norm_stderr": 0.035676037996391685 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.20588235294117646, "acc_stderr": 0.04023382273617749, "acc_norm": 0.20588235294117646, "acc_norm_stderr": 0.04023382273617749 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3148936170212766, "acc_stderr": 0.030363582197238167, "acc_norm": 0.3148936170212766, "acc_norm_stderr": 0.030363582197238167 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3333333333333333, "acc_stderr": 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"harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.30049261083743845, "acc_stderr": 0.03225799476233484, "acc_norm": 0.30049261083743845, "acc_norm_stderr": 0.03225799476233484 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.15, "acc_stderr": 0.035887028128263714, "acc_norm": 0.15, "acc_norm_stderr": 0.035887028128263714 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.26666666666666666, "acc_stderr": 0.034531318018854146, "acc_norm": 0.26666666666666666, "acc_norm_stderr": 0.034531318018854146 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.31313131313131315, "acc_stderr": 0.03304205087813653, "acc_norm": 0.31313131313131315, "acc_norm_stderr": 0.03304205087813653 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.27461139896373055, "acc_stderr": 0.03221024508041154, "acc_norm": 0.27461139896373055, "acc_norm_stderr": 0.03221024508041154 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.32564102564102565, "acc_stderr": 0.02375966576741229, "acc_norm": 0.32564102564102565, "acc_norm_stderr": 0.02375966576741229 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2518518518518518, "acc_stderr": 0.02646611753895991, "acc_norm": 0.2518518518518518, "acc_norm_stderr": 0.02646611753895991 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.2773109243697479, "acc_stderr": 0.029079374539480007, "acc_norm": 0.2773109243697479, "acc_norm_stderr": 0.029079374539480007 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.26490066225165565, "acc_stderr": 0.03603038545360383, "acc_norm": 0.26490066225165565, "acc_norm_stderr": 0.03603038545360383 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.27339449541284405, "acc_stderr": 0.019109299846098275, "acc_norm": 0.27339449541284405, "acc_norm_stderr": 0.019109299846098275 }, "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": 0.24019607843137256, "acc_stderr": 0.02998373305591361, "acc_norm": 0.24019607843137256, "acc_norm_stderr": 0.02998373305591361 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.25316455696202533, "acc_stderr": 0.028304657943035303, "acc_norm": 0.25316455696202533, "acc_norm_stderr": 0.028304657943035303 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.3452914798206278, "acc_stderr": 0.03191100192835794, "acc_norm": 0.3452914798206278, "acc_norm_stderr": 0.03191100192835794 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.22137404580152673, "acc_stderr": 0.03641297081313728, "acc_norm": 0.22137404580152673, "acc_norm_stderr": 0.03641297081313728 }, "harness|hendrycksTest-international_law|5": { "acc": 0.2975206611570248, "acc_stderr": 0.041733491480834974, "acc_norm": 0.2975206611570248, "acc_norm_stderr": 0.041733491480834974 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.28703703703703703, "acc_stderr": 0.043733130409147614, "acc_norm": 0.28703703703703703, "acc_norm_stderr": 0.043733130409147614 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.26993865030674846, "acc_stderr": 0.034878251684978906, "acc_norm": 0.26993865030674846, "acc_norm_stderr": 0.034878251684978906 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.26785714285714285, "acc_stderr": 0.04203277291467764, "acc_norm": 0.26785714285714285, "acc_norm_stderr": 0.04203277291467764 }, "harness|hendrycksTest-management|5": { "acc": 0.2524271844660194, "acc_stderr": 0.04301250399690877, "acc_norm": 0.2524271844660194, "acc_norm_stderr": 0.04301250399690877 }, "harness|hendrycksTest-marketing|5": { "acc": 0.2692307692307692, "acc_stderr": 0.02905858830374884, "acc_norm": 0.2692307692307692, "acc_norm_stderr": 0.02905858830374884 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.28991060025542786, "acc_stderr": 0.016225017944770957, "acc_norm": 0.28991060025542786, "acc_norm_stderr": 0.016225017944770957 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.25722543352601157, "acc_stderr": 0.02353292543104428, "acc_norm": 0.25722543352601157, "acc_norm_stderr": 0.02353292543104428 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.24692737430167597, "acc_stderr": 0.014422292204808835, "acc_norm": 0.24692737430167597, "acc_norm_stderr": 0.014422292204808835 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.27124183006535946, "acc_stderr": 0.025457756696667878, "acc_norm": 0.27124183006535946, "acc_norm_stderr": 0.025457756696667878 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.3183279742765273, "acc_stderr": 0.026457225067811032, "acc_norm": 0.3183279742765273, "acc_norm_stderr": 0.026457225067811032 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.2839506172839506, "acc_stderr": 0.025089478523765134, "acc_norm": 0.2839506172839506, "acc_norm_stderr": 0.025089478523765134 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.25177304964539005, "acc_stderr": 0.025892151156709405, "acc_norm": 0.25177304964539005, "acc_norm_stderr": 0.025892151156709405 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.242503259452412, "acc_stderr": 0.01094657096634878, "acc_norm": 0.242503259452412, "acc_norm_stderr": 0.01094657096634878 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.4522058823529412, "acc_stderr": 0.030233758551596455, "acc_norm": 0.4522058823529412, "acc_norm_stderr": 0.030233758551596455 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.24509803921568626, "acc_stderr": 0.017401816711427657, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.017401816711427657 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.3, "acc_stderr": 0.04389311454644286, "acc_norm": 0.3, "acc_norm_stderr": 0.04389311454644286 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.21224489795918366, "acc_stderr": 0.026176967197866767, "acc_norm": 0.21224489795918366, "acc_norm_stderr": 0.026176967197866767 }, "harness|hendrycksTest-sociology|5": { "acc": 0.2537313432835821, "acc_stderr": 0.03076944496729601, "acc_norm": 0.2537313432835821, "acc_norm_stderr": 0.03076944496729601 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-virology|5": { "acc": 0.2891566265060241, "acc_stderr": 0.03529486801511115, "acc_norm": 0.2891566265060241, "acc_norm_stderr": 0.03529486801511115 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.26900584795321636, "acc_stderr": 0.0340105262010409, "acc_norm": 0.26900584795321636, "acc_norm_stderr": 0.0340105262010409 }, "harness|truthfulqa:mc|0": { "mc1": 0.23623011015911874, "mc1_stderr": 0.014869755015871114, "mc2": 0.3585983664640556, "mc2_stderr": 0.013742745779138914 }, "harness|winogrande|5": { "acc": 0.6471981057616417, "acc_stderr": 0.013429728101788961 }, "harness|gsm8k|5": { "acc": 0.019711902956785442, "acc_stderr": 0.003828982978735702 } } ``` ## Dataset Details ### Dataset Description  - **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]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More Information Needed] ### Source Data  #### Data Collection and Processing  [More Information Needed] #### Who are the source data producers?  [More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

mserna/livecell-hf

--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 1016288264.76 num_examples: 4184 download_size: 1003022893 dataset_size: 1016288264.76 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "livecell-hf" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

CyberHarem/shichijou_aria_seitokaiyakuindomo

--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Shichijou Aria (Seitokai Yakuindomo) This is the dataset of Shichijou Aria (Seitokai Yakuindomo), containing 891 images and their tags. The core tags of this character are `brown_hair, long_hair, brown_eyes, bow`, which are pruned in this dataset. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). ## List of Packages | Name | Images | Size | Download | Type | Description | |:-----------------|---------:|:-----------|:-----------------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------| | raw | 891 | 419.53 MiB | [Download](https://huggingface.co/datasets/CyberHarem/shichijou_aria_seitokaiyakuindomo/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). | | 800 | 891 | 372.14 MiB | [Download](https://huggingface.co/datasets/CyberHarem/shichijou_aria_seitokaiyakuindomo/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. | | stage3-p480-800 | 1847 | 730.95 MiB | [Download](https://huggingface.co/datasets/CyberHarem/shichijou_aria_seitokaiyakuindomo/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. | | 1200 | 891 | 419.22 MiB | [Download](https://huggingface.co/datasets/CyberHarem/shichijou_aria_seitokaiyakuindomo/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. | | stage3-p480-1200 | 1847 | 800.75 MiB | [Download](https://huggingface.co/datasets/CyberHarem/shichijou_aria_seitokaiyakuindomo/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/shichijou_aria_seitokaiyakuindomo', 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 | 16 | ![](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, blazer, school_uniform, solo, smile, closed_eyes | | 1 | 8 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | 1girl, anime_coloring, bowtie, hair_between_eyes, looking_at_viewer, school_uniform, solo, blazer, smile | | 2 | 6 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | 1girl, blazer, bowtie, school_uniform, solo, upper_body, red_bow, smile, hair_between_eyes | | 3 | 9 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | 1girl, blazer, school_uniform, solo, bowtie, smile, upper_body, anime_coloring | | 4 | 12 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | 1girl, blazer, hair_between_eyes, school_uniform, solo, shirt, upper_body, anime_coloring, smile, looking_at_viewer, red_bowtie | | 5 | 20 | ![](samples/5/clu5-sample0.png) | ![](samples/5/clu5-sample1.png) | ![](samples/5/clu5-sample2.png) | ![](samples/5/clu5-sample3.png) | ![](samples/5/clu5-sample4.png) | 1girl, blazer, plaid_skirt, school_uniform, solo, smile | | 6 | 6 | ![](samples/6/clu6-sample0.png) | ![](samples/6/clu6-sample1.png) | ![](samples/6/clu6-sample2.png) | ![](samples/6/clu6-sample3.png) | ![](samples/6/clu6-sample4.png) | 1girl, anime_coloring, dress_shirt, school_uniform, smile, solo, upper_body, bowtie, hair_between_eyes, looking_at_viewer, red_bow, white_shirt | | 7 | 5 | ![](samples/7/clu7-sample0.png) | ![](samples/7/clu7-sample1.png) | ![](samples/7/clu7-sample2.png) | ![](samples/7/clu7-sample3.png) | ![](samples/7/clu7-sample4.png) | 1girl, blazer, collared_shirt, hair_between_eyes, red_bowtie, school_uniform, smile, solo, upper_body, white_shirt, bangs, brown_jacket, closed_mouth, long_sleeves, indoors, looking_at_viewer, wing_collar | | 8 | 5 | ![](samples/8/clu8-sample0.png) | ![](samples/8/clu8-sample1.png) | ![](samples/8/clu8-sample2.png) | ![](samples/8/clu8-sample3.png) | ![](samples/8/clu8-sample4.png) | 1girl, blazer, chair, school_uniform, sitting, solo, red_bowtie, smile, upper_body | | 9 | 9 | ![](samples/9/clu9-sample0.png) | ![](samples/9/clu9-sample1.png) | ![](samples/9/clu9-sample2.png) | ![](samples/9/clu9-sample3.png) | ![](samples/9/clu9-sample4.png) | 1girl, blazer, long_sleeves, plaid_skirt, pleated_skirt, red_bowtie, school_uniform, solo, brown_skirt, indoors, white_shirt, brown_jacket, closed_mouth, collared_shirt, sitting, smile, closed_eyes, folding_chair | | 10 | 6 | ![](samples/10/clu10-sample0.png) | ![](samples/10/clu10-sample1.png) | ![](samples/10/clu10-sample2.png) | ![](samples/10/clu10-sample3.png) | ![](samples/10/clu10-sample4.png) | 2girls, school_uniform, smile, blazer, |_| | | 11 | 10 | ![](samples/11/clu11-sample0.png) | ![](samples/11/clu11-sample1.png) | ![](samples/11/clu11-sample2.png) | ![](samples/11/clu11-sample3.png) | ![](samples/11/clu11-sample4.png) | 1girl, solo, |_|, simple_background, white_background, upper_body, smile, collarbone, ponytail, hair_between_eyes, shirt | | 12 | 9 | ![](samples/12/clu12-sample0.png) | ![](samples/12/clu12-sample1.png) | ![](samples/12/clu12-sample2.png) | ![](samples/12/clu12-sample3.png) | ![](samples/12/clu12-sample4.png) | 1girl, solo, yukata, ponytail, smile, night_sky | ### Table Version | # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | blazer | school_uniform | solo | smile | closed_eyes | anime_coloring | bowtie | hair_between_eyes | looking_at_viewer | upper_body | red_bow | shirt | red_bowtie | plaid_skirt | dress_shirt | white_shirt | collared_shirt | bangs | brown_jacket | closed_mouth | long_sleeves | indoors | wing_collar | chair | sitting | pleated_skirt | brown_skirt | folding_chair | 2girls | |_| | simple_background | white_background | collarbone | ponytail | yukata | night_sky | |----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:---------|:-----------------|:-------|:--------|:--------------|:-----------------|:---------|:--------------------|:--------------------|:-------------|:----------|:--------|:-------------|:--------------|:--------------|:--------------|:-----------------|:--------|:---------------|:---------------|:---------------|:----------|:--------------|:--------|:----------|:----------------|:--------------|:----------------|:---------|:------|:--------------------|:-------------------|:-------------|:-----------|:---------|:------------| | 0 | 16 | ![](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 | 8 | ![](samples/1/clu1-sample0.png) | ![](samples/1/clu1-sample1.png) | ![](samples/1/clu1-sample2.png) | ![](samples/1/clu1-sample3.png) | ![](samples/1/clu1-sample4.png) | X | X | X | X | X | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 2 | 6 | ![](samples/2/clu2-sample0.png) | ![](samples/2/clu2-sample1.png) | ![](samples/2/clu2-sample2.png) | ![](samples/2/clu2-sample3.png) | ![](samples/2/clu2-sample4.png) | X | X | X | X | X | | | X | X | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | 3 | 9 | ![](samples/3/clu3-sample0.png) | ![](samples/3/clu3-sample1.png) | ![](samples/3/clu3-sample2.png) | ![](samples/3/clu3-sample3.png) | ![](samples/3/clu3-sample4.png) | X | X | X | X | X | | X | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | 4 | 12 | ![](samples/4/clu4-sample0.png) | ![](samples/4/clu4-sample1.png) | ![](samples/4/clu4-sample2.png) | ![](samples/4/clu4-sample3.png) | ![](samples/4/clu4-sample4.png) | X | X | X | X | X | | X | | X | X | X | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | 5 | 20 | ![](samples/5/clu5-sample0.png) | ![](samples/5/clu5-sample1.png) | ![](samples/5/clu5-sample2.png) | ![](samples/5/clu5-sample3.png) | ![](samples/5/clu5-sample4.png) | X | X | X | X | X | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | 6 | 6 | ![](samples/6/clu6-sample0.png) | ![](samples/6/clu6-sample1.png) | ![](samples/6/clu6-sample2.png) | ![](samples/6/clu6-sample3.png) | ![](samples/6/clu6-sample4.png) | X | | X | X | X | | X | X | X | X | X | X | | | | X | X | | | | | | | | | | | | | | | | | | | | | | 7 | 5 | ![](samples/7/clu7-sample0.png) | ![](samples/7/clu7-sample1.png) | ![](samples/7/clu7-sample2.png) | ![](samples/7/clu7-sample3.png) | ![](samples/7/clu7-sample4.png) | X | X | X | X | X | | | | X | X | X | | | X | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | 8 | 5 | ![](samples/8/clu8-sample0.png) | ![](samples/8/clu8-sample1.png) | ![](samples/8/clu8-sample2.png) | ![](samples/8/clu8-sample3.png) | ![](samples/8/clu8-sample4.png) | X | X | X | X | X | | | | | | X | | | X | | | | | | | | | | | X | X | | | | | | | | | | | | | 9 | 9 | ![](samples/9/clu9-sample0.png) | ![](samples/9/clu9-sample1.png) | ![](samples/9/clu9-sample2.png) | ![](samples/9/clu9-sample3.png) | ![](samples/9/clu9-sample4.png) | X | X | X | X | X | X | | | | | | | | X | X | | X | X | | X | X | X | X | | | X | X | X | X | | | | | | | | | | 10 | 6 | ![](samples/10/clu10-sample0.png) | ![](samples/10/clu10-sample1.png) | ![](samples/10/clu10-sample2.png) | ![](samples/10/clu10-sample3.png) | ![](samples/10/clu10-sample4.png) | | X | X | | X | | | | | | | | | | | | | | | | | | | | | | | | | X | X | | | | | | | | 11 | 10 | ![](samples/11/clu11-sample0.png) | ![](samples/11/clu11-sample1.png) | ![](samples/11/clu11-sample2.png) | ![](samples/11/clu11-sample3.png) | ![](samples/11/clu11-sample4.png) | X | | | X | X | | | | X | | X | | X | | | | | | | | | | | | | | | | | | X | X | X | X | X | | | | 12 | 9 | ![](samples/12/clu12-sample0.png) | ![](samples/12/clu12-sample1.png) | ![](samples/12/clu12-sample2.png) | ![](samples/12/clu12-sample3.png) | ![](samples/12/clu12-sample4.png) | X | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X |

Carlosgg14/piccolo

--- license: openrail ---

darcy01/autotrain-data-hanzbydarcycao

--- language: - zh - en task_categories: - translation --- # AutoTrain Dataset for project: hanzbydarcycao ## Dataset Description This dataset has been automatically processed by AutoTrain for project hanzbydarcycao. ### Languages The BCP-47 code for the dataset's language is zh2en. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "source": "sarashi", "target": "sarashi" }, { "source": "Dojo", "target": "Dojo" } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "source": "Value(dtype='string', id=None)", "target": "Value(dtype='string', id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: | Split name | Num samples | | ------------ | ------------------- | | train | 98 | | valid | 25 |

phanvancongthanh/pubchem_bioassay_standardized

--- dataset_info: features: - name: standardized_smiles dtype: string splits: - name: train num_bytes: 10187907266 num_examples: 210186056 download_size: 4860575313 dataset_size: 10187907266 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "pubchem_bioassay_standardized" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

lhk/test_dataset

--- license: cc-by-2.0 ---

FINNUMBER/FINCH_TRAIN_QA_BQA_400

--- 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: 1612883 num_examples: 400 download_size: 871345 dataset_size: 1612883 configs: - config_name: default data_files: - split: train path: data/train-* ---

open-llm-leaderboard/details_JiheonJeong__v1

--- pretty_name: Evaluation run of JiheonJeong/v1 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [JiheonJeong/v1](https://huggingface.co/JiheonJeong/v1) 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_JiheonJeong__v1\"\ ,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\ These are the [latest results from run 2024-03-27T19:55:05.428463](https://huggingface.co/datasets/open-llm-leaderboard/details_JiheonJeong__v1/blob/main/results_2024-03-27T19-55-05.428463.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\": 0.42090733682944437,\n\ \ \"acc_stderr\": 0.03455222362037901,\n \"acc_norm\": 0.42437664279794174,\n\ \ \"acc_norm_stderr\": 0.035312936290375636,\n \"mc1\": 0.21909424724602203,\n\ \ \"mc1_stderr\": 0.014480038578757442,\n \"mc2\": 0.33036644378983426,\n\ \ \"mc2_stderr\": 0.01345975351436465\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.46928327645051193,\n \"acc_stderr\": 0.014583792546304038,\n\ \ \"acc_norm\": 0.4812286689419795,\n \"acc_norm_stderr\": 0.014601090150633964\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5300736904999004,\n\ \ \"acc_stderr\": 0.004980747448813311,\n \"acc_norm\": 0.7159928301135232,\n\ \ \"acc_norm_stderr\": 0.0045001864244437985\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \ \ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.4666666666666667,\n\ \ \"acc_stderr\": 0.043097329010363554,\n \"acc_norm\": 0.4666666666666667,\n\ \ \"acc_norm_stderr\": 0.043097329010363554\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.42105263157894735,\n \"acc_stderr\": 0.040179012759817494,\n\ \ \"acc_norm\": 0.42105263157894735,\n \"acc_norm_stderr\": 0.040179012759817494\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.41,\n\ \ \"acc_stderr\": 0.049431107042371025,\n \"acc_norm\": 0.41,\n \ \ \"acc_norm_stderr\": 0.049431107042371025\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.47547169811320755,\n \"acc_stderr\": 0.030735822206205615,\n\ \ \"acc_norm\": 0.47547169811320755,\n \"acc_norm_stderr\": 0.030735822206205615\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.4583333333333333,\n\ \ \"acc_stderr\": 0.04166666666666665,\n \"acc_norm\": 0.4583333333333333,\n\ \ \"acc_norm_stderr\": 0.04166666666666665\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.39,\n \"acc_stderr\": 0.04902071300001975,\n \ \ \"acc_norm\": 0.39,\n \"acc_norm_stderr\": 0.04902071300001975\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.39,\n \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.39,\n\ \ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \ \ \"acc_norm\": 0.29,\n \"acc_norm_stderr\": 0.045604802157206845\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.4393063583815029,\n\ \ \"acc_stderr\": 0.03784271932887467,\n \"acc_norm\": 0.4393063583815029,\n\ \ \"acc_norm_stderr\": 0.03784271932887467\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.17647058823529413,\n \"acc_stderr\": 0.0379328118530781,\n\ \ \"acc_norm\": 0.17647058823529413,\n \"acc_norm_stderr\": 0.0379328118530781\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.54,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.54,\n\ \ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.41702127659574467,\n \"acc_stderr\": 0.032232762667117124,\n\ \ \"acc_norm\": 0.41702127659574467,\n \"acc_norm_stderr\": 0.032232762667117124\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.30701754385964913,\n\ \ \"acc_stderr\": 0.04339138322579861,\n \"acc_norm\": 0.30701754385964913,\n\ \ \"acc_norm_stderr\": 0.04339138322579861\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.4206896551724138,\n \"acc_stderr\": 0.0411391498118926,\n\ \ \"acc_norm\": 0.4206896551724138,\n \"acc_norm_stderr\": 0.0411391498118926\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.2777777777777778,\n \"acc_stderr\": 0.023068188848261124,\n \"\ acc_norm\": 0.2777777777777778,\n \"acc_norm_stderr\": 0.023068188848261124\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.2777777777777778,\n\ \ \"acc_stderr\": 0.040061680838488774,\n \"acc_norm\": 0.2777777777777778,\n\ \ \"acc_norm_stderr\": 0.040061680838488774\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.3,\n \"acc_stderr\": 0.046056618647183814,\n \ \ \"acc_norm\": 0.3,\n \"acc_norm_stderr\": 0.046056618647183814\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.47096774193548385,\n\ \ \"acc_stderr\": 0.028396016402761005,\n \"acc_norm\": 0.47096774193548385,\n\ \ \"acc_norm_stderr\": 0.028396016402761005\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\": 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \"acc_norm\"\ : 0.44,\n \"acc_norm_stderr\": 0.04988876515698589\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.41818181818181815,\n \"acc_stderr\": 0.03851716319398394,\n\ \ \"acc_norm\": 0.41818181818181815,\n \"acc_norm_stderr\": 0.03851716319398394\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.5202020202020202,\n \"acc_stderr\": 0.03559443565563918,\n \"\ acc_norm\": 0.5202020202020202,\n \"acc_norm_stderr\": 0.03559443565563918\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.5854922279792746,\n \"acc_stderr\": 0.03555300319557669,\n\ \ \"acc_norm\": 0.5854922279792746,\n \"acc_norm_stderr\": 0.03555300319557669\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.41025641025641024,\n \"acc_stderr\": 0.024939313906940784,\n\ \ \"acc_norm\": 0.41025641025641024,\n \"acc_norm_stderr\": 0.024939313906940784\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.26666666666666666,\n \"acc_stderr\": 0.02696242432507383,\n \ \ \"acc_norm\": 0.26666666666666666,\n \"acc_norm_stderr\": 0.02696242432507383\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.38235294117647056,\n \"acc_stderr\": 0.03156663099215416,\n\ \ \"acc_norm\": 0.38235294117647056,\n \"acc_norm_stderr\": 0.03156663099215416\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.25165562913907286,\n \"acc_stderr\": 0.03543304234389985,\n \"\ acc_norm\": 0.25165562913907286,\n \"acc_norm_stderr\": 0.03543304234389985\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.5669724770642202,\n \"acc_stderr\": 0.021244146569074345,\n \"\ acc_norm\": 0.5669724770642202,\n \"acc_norm_stderr\": 0.021244146569074345\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.37037037037037035,\n \"acc_stderr\": 0.03293377139415191,\n \"\ acc_norm\": 0.37037037037037035,\n \"acc_norm_stderr\": 0.03293377139415191\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.4411764705882353,\n \"acc_stderr\": 0.034849415144292316,\n \"\ acc_norm\": 0.4411764705882353,\n \"acc_norm_stderr\": 0.034849415144292316\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.39662447257383965,\n \"acc_stderr\": 0.03184399873811226,\n \ \ \"acc_norm\": 0.39662447257383965,\n \"acc_norm_stderr\": 0.03184399873811226\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.4349775784753363,\n\ \ \"acc_stderr\": 0.03327283370271344,\n \"acc_norm\": 0.4349775784753363,\n\ \ \"acc_norm_stderr\": 0.03327283370271344\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\":\ \ 0.6033057851239669,\n \"acc_stderr\": 0.044658697805310094,\n \"\ acc_norm\": 0.6033057851239669,\n \"acc_norm_stderr\": 0.044658697805310094\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.4074074074074074,\n\ \ \"acc_stderr\": 0.047500773411999854,\n \"acc_norm\": 0.4074074074074074,\n\ \ \"acc_norm_stderr\": 0.047500773411999854\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.4110429447852761,\n \"acc_stderr\": 0.038656978537853624,\n\ \ \"acc_norm\": 0.4110429447852761,\n \"acc_norm_stderr\": 0.038656978537853624\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.39285714285714285,\n\ \ \"acc_stderr\": 0.04635550135609976,\n \"acc_norm\": 0.39285714285714285,\n\ \ \"acc_norm_stderr\": 0.04635550135609976\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.5728155339805825,\n \"acc_stderr\": 0.04897957737781168,\n\ \ \"acc_norm\": 0.5728155339805825,\n \"acc_norm_stderr\": 0.04897957737781168\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.6111111111111112,\n\ \ \"acc_stderr\": 0.03193705726200293,\n \"acc_norm\": 0.6111111111111112,\n\ \ \"acc_norm_stderr\": 0.03193705726200293\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.5466155810983397,\n\ \ \"acc_stderr\": 0.017802087135850304,\n \"acc_norm\": 0.5466155810983397,\n\ \ \"acc_norm_stderr\": 0.017802087135850304\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.43641618497109824,\n \"acc_stderr\": 0.02670054542494369,\n\ \ \"acc_norm\": 0.43641618497109824,\n \"acc_norm_stderr\": 0.02670054542494369\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.24134078212290502,\n\ \ \"acc_stderr\": 0.014310999547961452,\n \"acc_norm\": 0.24134078212290502,\n\ \ \"acc_norm_stderr\": 0.014310999547961452\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.46078431372549017,\n \"acc_stderr\": 0.028541722692618874,\n\ \ \"acc_norm\": 0.46078431372549017,\n \"acc_norm_stderr\": 0.028541722692618874\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.41479099678456594,\n\ \ \"acc_stderr\": 0.02798268045975956,\n \"acc_norm\": 0.41479099678456594,\n\ \ \"acc_norm_stderr\": 0.02798268045975956\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.4722222222222222,\n \"acc_stderr\": 0.027777777777777797,\n\ \ \"acc_norm\": 0.4722222222222222,\n \"acc_norm_stderr\": 0.027777777777777797\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.3404255319148936,\n \"acc_stderr\": 0.028267657482650144,\n \ \ \"acc_norm\": 0.3404255319148936,\n \"acc_norm_stderr\": 0.028267657482650144\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3428943937418514,\n\ \ \"acc_stderr\": 0.012123463271585895,\n \"acc_norm\": 0.3428943937418514,\n\ \ \"acc_norm_stderr\": 0.012123463271585895\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.34191176470588236,\n \"acc_stderr\": 0.028814722422254177,\n\ \ \"acc_norm\": 0.34191176470588236,\n \"acc_norm_stderr\": 0.028814722422254177\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.3758169934640523,\n \"acc_stderr\": 0.019594021136577454,\n \ \ \"acc_norm\": 0.3758169934640523,\n \"acc_norm_stderr\": 0.019594021136577454\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.4818181818181818,\n\ \ \"acc_stderr\": 0.04785964010794916,\n \"acc_norm\": 0.4818181818181818,\n\ \ \"acc_norm_stderr\": 0.04785964010794916\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.46122448979591835,\n \"acc_stderr\": 0.031912820526692774,\n\ \ \"acc_norm\": 0.46122448979591835,\n \"acc_norm_stderr\": 0.031912820526692774\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.417910447761194,\n\ \ \"acc_stderr\": 0.034875586404620636,\n \"acc_norm\": 0.417910447761194,\n\ \ \"acc_norm_stderr\": 0.034875586404620636\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.57,\n \"acc_stderr\": 0.04975698519562428,\n \ \ \"acc_norm\": 0.57,\n \"acc_norm_stderr\": 0.04975698519562428\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.4578313253012048,\n\ \ \"acc_stderr\": 0.0387862677100236,\n \"acc_norm\": 0.4578313253012048,\n\ \ \"acc_norm_stderr\": 0.0387862677100236\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.5321637426900585,\n \"acc_stderr\": 0.03826882417660368,\n\ \ \"acc_norm\": 0.5321637426900585,\n \"acc_norm_stderr\": 0.03826882417660368\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.21909424724602203,\n\ \ \"mc1_stderr\": 0.014480038578757442,\n \"mc2\": 0.33036644378983426,\n\ \ \"mc2_stderr\": 0.01345975351436465\n },\n \"harness|winogrande|5\"\ : {\n \"acc\": 0.6606156274664562,\n \"acc_stderr\": 0.01330771492894175\n\ \ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.17437452615617893,\n \ \ \"acc_stderr\": 0.010451421361976234\n }\n}\n```" repo_url: https://huggingface.co/JiheonJeong/v1 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_27T18_34_04.185928 path: - '**/details_harness|arc:challenge|25_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|arc:challenge|25_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2024-03-27T19-55-05.428463.parquet' - config_name: harness_gsm8k_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|gsm8k|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|gsm8k|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|gsm8k|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hellaswag|10_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hellaswag|10_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-27T18-34-04.185928.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-international_law|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-management|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-marketing|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-sociology|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-virology|5_2024-03-27T19-55-05.428463.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-management|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-management|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-virology|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2024-03-27T19-55-05.428463.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|truthfulqa:mc|0_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|truthfulqa:mc|0_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2024-03-27T19-55-05.428463.parquet' - config_name: harness_winogrande_5 data_files: - split: 2024_03_27T18_34_04.185928 path: - '**/details_harness|winogrande|5_2024-03-27T18-34-04.185928.parquet' - split: 2024_03_27T19_55_05.428463 path: - '**/details_harness|winogrande|5_2024-03-27T19-55-05.428463.parquet' - split: latest path: - '**/details_harness|winogrande|5_2024-03-27T19-55-05.428463.parquet' - config_name: results data_files: - split: 2024_03_27T18_34_04.185928 path: - results_2024-03-27T18-34-04.185928.parquet - split: 2024_03_27T19_55_05.428463 path: - results_2024-03-27T19-55-05.428463.parquet - split: latest path: - results_2024-03-27T19-55-05.428463.parquet --- # Dataset Card for Evaluation run of JiheonJeong/v1  Dataset automatically created during the evaluation run of model [JiheonJeong/v1](https://huggingface.co/JiheonJeong/v1) 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_JiheonJeong__v1", "harness_winogrande_5", split="train") ``` ## Latest results These are the [latest results from run 2024-03-27T19:55:05.428463](https://huggingface.co/datasets/open-llm-leaderboard/details_JiheonJeong__v1/blob/main/results_2024-03-27T19-55-05.428463.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": 0.42090733682944437, "acc_stderr": 0.03455222362037901, "acc_norm": 0.42437664279794174, "acc_norm_stderr": 0.035312936290375636, "mc1": 0.21909424724602203, "mc1_stderr": 0.014480038578757442, "mc2": 0.33036644378983426, "mc2_stderr": 0.01345975351436465 }, "harness|arc:challenge|25": { "acc": 0.46928327645051193, "acc_stderr": 0.014583792546304038, "acc_norm": 0.4812286689419795, "acc_norm_stderr": 0.014601090150633964 }, "harness|hellaswag|10": { "acc": 0.5300736904999004, "acc_stderr": 0.004980747448813311, "acc_norm": 0.7159928301135232, "acc_norm_stderr": 0.0045001864244437985 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4666666666666667, "acc_stderr": 0.043097329010363554, "acc_norm": 0.4666666666666667, "acc_norm_stderr": 0.043097329010363554 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.42105263157894735, "acc_stderr": 0.040179012759817494, "acc_norm": 0.42105263157894735, "acc_norm_stderr": 0.040179012759817494 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.47547169811320755, "acc_stderr": 0.030735822206205615, "acc_norm": 0.47547169811320755, "acc_norm_stderr": 0.030735822206205615 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4583333333333333, "acc_stderr": 0.04166666666666665, "acc_norm": 0.4583333333333333, "acc_norm_stderr": 0.04166666666666665 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4393063583815029, "acc_stderr": 0.03784271932887467, "acc_norm": 0.4393063583815029, "acc_norm_stderr": 0.03784271932887467 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.17647058823529413, "acc_stderr": 0.0379328118530781, "acc_norm": 0.17647058823529413, "acc_norm_stderr": 0.0379328118530781 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.41702127659574467, "acc_stderr": 0.032232762667117124, "acc_norm": 0.41702127659574467, "acc_norm_stderr": 0.032232762667117124 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.30701754385964913, "acc_stderr": 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"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": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.41818181818181815, "acc_stderr": 0.03851716319398394, "acc_norm": 0.41818181818181815, "acc_norm_stderr": 0.03851716319398394 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5202020202020202, "acc_stderr": 0.03559443565563918, "acc_norm": 0.5202020202020202, "acc_norm_stderr": 0.03559443565563918 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.5854922279792746, "acc_stderr": 0.03555300319557669, "acc_norm": 0.5854922279792746, "acc_norm_stderr": 0.03555300319557669 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.41025641025641024, "acc_stderr": 0.024939313906940784, "acc_norm": 0.41025641025641024, "acc_norm_stderr": 0.024939313906940784 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.26666666666666666, "acc_stderr": 0.02696242432507383, "acc_norm": 0.26666666666666666, "acc_norm_stderr": 0.02696242432507383 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.38235294117647056, "acc_stderr": 0.03156663099215416, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.03156663099215416 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.25165562913907286, "acc_stderr": 0.03543304234389985, "acc_norm": 0.25165562913907286, "acc_norm_stderr": 0.03543304234389985 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.5669724770642202, "acc_stderr": 0.021244146569074345, "acc_norm": 0.5669724770642202, "acc_norm_stderr": 0.021244146569074345 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.37037037037037035, "acc_stderr": 0.03293377139415191, "acc_norm": 0.37037037037037035, "acc_norm_stderr": 0.03293377139415191 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.4411764705882353, "acc_stderr": 0.034849415144292316, "acc_norm": 0.4411764705882353, "acc_norm_stderr": 0.034849415144292316 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.39662447257383965, "acc_stderr": 0.03184399873811226, "acc_norm": 0.39662447257383965, "acc_norm_stderr": 0.03184399873811226 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.4349775784753363, "acc_stderr": 0.03327283370271344, "acc_norm": 0.4349775784753363, "acc_norm_stderr": 0.03327283370271344 }, "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": 0.6033057851239669, "acc_stderr": 0.044658697805310094, "acc_norm": 0.6033057851239669, "acc_norm_stderr": 0.044658697805310094 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.4074074074074074, "acc_stderr": 0.047500773411999854, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.047500773411999854 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.4110429447852761, "acc_stderr": 0.038656978537853624, "acc_norm": 0.4110429447852761, "acc_norm_stderr": 0.038656978537853624 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.39285714285714285, "acc_stderr": 0.04635550135609976, "acc_norm": 0.39285714285714285, "acc_norm_stderr": 0.04635550135609976 }, "harness|hendrycksTest-management|5": { "acc": 0.5728155339805825, "acc_stderr": 0.04897957737781168, "acc_norm": 0.5728155339805825, "acc_norm_stderr": 0.04897957737781168 }, "harness|hendrycksTest-marketing|5": { "acc": 0.6111111111111112, "acc_stderr": 0.03193705726200293, "acc_norm": 0.6111111111111112, "acc_norm_stderr": 0.03193705726200293 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.43, "acc_stderr": 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"harness|hendrycksTest-prehistory|5": { "acc": 0.4722222222222222, "acc_stderr": 0.027777777777777797, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.027777777777777797 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.3404255319148936, "acc_stderr": 0.028267657482650144, "acc_norm": 0.3404255319148936, "acc_norm_stderr": 0.028267657482650144 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.3428943937418514, "acc_stderr": 0.012123463271585895, "acc_norm": 0.3428943937418514, "acc_norm_stderr": 0.012123463271585895 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.34191176470588236, "acc_stderr": 0.028814722422254177, "acc_norm": 0.34191176470588236, "acc_norm_stderr": 0.028814722422254177 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.3758169934640523, "acc_stderr": 0.019594021136577454, "acc_norm": 0.3758169934640523, "acc_norm_stderr": 0.019594021136577454 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.4818181818181818, "acc_stderr": 0.04785964010794916, "acc_norm": 0.4818181818181818, "acc_norm_stderr": 0.04785964010794916 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.46122448979591835, "acc_stderr": 0.031912820526692774, "acc_norm": 0.46122448979591835, "acc_norm_stderr": 0.031912820526692774 }, "harness|hendrycksTest-sociology|5": { "acc": 0.417910447761194, "acc_stderr": 0.034875586404620636, "acc_norm": 0.417910447761194, "acc_norm_stderr": 0.034875586404620636 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.57, "acc_stderr": 0.04975698519562428, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-virology|5": { "acc": 0.4578313253012048, "acc_stderr": 0.0387862677100236, "acc_norm": 0.4578313253012048, "acc_norm_stderr": 0.0387862677100236 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.5321637426900585, "acc_stderr": 0.03826882417660368, "acc_norm": 0.5321637426900585, "acc_norm_stderr": 0.03826882417660368 }, "harness|truthfulqa:mc|0": { "mc1": 0.21909424724602203, "mc1_stderr": 0.014480038578757442, "mc2": 0.33036644378983426, "mc2_stderr": 0.01345975351436465 }, "harness|winogrande|5": { "acc": 0.6606156274664562, "acc_stderr": 0.01330771492894175 }, "harness|gsm8k|5": { "acc": 0.17437452615617893, "acc_stderr": 0.010451421361976234 } } ``` ## Dataset Details ### Dataset Description  - **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]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Dataset Structure  [More Information Needed] ## Dataset Creation ### Curation Rationale  [More 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[More Information Needed] ### Annotations [optional]  #### Annotation process  [More Information Needed] #### Who are the annotators?  [More Information Needed] #### Personal and Sensitive Information  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]

gguichard/myriade_noun_aligned_with_wordnet

--- dataset_info: features: - name: tokens sequence: string - name: wn_sens sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 76227656 num_examples: 127112 download_size: 18764458 dataset_size: 76227656 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "myriade_noun_aligned_with_wordnet" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

joey234/mmlu-anatomy-original-neg-prepend

--- dataset_info: features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D - name: neg_prompt dtype: string splits: - name: test num_bytes: 2413 num_examples: 6 download_size: 6038 dataset_size: 2413 --- # Dataset Card for "mmlu-anatomy-original-neg-prepend" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Joi123/bitcoin-tweets-2023

--- language: - en tags: - bitcoin - tweets - tweet - Twitter - btc size_categories: - 100K<n<1M pretty_name: h ---

byebyebye/ukr-wiki-qa-v1

--- dataset_info: features: - name: prompt dtype: string - name: topic dtype: string - name: question dtype: string - name: response dtype: string splits: - name: train num_bytes: 58645347 num_examples: 40567 download_size: 28771700 dataset_size: 58645347 configs: - config_name: default data_files: - split: train path: data/train-* ---

itamarcard/vitrine

--- license: openrail ---