id
stringlengths
2
115
lastModified
stringlengths
24
24
tags
list
author
stringlengths
2
42
description
stringlengths
0
68.7k
citation
stringlengths
0
10.7k
cardData
null
likes
int64
0
3.55k
downloads
int64
0
10.1M
card
stringlengths
0
1.01M
asus-aics/QALM
2023-09-15T07:46:43.000Z
[ "region:us" ]
asus-aics
null
null
null
0
0
Citations to various datasets and documentation to be added
CyberHarem/yuuki_haru_idolmastercinderellagirls
2023-09-17T17:38:42.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of yuuki_haru (THE iDOLM@STER: Cinderella Girls) This is the dataset of yuuki_haru (THE iDOLM@STER: Cinderella Girls), containing 200 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 200 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 544 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 200 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 200 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 200 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 200 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 200 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 544 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 544 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 544 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
goodfellowliu/Flickr2K
2023-09-15T07:58:13.000Z
[ "license:apache-2.0", "region:us" ]
goodfellowliu
null
null
null
0
0
--- license: apache-2.0 ---
CyberHarem/yokoyama_chika_idolmastercinderellagirls
2023-09-17T17:38:44.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of yokoyama_chika (THE iDOLM@STER: Cinderella Girls) This is the dataset of yokoyama_chika (THE iDOLM@STER: Cinderella Girls), containing 84 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 84 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 234 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 84 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 84 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 84 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 84 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 84 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 234 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 234 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 234 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/saionji_kotoka_idolmastercinderellagirls
2023-09-17T17:38:46.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of saionji_kotoka (THE iDOLM@STER: Cinderella Girls) This is the dataset of saionji_kotoka (THE iDOLM@STER: Cinderella Girls), containing 81 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 81 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 215 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 81 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 81 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 81 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 81 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 81 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 215 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 215 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 215 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/etou_misaki_idolmastercinderellagirls
2023-09-17T17:38:48.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of etou_misaki (THE iDOLM@STER: Cinderella Girls) This is the dataset of etou_misaki (THE iDOLM@STER: Cinderella Girls), containing 29 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 29 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 71 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 29 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 29 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 29 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 29 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 29 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 71 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 71 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 71 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
edbeeching/gia-dataset-tokenized-2024-2
2023-09-15T11:03:29.000Z
[ "region:us" ]
edbeeching
null
null
null
0
0
--- dataset_info: - config_name: atari-alien features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: loss_mask sequence: bool - name: patch_positions sequence: sequence: sequence: float64 - name: input_ids sequence: int32 - name: input_types sequence: int64 - name: local_positions sequence: int64 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2427492496 num_examples: 1836 download_size: 197411801 dataset_size: 2427492496 - config_name: atari-amidar features: - name: loss_mask sequence: bool - name: local_positions sequence: int64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: input_ids sequence: int32 - name: input_types sequence: int64 - name: attention_mask sequence: bool splits: - name: train num_bytes: 23292403388 num_examples: 17641 - name: test num_bytes: 2157941388 num_examples: 1637 download_size: 1619960876 dataset_size: 25450344776 - config_name: atari-assault features: - name: loss_mask sequence: bool - name: local_positions sequence: int64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: input_ids sequence: int32 - name: input_types sequence: int64 - name: attention_mask sequence: bool splits: - name: train num_bytes: 23077576568 num_examples: 17434 - name: test num_bytes: 1898092400 num_examples: 1436 download_size: 760479036 dataset_size: 24975668968 - config_name: atari-asterix features: - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: loss_mask sequence: bool - name: patches sequence: sequence: sequence: sequence: uint8 - name: attention_mask sequence: bool splits: - name: train num_bytes: 25094377660 num_examples: 19161 download_size: 943683526 dataset_size: 25094377660 - config_name: atari-asteroids features: - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: loss_mask sequence: bool - name: patches sequence: sequence: sequence: sequence: uint8 - name: attention_mask sequence: bool splits: - name: train num_bytes: 22677165856 num_examples: 17112 download_size: 807221186 dataset_size: 22677165856 - config_name: atari-atlantis features: - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: loss_mask sequence: bool - name: patches sequence: sequence: sequence: sequence: uint8 - name: attention_mask sequence: bool splits: - name: train num_bytes: 22825149408 num_examples: 17240 download_size: 745609354 dataset_size: 22825149408 - config_name: atari-bankheist features: - name: input_types sequence: int64 - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: input_ids sequence: int32 - name: loss_mask sequence: bool - name: attention_mask sequence: bool splits: - name: train num_bytes: 23741888116 num_examples: 18043 - name: test num_bytes: 2701097304 num_examples: 2050 download_size: 2847993069 dataset_size: 26442985420 - config_name: atari-battlezone features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: local_positions sequence: int64 - name: loss_mask sequence: bool - name: input_types sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: input_ids sequence: int32 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2683381416 num_examples: 2030 download_size: 162167846 dataset_size: 2683381416 - config_name: atari-berzerk features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: loss_mask sequence: bool - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2683232284 num_examples: 2025 download_size: 98071291 dataset_size: 2683232284 - config_name: atari-bowling features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: loss_mask sequence: bool - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2638612892 num_examples: 2001 download_size: 57099861 dataset_size: 2638612892 - config_name: atari-boxing features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: loss_mask sequence: bool - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2925635312 num_examples: 2252 download_size: 154591181 dataset_size: 2925635312 - config_name: atari-breakout features: - name: loss_mask sequence: bool - name: patch_positions sequence: sequence: sequence: float64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: attention_mask sequence: bool splits: - name: train num_bytes: 21372025124 num_examples: 16135 - name: test num_bytes: 2843462328 num_examples: 2146 download_size: 740521401 dataset_size: 24215487452 - config_name: atari-centipede features: - name: loss_mask sequence: bool - name: patch_positions sequence: sequence: sequence: float64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: attention_mask sequence: bool splits: - name: train num_bytes: 24525541956 num_examples: 18727 - name: test num_bytes: 2743854332 num_examples: 2097 download_size: 886355860 dataset_size: 27269396288 - config_name: atari-choppercommand features: - name: loss_mask sequence: bool - name: patch_positions sequence: sequence: sequence: float64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: attention_mask sequence: bool splits: - name: train num_bytes: 21916144968 num_examples: 16598 - name: test num_bytes: 3130204472 num_examples: 2370 download_size: 1120222280 dataset_size: 25046349440 - config_name: atari-crazyclimber features: - name: input_types sequence: int64 - name: loss_mask sequence: bool - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: local_positions sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2452295076 num_examples: 1855 download_size: 147409815 dataset_size: 2452295076 - config_name: atari-defender features: - name: input_types sequence: int64 - name: loss_mask sequence: bool - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: local_positions sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2667101644 num_examples: 2013 download_size: 76162534 dataset_size: 2667101644 - config_name: atari-demonattack features: - name: input_types sequence: int64 - name: loss_mask sequence: bool - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: local_positions sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2655965584 num_examples: 2004 download_size: 71540075 dataset_size: 2655965584 - config_name: atari-doubledunk features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: local_positions sequence: int64 - name: input_ids sequence: int32 - name: input_types sequence: int64 - name: loss_mask sequence: bool - name: patch_positions sequence: sequence: sequence: float64 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2654251456 num_examples: 2032 download_size: 140407266 dataset_size: 2654251456 - config_name: atari-fishingderby features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: local_positions sequence: int64 - name: input_ids sequence: int32 - name: input_types sequence: int64 - name: loss_mask sequence: bool - name: patch_positions sequence: sequence: sequence: float64 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2865449308 num_examples: 2177 download_size: 236590614 dataset_size: 2865449308 - config_name: atari-freeway features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: local_positions sequence: int64 - name: input_ids sequence: int32 - name: input_types sequence: int64 - name: loss_mask sequence: bool - name: patch_positions sequence: sequence: sequence: float64 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2646386200 num_examples: 2002 download_size: 182728240 dataset_size: 2646386200 - config_name: atari-frostbite features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: loss_mask sequence: bool - name: input_ids sequence: int32 - name: input_types sequence: int64 - name: local_positions sequence: int64 - name: attention_mask sequence: bool splits: - name: train num_bytes: 23145553316 num_examples: 17551 - name: test num_bytes: 2683086716 num_examples: 2033 download_size: 1661407235 dataset_size: 25828640032 - config_name: atari-gravitar features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: loss_mask sequence: bool - name: input_ids sequence: int32 - name: input_types sequence: int64 - name: local_positions sequence: int64 - name: attention_mask sequence: bool splits: - name: train num_bytes: 26186279752 num_examples: 20126 - name: test num_bytes: 2990268724 num_examples: 2299 download_size: 939142901 dataset_size: 29176548476 - config_name: atari-hero features: - name: input_ids sequence: int32 - name: loss_mask sequence: bool - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: input_types sequence: int64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2756503068 num_examples: 2089 download_size: 131026317 dataset_size: 2756503068 - config_name: atari-icehockey features: - name: patch_positions sequence: sequence: sequence: float64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: loss_mask sequence: bool - name: attention_mask sequence: bool splits: - name: test num_bytes: 2538945980 num_examples: 1921 download_size: 89405392 dataset_size: 2538945980 - config_name: atari-jamesbond features: - name: patch_positions sequence: sequence: sequence: float64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: loss_mask sequence: bool - name: attention_mask sequence: bool splits: - name: test num_bytes: 4473778328 num_examples: 3378 download_size: 224917482 dataset_size: 4473778328 - config_name: atari-kangaroo features: - name: patch_positions sequence: sequence: sequence: float64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: loss_mask sequence: bool - name: attention_mask sequence: bool splits: - name: test num_bytes: 2993217516 num_examples: 2285 download_size: 140119408 dataset_size: 2993217516 - config_name: atari-mspacman features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: loss_mask sequence: bool - name: input_types sequence: int64 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2479651844 num_examples: 1879 download_size: 217259145 dataset_size: 2479651844 - config_name: atari-namethisgame features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: loss_mask sequence: bool - name: input_types sequence: int64 - name: attention_mask sequence: bool splits: - name: test num_bytes: 3006648420 num_examples: 2271 download_size: 158870157 dataset_size: 3006648420 - config_name: atari-phoenix features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: loss_mask sequence: bool - name: input_types sequence: int64 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2655773200 num_examples: 2004 download_size: 79861580 dataset_size: 2655773200 - config_name: atari-qbert features: - name: patch_positions sequence: sequence: sequence: float64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: input_types sequence: int64 - name: loss_mask sequence: bool - name: local_positions sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2547887868 num_examples: 1929 download_size: 174392419 dataset_size: 2547887868 - config_name: atari-riverraid features: - name: patch_positions sequence: sequence: sequence: float64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: input_types sequence: int64 - name: loss_mask sequence: bool - name: local_positions sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2555182372 num_examples: 1943 download_size: 174672084 dataset_size: 2555182372 - config_name: atari-roadrunner features: - name: patch_positions sequence: sequence: sequence: float64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: input_types sequence: int64 - name: loss_mask sequence: bool - name: local_positions sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2521407028 num_examples: 1915 download_size: 125390334 dataset_size: 2521407028 - config_name: atari-robotank features: - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: loss_mask sequence: bool - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: input_types sequence: int64 - name: attention_mask sequence: bool splits: - name: train num_bytes: 22475017052 num_examples: 16985 - name: test num_bytes: 2229677068 num_examples: 1685 download_size: 1298755118 dataset_size: 24704694120 - config_name: atari-seaquest features: - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: loss_mask sequence: bool - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: input_types sequence: int64 - name: attention_mask sequence: bool splits: - name: train num_bytes: 23841045496 num_examples: 18114 - name: test num_bytes: 2738008960 num_examples: 2080 download_size: 910338340 dataset_size: 26579054456 - config_name: atari-skiing features: - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: loss_mask sequence: bool - name: patches sequence: sequence: sequence: sequence: uint8 - name: patch_positions sequence: sequence: sequence: float64 - name: input_types sequence: int64 - name: attention_mask sequence: bool splits: - name: train num_bytes: 26305597476 num_examples: 20359 - name: test num_bytes: 2941523916 num_examples: 2277 download_size: 1797518108 dataset_size: 29247121392 - config_name: atari-solaris features: - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: patches sequence: sequence: sequence: sequence: uint8 - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: loss_mask sequence: bool - name: attention_mask sequence: bool splits: - name: test num_bytes: 2273188716 num_examples: 1717 download_size: 126936781 dataset_size: 2273188716 - config_name: atari-spaceinvaders features: - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: patches sequence: sequence: sequence: sequence: uint8 - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: loss_mask sequence: bool - name: attention_mask sequence: bool splits: - name: test num_bytes: 4137369016 num_examples: 3122 download_size: 146426375 dataset_size: 4137369016 - config_name: atari-stargunner features: - name: input_types sequence: int64 - name: input_ids sequence: int32 - name: patches sequence: sequence: sequence: sequence: uint8 - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: loss_mask sequence: bool - name: attention_mask sequence: bool splits: - name: test num_bytes: 2565341980 num_examples: 1937 download_size: 72577790 dataset_size: 2565341980 - config_name: atari-surround features: - name: loss_mask sequence: bool - name: local_positions sequence: int64 - name: input_types sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: input_ids sequence: int32 - name: patches sequence: sequence: sequence: sequence: uint8 - name: attention_mask sequence: bool splits: - name: train num_bytes: 22468793380 num_examples: 17023 - name: test num_bytes: 2933488488 num_examples: 2222 download_size: 904796125 dataset_size: 25402281868 - config_name: atari-tennis features: - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: loss_mask sequence: bool - name: input_types sequence: int64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2484015692 num_examples: 1877 download_size: 95167453 dataset_size: 2484015692 - config_name: atari-timepilot features: - name: input_ids sequence: int32 - name: local_positions sequence: int64 - name: patch_positions sequence: sequence: sequence: float64 - name: loss_mask sequence: bool - name: input_types sequence: int64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: attention_mask sequence: bool splits: - name: test num_bytes: 2558172240 num_examples: 1932 download_size: 86471773 dataset_size: 2558172240 - config_name: atari-tutankham features: - name: patches sequence: sequence: sequence: sequence: uint8 - name: local_positions sequence: int64 - name: input_types sequence: int64 - name: loss_mask sequence: bool - name: input_ids sequence: int32 - name: patch_positions sequence: sequence: sequence: float64 - name: attention_mask sequence: bool splits: - name: test num_bytes: 3517105220 num_examples: 2655 download_size: 144491974 dataset_size: 3517105220 - config_name: atari-videopinball features: - name: patch_positions sequence: sequence: sequence: float64 - name: input_types sequence: int64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: local_positions sequence: int64 - name: loss_mask sequence: bool - name: input_ids sequence: int32 - name: attention_mask sequence: bool splits: - name: train num_bytes: 22581644248 num_examples: 17042 - name: test num_bytes: 856644644 num_examples: 647 download_size: 1483962740 dataset_size: 23438288892 - config_name: atari-wizardofwor features: - name: patch_positions sequence: sequence: sequence: float64 - name: input_types sequence: int64 - name: patches sequence: sequence: sequence: sequence: uint8 - name: local_positions sequence: int64 - name: loss_mask sequence: bool - name: input_ids sequence: int32 - name: attention_mask sequence: bool splits: - name: train num_bytes: 22744043928 num_examples: 17218 - name: test num_bytes: 2648734220 num_examples: 2005 download_size: 1739703310 dataset_size: 25392778148 - config_name: atari-yarsrevenge features: - name: input_types sequence: int64 - name: loss_mask sequence: bool - name: patch_positions sequence: sequence: sequence: float64 - name: local_positions sequence: int64 - name: input_ids sequence: int32 - name: patches sequence: sequence: sequence: sequence: uint8 - name: attention_mask sequence: bool splits: - name: train num_bytes: 22080700236 num_examples: 16669 - name: test num_bytes: 2579104820 num_examples: 1947 download_size: 3451148232 dataset_size: 24659805056 - config_name: atari-zaxxon features: - name: input_types sequence: int64 - name: loss_mask sequence: bool - name: patch_positions sequence: sequence: sequence: float64 - name: local_positions sequence: int64 - name: input_ids sequence: int32 - name: patches sequence: sequence: sequence: sequence: uint8 - name: attention_mask sequence: bool splits: - name: train num_bytes: 22058040148 num_examples: 16667 - name: test num_bytes: 2768806832 num_examples: 2092 download_size: 1229966010 dataset_size: 24826846980 configs: - config_name: atari-alien data_files: - split: test path: atari-alien/test-* - config_name: atari-amidar data_files: - split: train path: atari-amidar/train-* - split: test path: atari-amidar/test-* - config_name: atari-assault data_files: - split: train path: atari-assault/train-* - split: test path: atari-assault/test-* - config_name: atari-asterix data_files: - split: train path: atari-asterix/train-* - config_name: atari-asteroids data_files: - split: train path: atari-asteroids/train-* - config_name: atari-atlantis data_files: - split: train path: atari-atlantis/train-* - config_name: atari-bankheist data_files: - split: train path: atari-bankheist/train-* - split: test path: atari-bankheist/test-* - config_name: atari-battlezone data_files: - split: test path: atari-battlezone/test-* - config_name: atari-berzerk data_files: - split: test path: atari-berzerk/test-* - config_name: atari-bowling data_files: - split: test path: atari-bowling/test-* - config_name: atari-boxing data_files: - split: test path: atari-boxing/test-* - config_name: atari-breakout data_files: - split: train path: atari-breakout/train-* - split: test path: atari-breakout/test-* - config_name: atari-centipede data_files: - split: train path: atari-centipede/train-* - split: test path: atari-centipede/test-* - config_name: atari-choppercommand data_files: - split: train path: atari-choppercommand/train-* - split: test path: atari-choppercommand/test-* - config_name: atari-crazyclimber data_files: - split: test path: atari-crazyclimber/test-* - config_name: atari-defender data_files: - split: test path: atari-defender/test-* - config_name: atari-demonattack data_files: - split: test path: atari-demonattack/test-* - config_name: atari-doubledunk data_files: - split: test path: atari-doubledunk/test-* - config_name: atari-fishingderby data_files: - split: test path: atari-fishingderby/test-* - config_name: atari-freeway data_files: - split: test path: atari-freeway/test-* - config_name: atari-frostbite data_files: - split: train path: atari-frostbite/train-* - split: test path: atari-frostbite/test-* - config_name: atari-gravitar data_files: - split: train path: atari-gravitar/train-* - split: test path: atari-gravitar/test-* - config_name: atari-hero data_files: - split: test path: atari-hero/test-* - config_name: atari-icehockey data_files: - split: test path: atari-icehockey/test-* - config_name: atari-jamesbond data_files: - split: test path: atari-jamesbond/test-* - config_name: atari-kangaroo data_files: - split: test path: atari-kangaroo/test-* - config_name: atari-mspacman data_files: - split: test path: atari-mspacman/test-* - config_name: atari-namethisgame data_files: - split: test path: atari-namethisgame/test-* - config_name: atari-phoenix data_files: - split: test path: atari-phoenix/test-* - config_name: atari-qbert data_files: - split: test path: atari-qbert/test-* - config_name: atari-riverraid data_files: - split: test path: atari-riverraid/test-* - config_name: atari-roadrunner data_files: - split: test path: atari-roadrunner/test-* - config_name: atari-robotank data_files: - split: train path: atari-robotank/train-* - split: test path: atari-robotank/test-* - config_name: atari-seaquest data_files: - split: train path: atari-seaquest/train-* - split: test path: atari-seaquest/test-* - config_name: atari-skiing data_files: - split: train path: atari-skiing/train-* - split: test path: atari-skiing/test-* - config_name: atari-solaris data_files: - split: test path: atari-solaris/test-* - config_name: atari-spaceinvaders data_files: - split: test path: atari-spaceinvaders/test-* - config_name: atari-stargunner data_files: - split: test path: atari-stargunner/test-* - config_name: atari-surround data_files: - split: train path: atari-surround/train-* - split: test path: atari-surround/test-* - config_name: atari-tennis data_files: - split: test path: atari-tennis/test-* - config_name: atari-timepilot data_files: - split: test path: atari-timepilot/test-* - config_name: atari-tutankham data_files: - split: test path: atari-tutankham/test-* - config_name: atari-videopinball data_files: - split: train path: atari-videopinball/train-* - split: test path: atari-videopinball/test-* - config_name: atari-wizardofwor data_files: - split: train path: atari-wizardofwor/train-* - split: test path: atari-wizardofwor/test-* - config_name: atari-yarsrevenge data_files: - split: train path: atari-yarsrevenge/train-* - split: test path: atari-yarsrevenge/test-* - config_name: atari-zaxxon data_files: - split: train path: atari-zaxxon/train-* - split: test path: atari-zaxxon/test-* --- # Dataset Card for "gia-dataset-tokenized-2024-2" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CyberHarem/matsuo_chizuru_idolmastercinderellagirls
2023-09-17T17:38:51.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of matsuo_chizuru (THE iDOLM@STER: Cinderella Girls) This is the dataset of matsuo_chizuru (THE iDOLM@STER: Cinderella Girls), containing 87 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 87 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 223 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 87 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 87 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 87 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 87 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 87 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 223 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 223 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 223 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
aboix/q76_campnow_downsampled_noduplicates_upsampled_deletedtest
2023-09-15T08:15:45.000Z
[ "region:us" ]
aboix
null
null
null
0
0
Entry not found
CyberHarem/mizuki_seira_idolmastercinderellagirls
2023-09-17T17:38:53.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of mizuki_seira (THE iDOLM@STER: Cinderella Girls) This is the dataset of mizuki_seira (THE iDOLM@STER: Cinderella Girls), containing 164 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 164 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 441 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 164 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 164 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 164 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 164 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 164 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 441 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 441 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 441 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
BSC-LT/aguila7b-private-inference
2023-09-21T09:19:55.000Z
[ "region:us" ]
BSC-LT
null
null
null
0
0
# Aguila7b Private Inference ## Dataset Description - **Homepage:** - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary [More Information Needed] ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]
cestwc/sample
2023-09-15T08:50:44.000Z
[ "region:us" ]
cestwc
null
null
null
0
0
--- dataset_info: features: - name: Unique Case Record Key dtype: int64 - name: Description dtype: string - name: Subject dtype: string - name: Reporting Sub Category dtype: class_label: names: '0': CRC Issues '1': Pedestrian Paths/POB/Linkway - Requests '2': Parks Infra - Others '3': Cockroaches '4': EPS Malfunction '5': Illegal Parking - Public Housing Disabled Lots '6': Abandoned Bulky Items/Dumping '7': Idling Engines '8': Illegal Parking - Public Housing General Reserved Lots '9': Noise - Events '10': Illegal Activities - Others '11': Hoarding '12': Tree Removal '13': Public Housing Infra - Others '14': Rodents '15': Playground/Fitness Equipment - Public Housing '16': Grass Cutting '17': Public Toilet Issues '18': Hazardous Toxic '19': Water Supply and Pressure - Other Public Areas '20': Smell/Smoky - Food Establishments/Cooking '21': Illegal Parking - Roads '22': Illegal Parking - Public Housing Loading and Unloading Bays '23': Water - Others '24': Graffiti/Stains '25': Obstruction of Public Accessibility by Articles '26': PMDs/PABs/Bicycles Usage Issues '27': Dust/Smell/Light - Construction '28': BCA - Building and Construction Matters '29': Flooding/Ponding '30': Smell - Drains/Canals/Sewer/Manhole '31': Noise - Food Establishments/Entertainment Outlets '32': Bus Shelters - Maintenance '33': CCTV Issues '34': Neighbour Disputes '35': Dogs - Nuisance '36': Dust - Others '37': Electricity Supply '38': Obstruction - Public Housing Common Areas '39': Pollution - Others '40': Noise - Others '41': Noise - Renovation '42': Water Pipe Maintenance and Issues - Public Housing '43': Tree Planting '44': Car Park - Maintenance '45': Roads/Structures - Maintenance '46': Street Lights - Maintenance '47': Dirty Areas/Litter - Other Public Areas '48': Illegal Advertisements '49': High Rise Littering/Killer Litter '50': Lift - Others '51': Birds - Nuisance '52': Ceiling Leak '53': Animals - Others '54': Traffic Lights - Maintenance '55': Connectivity Related Infrastructure - Others '56': Illegal Parking - Motorcycles at Public Housing Common Areas '57': Pedestrian Crossings '58': Electrical - Others '59': Cats - Nuisance '60': Noise - Construction '61': Sewer - Other Public Areas '62': Spalling Concrete - Public Housing Common Areas '63': Wall Seepage '64': Urine/Faeces/Spitting '65': Sewer - Public Housing '66': Noise - Neighbours '67': Bees/Wasps/Hornets '68': Lift - Breakdown '69': Dead Animals/Birds '70': Tree/Shrub Maintenance '71': Corridor Lighting '72': Bus Shelters - Requests '73': Car Park - Requests '74': Drains/Drainage - Public Housing '75': Spalling Concrete - Within HDB Flat '76': Dirty Areas/Litter - Public Housing '77': Water Pipe Maintenance and Issues - Other Public Areas '78': Traffic Lights - Requests '79': Waste Pipe Defects - Public Housing '80': Waste and Recycling Management '81': Fallen Tree/Branch '82': Infra - Others '83': Building Defects '84': Wet Laundry '85': Illegal Parking - Heavy Vehicle Parking at Public Housing '86': Outdoor Lighting '87': Dirty Drains/Canals '88': Pedestrian Paths/POB/Linkway - Maintenance '89': Noise - Congregation in Common Areas '90': Smoking '91': Bins/Recycling '92': Road Works '93': Illegal Parking - Serious Obstruction '94': Smell - Other Sources '95': Pests - Others '96': Road Signs - Maintenance '97': Water Quality - Other Public Areas '98': Air Pollution/Smoke '99': Drains/Drainage - Other Public Areas '100': Illegal Parking - Public Housing Car Parks/Service Roads '101': Mosquitoes '102': Water Supply and Pressure - Public Housing '103': Parks Infra - Lighting - name: Reporting Category dtype: class_label: names: '0': Cleanliness '1': Enforcement Matters '2': Pests '3': Pollution '4': General Infrastructure/Facilities '5': Public Housing Lifts '6': Connectivity Related Infrastructure '7': Animals and Birds '8': Public Housing Infrastructure (Excl Lifts) '9': Greenery '10': Neighbour Issues '11': Illegal Parking '12': Noise - name: Preprocessed dtype: string - name: input_ids sequence: int32 - name: token_type_ids sequence: int8 - name: attention_mask sequence: int8 - name: labels dtype: int64 - name: tags sequence: sequence: float64 splits: - name: '2017' num_bytes: 33338600 num_examples: 45675 download_size: 16008523 dataset_size: 33338600 configs: - config_name: default data_files: - split: '2017' path: data/2017-* --- # Dataset Card for "sample" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
AnthonyRayo/TestforDocumentation
2023-09-15T08:52:08.000Z
[ "region:us" ]
AnthonyRayo
null
null
null
0
0
Entry not found
CyberHarem/kita_hinako_idolmastercinderellagirls
2023-09-17T17:38:55.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of kita_hinako (THE iDOLM@STER: Cinderella Girls) This is the dataset of kita_hinako (THE iDOLM@STER: Cinderella Girls), containing 71 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 71 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 193 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 71 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 71 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 71 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 71 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 71 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 193 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 193 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 193 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/fukuyama_mai_idolmastercinderellagirls
2023-09-17T17:38:57.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of fukuyama_mai (THE iDOLM@STER: Cinderella Girls) This is the dataset of fukuyama_mai (THE iDOLM@STER: Cinderella Girls), containing 137 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 137 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 381 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 137 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 137 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 137 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 137 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 137 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 381 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 381 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 381 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
sorimanse/Sori
2023-09-15T09:26:38.000Z
[ "region:us" ]
sorimanse
null
null
null
0
0
Entry not found
open-llm-leaderboard/details_lloorree__jfdslijsijdgis
2023-09-17T00:36:07.000Z
[ "region:us" ]
open-llm-leaderboard
null
null
null
0
0
--- pretty_name: Evaluation run of lloorree/jfdslijsijdgis dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [lloorree/jfdslijsijdgis](https://huggingface.co/lloorree/jfdslijsijdgis) on the\ \ [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 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_lloorree__jfdslijsijdgis\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-17T00:34:49.304226](https://huggingface.co/datasets/open-llm-leaderboard/details_lloorree__jfdslijsijdgis/blob/main/results_2023-09-17T00-34-49.304226.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\": 0.6907933129316588,\n\ \ \"acc_stderr\": 0.03107455661224763,\n \"acc_norm\": 0.694824769775718,\n\ \ \"acc_norm_stderr\": 0.031044197474221744,\n \"mc1\": 0.41615667074663404,\n\ \ \"mc1_stderr\": 0.017255657502903043,\n \"mc2\": 0.5820460749080146,\n\ \ \"mc2_stderr\": 0.015030523772190541\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6518771331058021,\n \"acc_stderr\": 0.01392100859517935,\n\ \ \"acc_norm\": 0.6962457337883959,\n \"acc_norm_stderr\": 0.013438909184778764\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6760605457080263,\n\ \ \"acc_stderr\": 0.00467020812857923,\n \"acc_norm\": 0.8695478988249352,\n\ \ \"acc_norm_stderr\": 0.0033611183954523846\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621505,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621505\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6296296296296297,\n\ \ \"acc_stderr\": 0.04171654161354543,\n \"acc_norm\": 0.6296296296296297,\n\ \ \"acc_norm_stderr\": 0.04171654161354543\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.8223684210526315,\n \"acc_stderr\": 0.03110318238312338,\n\ \ \"acc_norm\": 0.8223684210526315,\n \"acc_norm_stderr\": 0.03110318238312338\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.74,\n\ \ \"acc_stderr\": 0.0440844002276808,\n \"acc_norm\": 0.74,\n \ \ \"acc_norm_stderr\": 0.0440844002276808\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.7132075471698113,\n \"acc_stderr\": 0.02783491252754407,\n\ \ \"acc_norm\": 0.7132075471698113,\n \"acc_norm_stderr\": 0.02783491252754407\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8125,\n\ \ \"acc_stderr\": 0.032639560491693344,\n \"acc_norm\": 0.8125,\n\ \ \"acc_norm_stderr\": 0.032639560491693344\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \ \ \"acc_norm\": 0.5,\n \"acc_norm_stderr\": 0.050251890762960605\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.54,\n \"acc_stderr\": 0.05009082659620332,\n \"acc_norm\": 0.54,\n\ \ \"acc_norm_stderr\": 0.05009082659620332\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.048783173121456316,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.048783173121456316\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6705202312138728,\n\ \ \"acc_stderr\": 0.03583901754736413,\n \"acc_norm\": 0.6705202312138728,\n\ \ \"acc_norm_stderr\": 0.03583901754736413\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.38235294117647056,\n \"acc_stderr\": 0.04835503696107223,\n\ \ \"acc_norm\": 0.38235294117647056,\n \"acc_norm_stderr\": 0.04835503696107223\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.78,\n \"acc_stderr\": 0.041633319989322626,\n \"acc_norm\": 0.78,\n\ \ \"acc_norm_stderr\": 0.041633319989322626\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.6638297872340425,\n \"acc_stderr\": 0.030881618520676942,\n\ \ \"acc_norm\": 0.6638297872340425,\n \"acc_norm_stderr\": 0.030881618520676942\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.43859649122807015,\n\ \ \"acc_stderr\": 0.04668000738510455,\n \"acc_norm\": 0.43859649122807015,\n\ \ \"acc_norm_stderr\": 0.04668000738510455\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.6206896551724138,\n \"acc_stderr\": 0.040434618619167466,\n\ \ \"acc_norm\": 0.6206896551724138,\n \"acc_norm_stderr\": 0.040434618619167466\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.4444444444444444,\n \"acc_stderr\": 0.025591857761382182,\n \"\ acc_norm\": 0.4444444444444444,\n \"acc_norm_stderr\": 0.025591857761382182\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4444444444444444,\n\ \ \"acc_stderr\": 0.04444444444444449,\n \"acc_norm\": 0.4444444444444444,\n\ \ \"acc_norm_stderr\": 0.04444444444444449\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.47,\n \"acc_stderr\": 0.05016135580465919,\n \ \ \"acc_norm\": 0.47,\n \"acc_norm_stderr\": 0.05016135580465919\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.8064516129032258,\n\ \ \"acc_stderr\": 0.022475258525536057,\n \"acc_norm\": 0.8064516129032258,\n\ \ \"acc_norm_stderr\": 0.022475258525536057\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.5221674876847291,\n \"acc_stderr\": 0.03514528562175008,\n\ \ \"acc_norm\": 0.5221674876847291,\n \"acc_norm_stderr\": 0.03514528562175008\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.77,\n \"acc_stderr\": 0.04229525846816506,\n \"acc_norm\"\ : 0.77,\n \"acc_norm_stderr\": 0.04229525846816506\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.8484848484848485,\n \"acc_stderr\": 0.027998073798781668,\n\ \ \"acc_norm\": 0.8484848484848485,\n \"acc_norm_stderr\": 0.027998073798781668\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.8636363636363636,\n \"acc_stderr\": 0.024450155973189835,\n \"\ acc_norm\": 0.8636363636363636,\n \"acc_norm_stderr\": 0.024450155973189835\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.9533678756476683,\n \"acc_stderr\": 0.015216761819262592,\n\ \ \"acc_norm\": 0.9533678756476683,\n \"acc_norm_stderr\": 0.015216761819262592\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.7153846153846154,\n \"acc_stderr\": 0.022878322799706304,\n\ \ \"acc_norm\": 0.7153846153846154,\n \"acc_norm_stderr\": 0.022878322799706304\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.28888888888888886,\n \"acc_stderr\": 0.027634907264178544,\n \ \ \"acc_norm\": 0.28888888888888886,\n \"acc_norm_stderr\": 0.027634907264178544\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.7815126050420168,\n \"acc_stderr\": 0.026841514322958934,\n\ \ \"acc_norm\": 0.7815126050420168,\n \"acc_norm_stderr\": 0.026841514322958934\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.423841059602649,\n \"acc_stderr\": 0.04034846678603397,\n \"acc_norm\"\ : 0.423841059602649,\n \"acc_norm_stderr\": 0.04034846678603397\n },\n\ \ \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\": 0.8935779816513761,\n\ \ \"acc_stderr\": 0.013221554674594372,\n \"acc_norm\": 0.8935779816513761,\n\ \ \"acc_norm_stderr\": 0.013221554674594372\n },\n \"harness|hendrycksTest-high_school_statistics|5\"\ : {\n \"acc\": 0.6018518518518519,\n \"acc_stderr\": 0.033384734032074016,\n\ \ \"acc_norm\": 0.6018518518518519,\n \"acc_norm_stderr\": 0.033384734032074016\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.9117647058823529,\n \"acc_stderr\": 0.01990739979131695,\n \"\ acc_norm\": 0.9117647058823529,\n \"acc_norm_stderr\": 0.01990739979131695\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8565400843881856,\n \"acc_stderr\": 0.022818291821017012,\n \ \ \"acc_norm\": 0.8565400843881856,\n \"acc_norm_stderr\": 0.022818291821017012\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7982062780269058,\n\ \ \"acc_stderr\": 0.026936111912802263,\n \"acc_norm\": 0.7982062780269058,\n\ \ \"acc_norm_stderr\": 0.026936111912802263\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.8473282442748091,\n \"acc_stderr\": 0.031545216720054725,\n\ \ \"acc_norm\": 0.8473282442748091,\n \"acc_norm_stderr\": 0.031545216720054725\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.859504132231405,\n \"acc_stderr\": 0.03172233426002158,\n \"acc_norm\"\ : 0.859504132231405,\n \"acc_norm_stderr\": 0.03172233426002158\n },\n\ \ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8425925925925926,\n\ \ \"acc_stderr\": 0.03520703990517964,\n \"acc_norm\": 0.8425925925925926,\n\ \ \"acc_norm_stderr\": 0.03520703990517964\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.8159509202453987,\n \"acc_stderr\": 0.030446777687971726,\n\ \ \"acc_norm\": 0.8159509202453987,\n \"acc_norm_stderr\": 0.030446777687971726\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.5357142857142857,\n\ \ \"acc_stderr\": 0.04733667890053756,\n \"acc_norm\": 0.5357142857142857,\n\ \ \"acc_norm_stderr\": 0.04733667890053756\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.8252427184466019,\n \"acc_stderr\": 0.0376017800602662,\n\ \ \"acc_norm\": 0.8252427184466019,\n \"acc_norm_stderr\": 0.0376017800602662\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8760683760683761,\n\ \ \"acc_stderr\": 0.02158649400128138,\n \"acc_norm\": 0.8760683760683761,\n\ \ \"acc_norm_stderr\": 0.02158649400128138\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.72,\n \"acc_stderr\": 0.04512608598542127,\n \ \ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.04512608598542127\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8659003831417624,\n\ \ \"acc_stderr\": 0.012185528166499978,\n \"acc_norm\": 0.8659003831417624,\n\ \ \"acc_norm_stderr\": 0.012185528166499978\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7658959537572254,\n \"acc_stderr\": 0.022797110278071124,\n\ \ \"acc_norm\": 0.7658959537572254,\n \"acc_norm_stderr\": 0.022797110278071124\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.511731843575419,\n\ \ \"acc_stderr\": 0.016717897676932162,\n \"acc_norm\": 0.511731843575419,\n\ \ \"acc_norm_stderr\": 0.016717897676932162\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\": 0.7845659163987139,\n\ \ \"acc_stderr\": 0.023350225475471442,\n \"acc_norm\": 0.7845659163987139,\n\ \ \"acc_norm_stderr\": 0.023350225475471442\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.8240740740740741,\n \"acc_stderr\": 0.021185893615225188,\n\ \ \"acc_norm\": 0.8240740740740741,\n \"acc_norm_stderr\": 0.021185893615225188\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.5177304964539007,\n \"acc_stderr\": 0.02980873964223777,\n \ \ \"acc_norm\": 0.5177304964539007,\n \"acc_norm_stderr\": 0.02980873964223777\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.5397653194263363,\n\ \ \"acc_stderr\": 0.012729785386598545,\n \"acc_norm\": 0.5397653194263363,\n\ \ \"acc_norm_stderr\": 0.012729785386598545\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.7169117647058824,\n \"acc_stderr\": 0.02736586113151381,\n\ \ \"acc_norm\": 0.7169117647058824,\n \"acc_norm_stderr\": 0.02736586113151381\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.75,\n \"acc_stderr\": 0.01751781884501444,\n \"acc_norm\"\ : 0.75,\n \"acc_norm_stderr\": 0.01751781884501444\n },\n \"harness|hendrycksTest-public_relations|5\"\ : {\n \"acc\": 0.6909090909090909,\n \"acc_stderr\": 0.044262946482000985,\n\ \ \"acc_norm\": 0.6909090909090909,\n \"acc_norm_stderr\": 0.044262946482000985\n\ \ },\n \"harness|hendrycksTest-security_studies|5\": {\n \"acc\": 0.8122448979591836,\n\ \ \"acc_stderr\": 0.025000256039546195,\n \"acc_norm\": 0.8122448979591836,\n\ \ \"acc_norm_stderr\": 0.025000256039546195\n },\n \"harness|hendrycksTest-sociology|5\"\ : {\n \"acc\": 0.900497512437811,\n \"acc_stderr\": 0.0211662163046594,\n\ \ \"acc_norm\": 0.900497512437811,\n \"acc_norm_stderr\": 0.0211662163046594\n\ \ },\n \"harness|hendrycksTest-us_foreign_policy|5\": {\n \"acc\":\ \ 0.89,\n \"acc_stderr\": 0.03144660377352203,\n \"acc_norm\": 0.89,\n\ \ \"acc_norm_stderr\": 0.03144660377352203\n },\n \"harness|hendrycksTest-virology|5\"\ : {\n \"acc\": 0.5180722891566265,\n \"acc_stderr\": 0.03889951252827216,\n\ \ \"acc_norm\": 0.5180722891566265,\n \"acc_norm_stderr\": 0.03889951252827216\n\ \ },\n \"harness|hendrycksTest-world_religions|5\": {\n \"acc\": 0.8713450292397661,\n\ \ \"acc_stderr\": 0.02567934272327692,\n \"acc_norm\": 0.8713450292397661,\n\ \ \"acc_norm_stderr\": 0.02567934272327692\n },\n \"harness|truthfulqa:mc|0\"\ : {\n \"mc1\": 0.41615667074663404,\n \"mc1_stderr\": 0.017255657502903043,\n\ \ \"mc2\": 0.5820460749080146,\n \"mc2_stderr\": 0.015030523772190541\n\ \ }\n}\n```" repo_url: https://huggingface.co/lloorree/jfdslijsijdgis 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_15T09_43_22.432852 path: - '**/details_harness|arc:challenge|25_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|arc:challenge|25_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hellaswag|10_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hellaswag|10_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-15T09-43-22.432852.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-17T00-34-49.304226.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-management|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-management|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-virology|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-virology|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-17T00-34-49.304226.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_15T09_43_22.432852 path: - '**/details_harness|truthfulqa:mc|0_2023-09-15T09-43-22.432852.parquet' - split: 2023_09_17T00_34_49.304226 path: - '**/details_harness|truthfulqa:mc|0_2023-09-17T00-34-49.304226.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-09-17T00-34-49.304226.parquet' - config_name: results data_files: - split: 2023_09_15T09_43_22.432852 path: - results_2023-09-15T09-43-22.432852.parquet - split: 2023_09_17T00_34_49.304226 path: - results_2023-09-17T00-34-49.304226.parquet - split: latest path: - results_2023-09-17T00-34-49.304226.parquet --- # Dataset Card for Evaluation run of lloorree/jfdslijsijdgis ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/lloorree/jfdslijsijdgis - **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 [lloorree/jfdslijsijdgis](https://huggingface.co/lloorree/jfdslijsijdgis) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 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_lloorree__jfdslijsijdgis", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-17T00:34:49.304226](https://huggingface.co/datasets/open-llm-leaderboard/details_lloorree__jfdslijsijdgis/blob/main/results_2023-09-17T00-34-49.304226.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": 0.6907933129316588, "acc_stderr": 0.03107455661224763, "acc_norm": 0.694824769775718, "acc_norm_stderr": 0.031044197474221744, "mc1": 0.41615667074663404, "mc1_stderr": 0.017255657502903043, "mc2": 0.5820460749080146, "mc2_stderr": 0.015030523772190541 }, "harness|arc:challenge|25": { "acc": 0.6518771331058021, "acc_stderr": 0.01392100859517935, "acc_norm": 0.6962457337883959, "acc_norm_stderr": 0.013438909184778764 }, "harness|hellaswag|10": { "acc": 0.6760605457080263, "acc_stderr": 0.00467020812857923, "acc_norm": 0.8695478988249352, "acc_norm_stderr": 0.0033611183954523846 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.32, "acc_stderr": 0.04688261722621505, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6296296296296297, "acc_stderr": 0.04171654161354543, "acc_norm": 0.6296296296296297, "acc_norm_stderr": 0.04171654161354543 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8223684210526315, "acc_stderr": 0.03110318238312338, "acc_norm": 0.8223684210526315, "acc_norm_stderr": 0.03110318238312338 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.74, "acc_stderr": 0.0440844002276808, "acc_norm": 0.74, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7132075471698113, "acc_stderr": 0.02783491252754407, "acc_norm": 0.7132075471698113, "acc_norm_stderr": 0.02783491252754407 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8125, "acc_stderr": 0.032639560491693344, "acc_norm": 0.8125, "acc_norm_stderr": 0.032639560491693344 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6705202312138728, "acc_stderr": 0.03583901754736413, "acc_norm": 0.6705202312138728, "acc_norm_stderr": 0.03583901754736413 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.38235294117647056, "acc_stderr": 0.04835503696107223, "acc_norm": 0.38235294117647056, "acc_norm_stderr": 0.04835503696107223 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.78, "acc_stderr": 0.041633319989322626, "acc_norm": 0.78, "acc_norm_stderr": 0.041633319989322626 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6638297872340425, "acc_stderr": 0.030881618520676942, "acc_norm": 0.6638297872340425, "acc_norm_stderr": 0.030881618520676942 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.43859649122807015, "acc_stderr": 0.04668000738510455, "acc_norm": 0.43859649122807015, "acc_norm_stderr": 0.04668000738510455 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6206896551724138, "acc_stderr": 0.040434618619167466, "acc_norm": 0.6206896551724138, "acc_norm_stderr": 0.040434618619167466 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4444444444444444, "acc_stderr": 0.025591857761382182, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.025591857761382182 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4444444444444444, "acc_stderr": 0.04444444444444449, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.04444444444444449 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8064516129032258, "acc_stderr": 0.022475258525536057, "acc_norm": 0.8064516129032258, "acc_norm_stderr": 0.022475258525536057 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5221674876847291, "acc_stderr": 0.03514528562175008, "acc_norm": 0.5221674876847291, "acc_norm_stderr": 0.03514528562175008 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.77, "acc_stderr": 0.04229525846816506, "acc_norm": 0.77, "acc_norm_stderr": 0.04229525846816506 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8484848484848485, "acc_stderr": 0.027998073798781668, "acc_norm": 0.8484848484848485, "acc_norm_stderr": 0.027998073798781668 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8636363636363636, "acc_stderr": 0.024450155973189835, "acc_norm": 0.8636363636363636, "acc_norm_stderr": 0.024450155973189835 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9533678756476683, "acc_stderr": 0.015216761819262592, "acc_norm": 0.9533678756476683, "acc_norm_stderr": 0.015216761819262592 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7153846153846154, "acc_stderr": 0.022878322799706304, "acc_norm": 0.7153846153846154, "acc_norm_stderr": 0.022878322799706304 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.28888888888888886, "acc_stderr": 0.027634907264178544, "acc_norm": 0.28888888888888886, "acc_norm_stderr": 0.027634907264178544 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.7815126050420168, "acc_stderr": 0.026841514322958934, "acc_norm": 0.7815126050420168, "acc_norm_stderr": 0.026841514322958934 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.423841059602649, "acc_stderr": 0.04034846678603397, "acc_norm": 0.423841059602649, "acc_norm_stderr": 0.04034846678603397 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8935779816513761, "acc_stderr": 0.013221554674594372, "acc_norm": 0.8935779816513761, "acc_norm_stderr": 0.013221554674594372 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.6018518518518519, "acc_stderr": 0.033384734032074016, "acc_norm": 0.6018518518518519, "acc_norm_stderr": 0.033384734032074016 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.9117647058823529, "acc_stderr": 0.01990739979131695, "acc_norm": 0.9117647058823529, "acc_norm_stderr": 0.01990739979131695 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8565400843881856, "acc_stderr": 0.022818291821017012, "acc_norm": 0.8565400843881856, "acc_norm_stderr": 0.022818291821017012 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.7982062780269058, "acc_stderr": 0.026936111912802263, "acc_norm": 0.7982062780269058, "acc_norm_stderr": 0.026936111912802263 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.8473282442748091, "acc_stderr": 0.031545216720054725, "acc_norm": 0.8473282442748091, "acc_norm_stderr": 0.031545216720054725 }, "harness|hendrycksTest-international_law|5": { "acc": 0.859504132231405, "acc_stderr": 0.03172233426002158, "acc_norm": 0.859504132231405, "acc_norm_stderr": 0.03172233426002158 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.8425925925925926, "acc_stderr": 0.03520703990517964, "acc_norm": 0.8425925925925926, "acc_norm_stderr": 0.03520703990517964 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.8159509202453987, "acc_stderr": 0.030446777687971726, "acc_norm": 0.8159509202453987, "acc_norm_stderr": 0.030446777687971726 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.5357142857142857, "acc_stderr": 0.04733667890053756, "acc_norm": 0.5357142857142857, "acc_norm_stderr": 0.04733667890053756 }, "harness|hendrycksTest-management|5": { "acc": 0.8252427184466019, "acc_stderr": 0.0376017800602662, "acc_norm": 0.8252427184466019, "acc_norm_stderr": 0.0376017800602662 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8760683760683761, "acc_stderr": 0.02158649400128138, "acc_norm": 0.8760683760683761, "acc_norm_stderr": 0.02158649400128138 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.72, "acc_stderr": 0.04512608598542127, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542127 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8659003831417624, "acc_stderr": 0.012185528166499978, "acc_norm": 0.8659003831417624, "acc_norm_stderr": 0.012185528166499978 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7658959537572254, "acc_stderr": 0.022797110278071124, "acc_norm": 0.7658959537572254, "acc_norm_stderr": 0.022797110278071124 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.511731843575419, "acc_stderr": 0.016717897676932162, "acc_norm": 0.511731843575419, "acc_norm_stderr": 0.016717897676932162 }, "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": 0.7845659163987139, "acc_stderr": 0.023350225475471442, "acc_norm": 0.7845659163987139, "acc_norm_stderr": 0.023350225475471442 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.8240740740740741, "acc_stderr": 0.021185893615225188, "acc_norm": 0.8240740740740741, "acc_norm_stderr": 0.021185893615225188 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.5177304964539007, "acc_stderr": 0.02980873964223777, "acc_norm": 0.5177304964539007, "acc_norm_stderr": 0.02980873964223777 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.5397653194263363, "acc_stderr": 0.012729785386598545, "acc_norm": 0.5397653194263363, "acc_norm_stderr": 0.012729785386598545 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.7169117647058824, "acc_stderr": 0.02736586113151381, "acc_norm": 0.7169117647058824, "acc_norm_stderr": 0.02736586113151381 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.75, "acc_stderr": 0.01751781884501444, "acc_norm": 0.75, "acc_norm_stderr": 0.01751781884501444 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6909090909090909, "acc_stderr": 0.044262946482000985, "acc_norm": 0.6909090909090909, "acc_norm_stderr": 0.044262946482000985 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.8122448979591836, "acc_stderr": 0.025000256039546195, "acc_norm": 0.8122448979591836, "acc_norm_stderr": 0.025000256039546195 }, "harness|hendrycksTest-sociology|5": { "acc": 0.900497512437811, "acc_stderr": 0.0211662163046594, "acc_norm": 0.900497512437811, "acc_norm_stderr": 0.0211662163046594 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.89, "acc_stderr": 0.03144660377352203, "acc_norm": 0.89, "acc_norm_stderr": 0.03144660377352203 }, "harness|hendrycksTest-virology|5": { "acc": 0.5180722891566265, "acc_stderr": 0.03889951252827216, "acc_norm": 0.5180722891566265, "acc_norm_stderr": 0.03889951252827216 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8713450292397661, "acc_stderr": 0.02567934272327692, "acc_norm": 0.8713450292397661, "acc_norm_stderr": 0.02567934272327692 }, "harness|truthfulqa:mc|0": { "mc1": 0.41615667074663404, "mc1_stderr": 0.017255657502903043, "mc2": 0.5820460749080146, "mc2_stderr": 0.015030523772190541 } } ``` ### 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]
CyberHarem/koga_koharu_idolmastercinderellagirls
2023-09-17T17:38:59.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of koga_koharu (THE iDOLM@STER: Cinderella Girls) This is the dataset of koga_koharu (THE iDOLM@STER: Cinderella Girls), containing 82 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 82 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 203 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 82 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 82 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 82 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 82 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 82 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 203 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 203 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 203 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
qgyd2021/music_comment
2023-09-19T03:34:24.000Z
[ "size_categories:100M<n<1B", "language:zh", "license:apache-2.0", "music", "region:us" ]
qgyd2021
null
@dataset{music_comment, author = {Xing Tian}, title = {music_comment}, month = sep, year = 2023, publisher = {Xing Tian}, version = {1.0}, }
null
0
0
--- license: apache-2.0 language: - zh tags: - music size_categories: - 100M<n<1B --- ## 49万港台内地歌曲信息 数据来源于 [QQMusicSpider](https://github.com/yangjianxin1/QQMusicSpider). 数据可用于: * 根据歌手创作歌词. * 根据歌名创作歌词. * 根据歌名写评论.
BangumiBase/kumakumakumabear
2023-09-29T08:08:18.000Z
[ "size_categories:1K<n<10K", "license:mit", "art", "region:us" ]
BangumiBase
null
null
null
0
0
--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Kuma Kuma Kuma Bear This is the image base of bangumi Kuma Kuma Kuma Bear, we detected 99 characters, 6688 images in total. The full dataset is [here](all.zip). **Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: | # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 | |:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------| | 0 | 801 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 135 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 55 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 78 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 22 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 45 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 26 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 17 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 40 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 47 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 25 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 24 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 14 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 21 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 16 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 19 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 128 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 20 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 22 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | 19 | 58 | [Download](19/dataset.zip) | ![preview 1](19/preview_1.png) | ![preview 2](19/preview_2.png) | ![preview 3](19/preview_3.png) | ![preview 4](19/preview_4.png) | ![preview 5](19/preview_5.png) | ![preview 6](19/preview_6.png) | ![preview 7](19/preview_7.png) | ![preview 8](19/preview_8.png) | | 20 | 12 | [Download](20/dataset.zip) | ![preview 1](20/preview_1.png) | ![preview 2](20/preview_2.png) | ![preview 3](20/preview_3.png) | ![preview 4](20/preview_4.png) | ![preview 5](20/preview_5.png) | ![preview 6](20/preview_6.png) | ![preview 7](20/preview_7.png) | ![preview 8](20/preview_8.png) | | 21 | 180 | [Download](21/dataset.zip) | ![preview 1](21/preview_1.png) | ![preview 2](21/preview_2.png) | ![preview 3](21/preview_3.png) | ![preview 4](21/preview_4.png) | ![preview 5](21/preview_5.png) | ![preview 6](21/preview_6.png) | ![preview 7](21/preview_7.png) | ![preview 8](21/preview_8.png) | | 22 | 15 | [Download](22/dataset.zip) | ![preview 1](22/preview_1.png) | ![preview 2](22/preview_2.png) | ![preview 3](22/preview_3.png) | ![preview 4](22/preview_4.png) | ![preview 5](22/preview_5.png) | ![preview 6](22/preview_6.png) | ![preview 7](22/preview_7.png) | ![preview 8](22/preview_8.png) | | 23 | 14 | [Download](23/dataset.zip) | ![preview 1](23/preview_1.png) | ![preview 2](23/preview_2.png) | ![preview 3](23/preview_3.png) | ![preview 4](23/preview_4.png) | ![preview 5](23/preview_5.png) | ![preview 6](23/preview_6.png) | ![preview 7](23/preview_7.png) | ![preview 8](23/preview_8.png) | | 24 | 49 | [Download](24/dataset.zip) | ![preview 1](24/preview_1.png) | ![preview 2](24/preview_2.png) | ![preview 3](24/preview_3.png) | ![preview 4](24/preview_4.png) | ![preview 5](24/preview_5.png) | ![preview 6](24/preview_6.png) | ![preview 7](24/preview_7.png) | ![preview 8](24/preview_8.png) | | 25 | 13 | [Download](25/dataset.zip) | ![preview 1](25/preview_1.png) | ![preview 2](25/preview_2.png) | ![preview 3](25/preview_3.png) | ![preview 4](25/preview_4.png) | ![preview 5](25/preview_5.png) | ![preview 6](25/preview_6.png) | ![preview 7](25/preview_7.png) | ![preview 8](25/preview_8.png) | | 26 | 60 | [Download](26/dataset.zip) | ![preview 1](26/preview_1.png) | ![preview 2](26/preview_2.png) | ![preview 3](26/preview_3.png) | ![preview 4](26/preview_4.png) | ![preview 5](26/preview_5.png) | ![preview 6](26/preview_6.png) | ![preview 7](26/preview_7.png) | ![preview 8](26/preview_8.png) | | 27 | 15 | [Download](27/dataset.zip) | ![preview 1](27/preview_1.png) | ![preview 2](27/preview_2.png) | ![preview 3](27/preview_3.png) | ![preview 4](27/preview_4.png) | ![preview 5](27/preview_5.png) | ![preview 6](27/preview_6.png) | ![preview 7](27/preview_7.png) | ![preview 8](27/preview_8.png) | | 28 | 21 | [Download](28/dataset.zip) | ![preview 1](28/preview_1.png) | ![preview 2](28/preview_2.png) | ![preview 3](28/preview_3.png) | ![preview 4](28/preview_4.png) | ![preview 5](28/preview_5.png) | ![preview 6](28/preview_6.png) | ![preview 7](28/preview_7.png) | ![preview 8](28/preview_8.png) | | 29 | 103 | [Download](29/dataset.zip) | ![preview 1](29/preview_1.png) | ![preview 2](29/preview_2.png) | ![preview 3](29/preview_3.png) | ![preview 4](29/preview_4.png) | ![preview 5](29/preview_5.png) | ![preview 6](29/preview_6.png) | ![preview 7](29/preview_7.png) | ![preview 8](29/preview_8.png) | | 30 | 16 | [Download](30/dataset.zip) | ![preview 1](30/preview_1.png) | ![preview 2](30/preview_2.png) | ![preview 3](30/preview_3.png) | ![preview 4](30/preview_4.png) | ![preview 5](30/preview_5.png) | ![preview 6](30/preview_6.png) | ![preview 7](30/preview_7.png) | ![preview 8](30/preview_8.png) | | 31 | 12 | [Download](31/dataset.zip) | ![preview 1](31/preview_1.png) | ![preview 2](31/preview_2.png) | ![preview 3](31/preview_3.png) | ![preview 4](31/preview_4.png) | ![preview 5](31/preview_5.png) | ![preview 6](31/preview_6.png) | ![preview 7](31/preview_7.png) | ![preview 8](31/preview_8.png) | | 32 | 35 | [Download](32/dataset.zip) | ![preview 1](32/preview_1.png) | ![preview 2](32/preview_2.png) | ![preview 3](32/preview_3.png) | ![preview 4](32/preview_4.png) | ![preview 5](32/preview_5.png) | ![preview 6](32/preview_6.png) | ![preview 7](32/preview_7.png) | ![preview 8](32/preview_8.png) | | 33 | 8 | [Download](33/dataset.zip) | ![preview 1](33/preview_1.png) | ![preview 2](33/preview_2.png) | ![preview 3](33/preview_3.png) | ![preview 4](33/preview_4.png) | ![preview 5](33/preview_5.png) | ![preview 6](33/preview_6.png) | ![preview 7](33/preview_7.png) | ![preview 8](33/preview_8.png) | | 34 | 14 | [Download](34/dataset.zip) | ![preview 1](34/preview_1.png) | ![preview 2](34/preview_2.png) | ![preview 3](34/preview_3.png) | ![preview 4](34/preview_4.png) | ![preview 5](34/preview_5.png) | ![preview 6](34/preview_6.png) | ![preview 7](34/preview_7.png) | ![preview 8](34/preview_8.png) | | 35 | 15 | [Download](35/dataset.zip) | ![preview 1](35/preview_1.png) | ![preview 2](35/preview_2.png) | ![preview 3](35/preview_3.png) | ![preview 4](35/preview_4.png) | ![preview 5](35/preview_5.png) | ![preview 6](35/preview_6.png) | ![preview 7](35/preview_7.png) | ![preview 8](35/preview_8.png) | | 36 | 10 | [Download](36/dataset.zip) | ![preview 1](36/preview_1.png) | ![preview 2](36/preview_2.png) | ![preview 3](36/preview_3.png) | ![preview 4](36/preview_4.png) | ![preview 5](36/preview_5.png) | ![preview 6](36/preview_6.png) | ![preview 7](36/preview_7.png) | ![preview 8](36/preview_8.png) | | 37 | 16 | [Download](37/dataset.zip) | ![preview 1](37/preview_1.png) | ![preview 2](37/preview_2.png) | ![preview 3](37/preview_3.png) | ![preview 4](37/preview_4.png) | ![preview 5](37/preview_5.png) | ![preview 6](37/preview_6.png) | ![preview 7](37/preview_7.png) | ![preview 8](37/preview_8.png) | | 38 | 33 | [Download](38/dataset.zip) | ![preview 1](38/preview_1.png) | ![preview 2](38/preview_2.png) | ![preview 3](38/preview_3.png) | ![preview 4](38/preview_4.png) | ![preview 5](38/preview_5.png) | ![preview 6](38/preview_6.png) | ![preview 7](38/preview_7.png) | ![preview 8](38/preview_8.png) | | 39 | 17 | [Download](39/dataset.zip) | ![preview 1](39/preview_1.png) | ![preview 2](39/preview_2.png) | ![preview 3](39/preview_3.png) | ![preview 4](39/preview_4.png) | ![preview 5](39/preview_5.png) | ![preview 6](39/preview_6.png) | ![preview 7](39/preview_7.png) | ![preview 8](39/preview_8.png) | | 40 | 70 | [Download](40/dataset.zip) | ![preview 1](40/preview_1.png) | ![preview 2](40/preview_2.png) | ![preview 3](40/preview_3.png) | ![preview 4](40/preview_4.png) | ![preview 5](40/preview_5.png) | ![preview 6](40/preview_6.png) | ![preview 7](40/preview_7.png) | ![preview 8](40/preview_8.png) | | 41 | 10 | [Download](41/dataset.zip) | ![preview 1](41/preview_1.png) | ![preview 2](41/preview_2.png) | ![preview 3](41/preview_3.png) | ![preview 4](41/preview_4.png) | ![preview 5](41/preview_5.png) | ![preview 6](41/preview_6.png) | ![preview 7](41/preview_7.png) | ![preview 8](41/preview_8.png) | | 42 | 26 | [Download](42/dataset.zip) | ![preview 1](42/preview_1.png) | ![preview 2](42/preview_2.png) | ![preview 3](42/preview_3.png) | ![preview 4](42/preview_4.png) | ![preview 5](42/preview_5.png) | ![preview 6](42/preview_6.png) | ![preview 7](42/preview_7.png) | ![preview 8](42/preview_8.png) | | 43 | 1939 | [Download](43/dataset.zip) | ![preview 1](43/preview_1.png) | ![preview 2](43/preview_2.png) | ![preview 3](43/preview_3.png) | ![preview 4](43/preview_4.png) | ![preview 5](43/preview_5.png) | ![preview 6](43/preview_6.png) | ![preview 7](43/preview_7.png) | ![preview 8](43/preview_8.png) | | 44 | 105 | [Download](44/dataset.zip) | ![preview 1](44/preview_1.png) | ![preview 2](44/preview_2.png) | ![preview 3](44/preview_3.png) | ![preview 4](44/preview_4.png) | ![preview 5](44/preview_5.png) | ![preview 6](44/preview_6.png) | ![preview 7](44/preview_7.png) | ![preview 8](44/preview_8.png) | | 45 | 22 | [Download](45/dataset.zip) | ![preview 1](45/preview_1.png) | ![preview 2](45/preview_2.png) | ![preview 3](45/preview_3.png) | ![preview 4](45/preview_4.png) | ![preview 5](45/preview_5.png) | ![preview 6](45/preview_6.png) | ![preview 7](45/preview_7.png) | ![preview 8](45/preview_8.png) | | 46 | 36 | [Download](46/dataset.zip) | ![preview 1](46/preview_1.png) | ![preview 2](46/preview_2.png) | ![preview 3](46/preview_3.png) | ![preview 4](46/preview_4.png) | ![preview 5](46/preview_5.png) | ![preview 6](46/preview_6.png) | ![preview 7](46/preview_7.png) | ![preview 8](46/preview_8.png) | | 47 | 38 | [Download](47/dataset.zip) | ![preview 1](47/preview_1.png) | ![preview 2](47/preview_2.png) | ![preview 3](47/preview_3.png) | ![preview 4](47/preview_4.png) | ![preview 5](47/preview_5.png) | ![preview 6](47/preview_6.png) | ![preview 7](47/preview_7.png) | ![preview 8](47/preview_8.png) | | 48 | 8 | [Download](48/dataset.zip) | ![preview 1](48/preview_1.png) | ![preview 2](48/preview_2.png) | ![preview 3](48/preview_3.png) | ![preview 4](48/preview_4.png) | ![preview 5](48/preview_5.png) | ![preview 6](48/preview_6.png) | ![preview 7](48/preview_7.png) | ![preview 8](48/preview_8.png) | | 49 | 7 | [Download](49/dataset.zip) | ![preview 1](49/preview_1.png) | ![preview 2](49/preview_2.png) | ![preview 3](49/preview_3.png) | ![preview 4](49/preview_4.png) | ![preview 5](49/preview_5.png) | ![preview 6](49/preview_6.png) | ![preview 7](49/preview_7.png) | N/A | | 50 | 69 | [Download](50/dataset.zip) | ![preview 1](50/preview_1.png) | ![preview 2](50/preview_2.png) | ![preview 3](50/preview_3.png) | ![preview 4](50/preview_4.png) | ![preview 5](50/preview_5.png) | ![preview 6](50/preview_6.png) | ![preview 7](50/preview_7.png) | ![preview 8](50/preview_8.png) | | 51 | 66 | [Download](51/dataset.zip) | ![preview 1](51/preview_1.png) | ![preview 2](51/preview_2.png) | ![preview 3](51/preview_3.png) | ![preview 4](51/preview_4.png) | ![preview 5](51/preview_5.png) | ![preview 6](51/preview_6.png) | ![preview 7](51/preview_7.png) | ![preview 8](51/preview_8.png) | | 52 | 7 | [Download](52/dataset.zip) | ![preview 1](52/preview_1.png) | ![preview 2](52/preview_2.png) | ![preview 3](52/preview_3.png) | ![preview 4](52/preview_4.png) | ![preview 5](52/preview_5.png) | ![preview 6](52/preview_6.png) | ![preview 7](52/preview_7.png) | N/A | | 53 | 22 | [Download](53/dataset.zip) | ![preview 1](53/preview_1.png) | ![preview 2](53/preview_2.png) | ![preview 3](53/preview_3.png) | ![preview 4](53/preview_4.png) | ![preview 5](53/preview_5.png) | ![preview 6](53/preview_6.png) | ![preview 7](53/preview_7.png) | ![preview 8](53/preview_8.png) | | 54 | 7 | [Download](54/dataset.zip) | ![preview 1](54/preview_1.png) | ![preview 2](54/preview_2.png) | ![preview 3](54/preview_3.png) | ![preview 4](54/preview_4.png) | ![preview 5](54/preview_5.png) | ![preview 6](54/preview_6.png) | ![preview 7](54/preview_7.png) | N/A | | 55 | 14 | [Download](55/dataset.zip) | ![preview 1](55/preview_1.png) | ![preview 2](55/preview_2.png) | ![preview 3](55/preview_3.png) | ![preview 4](55/preview_4.png) | ![preview 5](55/preview_5.png) | ![preview 6](55/preview_6.png) | ![preview 7](55/preview_7.png) | ![preview 8](55/preview_8.png) | | 56 | 197 | [Download](56/dataset.zip) | ![preview 1](56/preview_1.png) | ![preview 2](56/preview_2.png) | ![preview 3](56/preview_3.png) | ![preview 4](56/preview_4.png) | ![preview 5](56/preview_5.png) | ![preview 6](56/preview_6.png) | ![preview 7](56/preview_7.png) | ![preview 8](56/preview_8.png) | | 57 | 52 | [Download](57/dataset.zip) | ![preview 1](57/preview_1.png) | ![preview 2](57/preview_2.png) | ![preview 3](57/preview_3.png) | ![preview 4](57/preview_4.png) | ![preview 5](57/preview_5.png) | ![preview 6](57/preview_6.png) | ![preview 7](57/preview_7.png) | ![preview 8](57/preview_8.png) | | 58 | 8 | [Download](58/dataset.zip) | ![preview 1](58/preview_1.png) | ![preview 2](58/preview_2.png) | ![preview 3](58/preview_3.png) | ![preview 4](58/preview_4.png) | ![preview 5](58/preview_5.png) | ![preview 6](58/preview_6.png) | ![preview 7](58/preview_7.png) | ![preview 8](58/preview_8.png) | | 59 | 29 | [Download](59/dataset.zip) | ![preview 1](59/preview_1.png) | ![preview 2](59/preview_2.png) | ![preview 3](59/preview_3.png) | ![preview 4](59/preview_4.png) | ![preview 5](59/preview_5.png) | ![preview 6](59/preview_6.png) | ![preview 7](59/preview_7.png) | ![preview 8](59/preview_8.png) | | 60 | 62 | [Download](60/dataset.zip) | ![preview 1](60/preview_1.png) | ![preview 2](60/preview_2.png) | ![preview 3](60/preview_3.png) | ![preview 4](60/preview_4.png) | ![preview 5](60/preview_5.png) | ![preview 6](60/preview_6.png) | ![preview 7](60/preview_7.png) | ![preview 8](60/preview_8.png) | | 61 | 26 | [Download](61/dataset.zip) | ![preview 1](61/preview_1.png) | ![preview 2](61/preview_2.png) | ![preview 3](61/preview_3.png) | ![preview 4](61/preview_4.png) | ![preview 5](61/preview_5.png) | ![preview 6](61/preview_6.png) | ![preview 7](61/preview_7.png) | ![preview 8](61/preview_8.png) | | 62 | 69 | [Download](62/dataset.zip) | ![preview 1](62/preview_1.png) | ![preview 2](62/preview_2.png) | ![preview 3](62/preview_3.png) | ![preview 4](62/preview_4.png) | ![preview 5](62/preview_5.png) | ![preview 6](62/preview_6.png) | ![preview 7](62/preview_7.png) | ![preview 8](62/preview_8.png) | | 63 | 30 | [Download](63/dataset.zip) | ![preview 1](63/preview_1.png) | ![preview 2](63/preview_2.png) | ![preview 3](63/preview_3.png) | ![preview 4](63/preview_4.png) | ![preview 5](63/preview_5.png) | ![preview 6](63/preview_6.png) | ![preview 7](63/preview_7.png) | ![preview 8](63/preview_8.png) | | 64 | 11 | [Download](64/dataset.zip) | ![preview 1](64/preview_1.png) | ![preview 2](64/preview_2.png) | ![preview 3](64/preview_3.png) | ![preview 4](64/preview_4.png) | ![preview 5](64/preview_5.png) | ![preview 6](64/preview_6.png) | ![preview 7](64/preview_7.png) | ![preview 8](64/preview_8.png) | | 65 | 55 | [Download](65/dataset.zip) | ![preview 1](65/preview_1.png) | ![preview 2](65/preview_2.png) | ![preview 3](65/preview_3.png) | ![preview 4](65/preview_4.png) | ![preview 5](65/preview_5.png) | ![preview 6](65/preview_6.png) | ![preview 7](65/preview_7.png) | ![preview 8](65/preview_8.png) | | 66 | 15 | [Download](66/dataset.zip) | ![preview 1](66/preview_1.png) | ![preview 2](66/preview_2.png) | ![preview 3](66/preview_3.png) | ![preview 4](66/preview_4.png) | ![preview 5](66/preview_5.png) | ![preview 6](66/preview_6.png) | ![preview 7](66/preview_7.png) | ![preview 8](66/preview_8.png) | | 67 | 204 | [Download](67/dataset.zip) | ![preview 1](67/preview_1.png) | ![preview 2](67/preview_2.png) | ![preview 3](67/preview_3.png) | ![preview 4](67/preview_4.png) | ![preview 5](67/preview_5.png) | ![preview 6](67/preview_6.png) | ![preview 7](67/preview_7.png) | ![preview 8](67/preview_8.png) | | 68 | 283 | [Download](68/dataset.zip) | ![preview 1](68/preview_1.png) | ![preview 2](68/preview_2.png) | ![preview 3](68/preview_3.png) | ![preview 4](68/preview_4.png) | ![preview 5](68/preview_5.png) | ![preview 6](68/preview_6.png) | ![preview 7](68/preview_7.png) | ![preview 8](68/preview_8.png) | | 69 | 26 | [Download](69/dataset.zip) | ![preview 1](69/preview_1.png) | ![preview 2](69/preview_2.png) | ![preview 3](69/preview_3.png) | ![preview 4](69/preview_4.png) | ![preview 5](69/preview_5.png) | ![preview 6](69/preview_6.png) | ![preview 7](69/preview_7.png) | ![preview 8](69/preview_8.png) | | 70 | 40 | [Download](70/dataset.zip) | ![preview 1](70/preview_1.png) | ![preview 2](70/preview_2.png) | ![preview 3](70/preview_3.png) | ![preview 4](70/preview_4.png) | ![preview 5](70/preview_5.png) | ![preview 6](70/preview_6.png) | ![preview 7](70/preview_7.png) | ![preview 8](70/preview_8.png) | | 71 | 17 | [Download](71/dataset.zip) | ![preview 1](71/preview_1.png) | ![preview 2](71/preview_2.png) | ![preview 3](71/preview_3.png) | ![preview 4](71/preview_4.png) | ![preview 5](71/preview_5.png) | ![preview 6](71/preview_6.png) | ![preview 7](71/preview_7.png) | ![preview 8](71/preview_8.png) | | 72 | 8 | [Download](72/dataset.zip) | ![preview 1](72/preview_1.png) | ![preview 2](72/preview_2.png) | ![preview 3](72/preview_3.png) | ![preview 4](72/preview_4.png) | ![preview 5](72/preview_5.png) | ![preview 6](72/preview_6.png) | ![preview 7](72/preview_7.png) | ![preview 8](72/preview_8.png) | | 73 | 13 | [Download](73/dataset.zip) | ![preview 1](73/preview_1.png) | ![preview 2](73/preview_2.png) | ![preview 3](73/preview_3.png) | ![preview 4](73/preview_4.png) | ![preview 5](73/preview_5.png) | ![preview 6](73/preview_6.png) | ![preview 7](73/preview_7.png) | ![preview 8](73/preview_8.png) | | 74 | 18 | [Download](74/dataset.zip) | ![preview 1](74/preview_1.png) | ![preview 2](74/preview_2.png) | ![preview 3](74/preview_3.png) | ![preview 4](74/preview_4.png) | ![preview 5](74/preview_5.png) | ![preview 6](74/preview_6.png) | ![preview 7](74/preview_7.png) | ![preview 8](74/preview_8.png) | | 75 | 16 | [Download](75/dataset.zip) | ![preview 1](75/preview_1.png) | ![preview 2](75/preview_2.png) | ![preview 3](75/preview_3.png) | ![preview 4](75/preview_4.png) | ![preview 5](75/preview_5.png) | ![preview 6](75/preview_6.png) | ![preview 7](75/preview_7.png) | ![preview 8](75/preview_8.png) | | 76 | 8 | [Download](76/dataset.zip) | ![preview 1](76/preview_1.png) | ![preview 2](76/preview_2.png) | ![preview 3](76/preview_3.png) | ![preview 4](76/preview_4.png) | ![preview 5](76/preview_5.png) | ![preview 6](76/preview_6.png) | ![preview 7](76/preview_7.png) | ![preview 8](76/preview_8.png) | | 77 | 10 | [Download](77/dataset.zip) | ![preview 1](77/preview_1.png) | ![preview 2](77/preview_2.png) | ![preview 3](77/preview_3.png) | ![preview 4](77/preview_4.png) | ![preview 5](77/preview_5.png) | ![preview 6](77/preview_6.png) | ![preview 7](77/preview_7.png) | ![preview 8](77/preview_8.png) | | 78 | 51 | [Download](78/dataset.zip) | ![preview 1](78/preview_1.png) | ![preview 2](78/preview_2.png) | ![preview 3](78/preview_3.png) | ![preview 4](78/preview_4.png) | ![preview 5](78/preview_5.png) | ![preview 6](78/preview_6.png) | ![preview 7](78/preview_7.png) | ![preview 8](78/preview_8.png) | | 79 | 135 | [Download](79/dataset.zip) | ![preview 1](79/preview_1.png) | ![preview 2](79/preview_2.png) | ![preview 3](79/preview_3.png) | ![preview 4](79/preview_4.png) | ![preview 5](79/preview_5.png) | ![preview 6](79/preview_6.png) | ![preview 7](79/preview_7.png) | ![preview 8](79/preview_8.png) | | 80 | 62 | [Download](80/dataset.zip) | ![preview 1](80/preview_1.png) | ![preview 2](80/preview_2.png) | ![preview 3](80/preview_3.png) | ![preview 4](80/preview_4.png) | ![preview 5](80/preview_5.png) | ![preview 6](80/preview_6.png) | ![preview 7](80/preview_7.png) | ![preview 8](80/preview_8.png) | | 81 | 14 | [Download](81/dataset.zip) | ![preview 1](81/preview_1.png) | ![preview 2](81/preview_2.png) | ![preview 3](81/preview_3.png) | ![preview 4](81/preview_4.png) | ![preview 5](81/preview_5.png) | ![preview 6](81/preview_6.png) | ![preview 7](81/preview_7.png) | ![preview 8](81/preview_8.png) | | 82 | 48 | [Download](82/dataset.zip) | ![preview 1](82/preview_1.png) | ![preview 2](82/preview_2.png) | ![preview 3](82/preview_3.png) | ![preview 4](82/preview_4.png) | ![preview 5](82/preview_5.png) | ![preview 6](82/preview_6.png) | ![preview 7](82/preview_7.png) | ![preview 8](82/preview_8.png) | | 83 | 15 | [Download](83/dataset.zip) | ![preview 1](83/preview_1.png) | ![preview 2](83/preview_2.png) | ![preview 3](83/preview_3.png) | ![preview 4](83/preview_4.png) | ![preview 5](83/preview_5.png) | ![preview 6](83/preview_6.png) | ![preview 7](83/preview_7.png) | ![preview 8](83/preview_8.png) | | 84 | 14 | [Download](84/dataset.zip) | ![preview 1](84/preview_1.png) | ![preview 2](84/preview_2.png) | ![preview 3](84/preview_3.png) | ![preview 4](84/preview_4.png) | ![preview 5](84/preview_5.png) | ![preview 6](84/preview_6.png) | ![preview 7](84/preview_7.png) | ![preview 8](84/preview_8.png) | | 85 | 38 | [Download](85/dataset.zip) | ![preview 1](85/preview_1.png) | ![preview 2](85/preview_2.png) | ![preview 3](85/preview_3.png) | ![preview 4](85/preview_4.png) | ![preview 5](85/preview_5.png) | ![preview 6](85/preview_6.png) | ![preview 7](85/preview_7.png) | ![preview 8](85/preview_8.png) | | 86 | 6 | [Download](86/dataset.zip) | ![preview 1](86/preview_1.png) | ![preview 2](86/preview_2.png) | ![preview 3](86/preview_3.png) | ![preview 4](86/preview_4.png) | ![preview 5](86/preview_5.png) | ![preview 6](86/preview_6.png) | N/A | N/A | | 87 | 14 | [Download](87/dataset.zip) | ![preview 1](87/preview_1.png) | ![preview 2](87/preview_2.png) | ![preview 3](87/preview_3.png) | ![preview 4](87/preview_4.png) | ![preview 5](87/preview_5.png) | ![preview 6](87/preview_6.png) | ![preview 7](87/preview_7.png) | ![preview 8](87/preview_8.png) | | 88 | 8 | [Download](88/dataset.zip) | ![preview 1](88/preview_1.png) | ![preview 2](88/preview_2.png) | ![preview 3](88/preview_3.png) | ![preview 4](88/preview_4.png) | ![preview 5](88/preview_5.png) | ![preview 6](88/preview_6.png) | ![preview 7](88/preview_7.png) | ![preview 8](88/preview_8.png) | | 89 | 9 | [Download](89/dataset.zip) | ![preview 1](89/preview_1.png) | ![preview 2](89/preview_2.png) | ![preview 3](89/preview_3.png) | ![preview 4](89/preview_4.png) | ![preview 5](89/preview_5.png) | ![preview 6](89/preview_6.png) | ![preview 7](89/preview_7.png) | ![preview 8](89/preview_8.png) | | 90 | 6 | [Download](90/dataset.zip) | ![preview 1](90/preview_1.png) | ![preview 2](90/preview_2.png) | ![preview 3](90/preview_3.png) | ![preview 4](90/preview_4.png) | ![preview 5](90/preview_5.png) | ![preview 6](90/preview_6.png) | N/A | N/A | | 91 | 5 | [Download](91/dataset.zip) | ![preview 1](91/preview_1.png) | ![preview 2](91/preview_2.png) | ![preview 3](91/preview_3.png) | ![preview 4](91/preview_4.png) | ![preview 5](91/preview_5.png) | N/A | N/A | N/A | | 92 | 38 | [Download](92/dataset.zip) | ![preview 1](92/preview_1.png) | ![preview 2](92/preview_2.png) | ![preview 3](92/preview_3.png) | ![preview 4](92/preview_4.png) | ![preview 5](92/preview_5.png) | ![preview 6](92/preview_6.png) | ![preview 7](92/preview_7.png) | ![preview 8](92/preview_8.png) | | 93 | 29 | [Download](93/dataset.zip) | ![preview 1](93/preview_1.png) | ![preview 2](93/preview_2.png) | ![preview 3](93/preview_3.png) | ![preview 4](93/preview_4.png) | ![preview 5](93/preview_5.png) | ![preview 6](93/preview_6.png) | ![preview 7](93/preview_7.png) | ![preview 8](93/preview_8.png) | | 94 | 7 | [Download](94/dataset.zip) | ![preview 1](94/preview_1.png) | ![preview 2](94/preview_2.png) | ![preview 3](94/preview_3.png) | ![preview 4](94/preview_4.png) | ![preview 5](94/preview_5.png) | ![preview 6](94/preview_6.png) | ![preview 7](94/preview_7.png) | N/A | | 95 | 17 | [Download](95/dataset.zip) | ![preview 1](95/preview_1.png) | ![preview 2](95/preview_2.png) | ![preview 3](95/preview_3.png) | ![preview 4](95/preview_4.png) | ![preview 5](95/preview_5.png) | ![preview 6](95/preview_6.png) | ![preview 7](95/preview_7.png) | ![preview 8](95/preview_8.png) | | 96 | 24 | [Download](96/dataset.zip) | ![preview 1](96/preview_1.png) | ![preview 2](96/preview_2.png) | ![preview 3](96/preview_3.png) | ![preview 4](96/preview_4.png) | ![preview 5](96/preview_5.png) | ![preview 6](96/preview_6.png) | ![preview 7](96/preview_7.png) | ![preview 8](96/preview_8.png) | | 97 | 11 | [Download](97/dataset.zip) | ![preview 1](97/preview_1.png) | ![preview 2](97/preview_2.png) | ![preview 3](97/preview_3.png) | ![preview 4](97/preview_4.png) | ![preview 5](97/preview_5.png) | ![preview 6](97/preview_6.png) | ![preview 7](97/preview_7.png) | ![preview 8](97/preview_8.png) | | noise | 223 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |
ppsanjay/dataerpici
2023-09-18T11:49:44.000Z
[ "region:us" ]
ppsanjay
null
null
null
0
0
Entry not found
marsexpress/none
2023-09-15T10:16:47.000Z
[ "region:us" ]
marsexpress
null
null
null
0
0
Entry not found
CyberHarem/harada_miyo_idolmastercinderellagirls
2023-09-17T17:39:01.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of harada_miyo (THE iDOLM@STER: Cinderella Girls) This is the dataset of harada_miyo (THE iDOLM@STER: Cinderella Girls), containing 64 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 64 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 172 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 64 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 64 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 64 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 64 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 64 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 172 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 172 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 172 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/yagami_makino_idolmastercinderellagirls
2023-09-17T17:39:03.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of yagami_makino (THE iDOLM@STER: Cinderella Girls) This is the dataset of yagami_makino (THE iDOLM@STER: Cinderella Girls), containing 161 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 161 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 405 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 161 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 161 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 161 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 161 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 161 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 405 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 405 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 405 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
ISOBIM/GeometricCommand
2023-09-15T10:30:15.000Z
[ "license:other", "region:us" ]
ISOBIM
null
null
null
0
0
--- license: other ---
NickKolok/regs-nextphoto
2023-09-16T15:03:23.000Z
[ "license:gpl-3.0", "region:us" ]
NickKolok
null
null
null
0
0
--- license: gpl-3.0 ---
CyberHarem/okazaki_yasuha_idolmastercinderellagirls
2023-09-17T17:39:05.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of okazaki_yasuha (THE iDOLM@STER: Cinderella Girls) This is the dataset of okazaki_yasuha (THE iDOLM@STER: Cinderella Girls), containing 50 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 50 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 127 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 50 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 50 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 50 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 50 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 50 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 127 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 127 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 127 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
open-llm-leaderboard/details_NewstaR__Morningstar-13b-hf
2023-09-15T10:47:50.000Z
[ "region:us" ]
open-llm-leaderboard
null
null
null
0
0
--- pretty_name: Evaluation run of NewstaR/Morningstar-13b-hf dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [NewstaR/Morningstar-13b-hf](https://huggingface.co/NewstaR/Morningstar-13b-hf)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_NewstaR__Morningstar-13b-hf\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-15T10:46:30.957408](https://huggingface.co/datasets/open-llm-leaderboard/details_NewstaR__Morningstar-13b-hf/blob/main/results_2023-09-15T10-46-30.957408.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\": 0.5478679055985619,\n\ \ \"acc_stderr\": 0.03451143209518346,\n \"acc_norm\": 0.551637824239685,\n\ \ \"acc_norm_stderr\": 0.03449240971096488,\n \"mc1\": 0.28518971848225216,\n\ \ \"mc1_stderr\": 0.015805827874454895,\n \"mc2\": 0.44118181192718914,\n\ \ \"mc2_stderr\": 0.01575597129997008\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.5580204778156996,\n \"acc_stderr\": 0.014512682523128343,\n\ \ \"acc_norm\": 0.590443686006826,\n \"acc_norm_stderr\": 0.01437035863247244\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6292571200955985,\n\ \ \"acc_stderr\": 0.0048201660022530795,\n \"acc_norm\": 0.819259111730731,\n\ \ \"acc_norm_stderr\": 0.0038401692240122715\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.31,\n \"acc_stderr\": 0.046482319871173156,\n \ \ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.046482319871173156\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.4740740740740741,\n\ \ \"acc_stderr\": 0.04313531696750574,\n \"acc_norm\": 0.4740740740740741,\n\ \ \"acc_norm_stderr\": 0.04313531696750574\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.5460526315789473,\n \"acc_stderr\": 0.04051646342874142,\n\ \ \"acc_norm\": 0.5460526315789473,\n \"acc_norm_stderr\": 0.04051646342874142\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.53,\n\ \ \"acc_stderr\": 0.05016135580465919,\n \"acc_norm\": 0.53,\n \ \ \"acc_norm_stderr\": 0.05016135580465919\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.5849056603773585,\n \"acc_stderr\": 0.03032594578928611,\n\ \ \"acc_norm\": 0.5849056603773585,\n \"acc_norm_stderr\": 0.03032594578928611\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5833333333333334,\n\ \ \"acc_stderr\": 0.04122728707651282,\n \"acc_norm\": 0.5833333333333334,\n\ \ \"acc_norm_stderr\": 0.04122728707651282\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.048783173121456316,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.048783173121456316\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"\ acc\": 0.47,\n \"acc_stderr\": 0.05016135580465919,\n \"acc_norm\"\ : 0.47,\n \"acc_norm_stderr\": 0.05016135580465919\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.4682080924855491,\n\ \ \"acc_stderr\": 0.03804749744364763,\n \"acc_norm\": 0.4682080924855491,\n\ \ \"acc_norm_stderr\": 0.03804749744364763\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3137254901960784,\n \"acc_stderr\": 0.04617034827006717,\n\ \ \"acc_norm\": 0.3137254901960784,\n \"acc_norm_stderr\": 0.04617034827006717\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.68,\n \"acc_stderr\": 0.04688261722621505,\n \"acc_norm\": 0.68,\n\ \ \"acc_norm_stderr\": 0.04688261722621505\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.03202563076101735,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.03202563076101735\n },\n\ \ \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.3157894736842105,\n\ \ \"acc_stderr\": 0.043727482902780064,\n \"acc_norm\": 0.3157894736842105,\n\ \ \"acc_norm_stderr\": 0.043727482902780064\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.503448275862069,\n \"acc_stderr\": 0.0416656757710158,\n\ \ \"acc_norm\": 0.503448275862069,\n \"acc_norm_stderr\": 0.0416656757710158\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.3412698412698413,\n \"acc_stderr\": 0.024419234966819064,\n \"\ acc_norm\": 0.3412698412698413,\n \"acc_norm_stderr\": 0.024419234966819064\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.30158730158730157,\n\ \ \"acc_stderr\": 0.04104947269903394,\n \"acc_norm\": 0.30158730158730157,\n\ \ \"acc_norm_stderr\": 0.04104947269903394\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\": 0.6419354838709678,\n\ \ \"acc_stderr\": 0.02727389059430064,\n \"acc_norm\": 0.6419354838709678,\n\ \ \"acc_norm_stderr\": 0.02727389059430064\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.458128078817734,\n \"acc_stderr\": 0.03505630140785741,\n\ \ \"acc_norm\": 0.458128078817734,\n \"acc_norm_stderr\": 0.03505630140785741\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.59,\n \"acc_stderr\": 0.04943110704237102,\n \"acc_norm\"\ : 0.59,\n \"acc_norm_stderr\": 0.04943110704237102\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.6787878787878788,\n \"acc_stderr\": 0.03646204963253811,\n\ \ \"acc_norm\": 0.6787878787878788,\n \"acc_norm_stderr\": 0.03646204963253811\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.702020202020202,\n \"acc_stderr\": 0.03258630383836556,\n \"acc_norm\"\ : 0.702020202020202,\n \"acc_norm_stderr\": 0.03258630383836556\n },\n\ \ \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n \ \ \"acc\": 0.7875647668393783,\n \"acc_stderr\": 0.029519282616817234,\n\ \ \"acc_norm\": 0.7875647668393783,\n \"acc_norm_stderr\": 0.029519282616817234\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.4948717948717949,\n \"acc_stderr\": 0.02534967290683866,\n \ \ \"acc_norm\": 0.4948717948717949,\n \"acc_norm_stderr\": 0.02534967290683866\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.3074074074074074,\n \"acc_stderr\": 0.02813325257881564,\n \ \ \"acc_norm\": 0.3074074074074074,\n \"acc_norm_stderr\": 0.02813325257881564\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.5294117647058824,\n \"acc_stderr\": 0.03242225027115007,\n \ \ \"acc_norm\": 0.5294117647058824,\n \"acc_norm_stderr\": 0.03242225027115007\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.33774834437086093,\n \"acc_stderr\": 0.038615575462551684,\n \"\ acc_norm\": 0.33774834437086093,\n \"acc_norm_stderr\": 0.038615575462551684\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.7321100917431193,\n \"acc_stderr\": 0.018987462257978652,\n \"\ acc_norm\": 0.7321100917431193,\n \"acc_norm_stderr\": 0.018987462257978652\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.3888888888888889,\n \"acc_stderr\": 0.03324708911809117,\n \"\ acc_norm\": 0.3888888888888889,\n \"acc_norm_stderr\": 0.03324708911809117\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.7401960784313726,\n \"acc_stderr\": 0.03077855467869326,\n \"\ acc_norm\": 0.7401960784313726,\n \"acc_norm_stderr\": 0.03077855467869326\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.7172995780590717,\n \"acc_stderr\": 0.02931281415395592,\n \ \ \"acc_norm\": 0.7172995780590717,\n \"acc_norm_stderr\": 0.02931281415395592\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6457399103139013,\n\ \ \"acc_stderr\": 0.032100621541349864,\n \"acc_norm\": 0.6457399103139013,\n\ \ \"acc_norm_stderr\": 0.032100621541349864\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.6335877862595419,\n \"acc_stderr\": 0.04225875451969637,\n\ \ \"acc_norm\": 0.6335877862595419,\n \"acc_norm_stderr\": 0.04225875451969637\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.768595041322314,\n \"acc_stderr\": 0.03849856098794089,\n \"acc_norm\"\ : 0.768595041322314,\n \"acc_norm_stderr\": 0.03849856098794089\n },\n\ \ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.6944444444444444,\n\ \ \"acc_stderr\": 0.044531975073749834,\n \"acc_norm\": 0.6944444444444444,\n\ \ \"acc_norm_stderr\": 0.044531975073749834\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.6503067484662577,\n \"acc_stderr\": 0.037466683254700206,\n\ \ \"acc_norm\": 0.6503067484662577,\n \"acc_norm_stderr\": 0.037466683254700206\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.35714285714285715,\n\ \ \"acc_stderr\": 0.04547960999764376,\n \"acc_norm\": 0.35714285714285715,\n\ \ \"acc_norm_stderr\": 0.04547960999764376\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.7378640776699029,\n \"acc_stderr\": 0.04354631077260595,\n\ \ \"acc_norm\": 0.7378640776699029,\n \"acc_norm_stderr\": 0.04354631077260595\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7863247863247863,\n\ \ \"acc_stderr\": 0.026853450377009175,\n \"acc_norm\": 0.7863247863247863,\n\ \ \"acc_norm_stderr\": 0.026853450377009175\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.57,\n \"acc_stderr\": 0.049756985195624284,\n \ \ \"acc_norm\": 0.57,\n \"acc_norm_stderr\": 0.049756985195624284\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.7471264367816092,\n\ \ \"acc_stderr\": 0.015543377313719681,\n \"acc_norm\": 0.7471264367816092,\n\ \ \"acc_norm_stderr\": 0.015543377313719681\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.6127167630057804,\n \"acc_stderr\": 0.026226158605124655,\n\ \ \"acc_norm\": 0.6127167630057804,\n \"acc_norm_stderr\": 0.026226158605124655\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.3094972067039106,\n\ \ \"acc_stderr\": 0.015461169002371539,\n \"acc_norm\": 0.3094972067039106,\n\ \ \"acc_norm_stderr\": 0.015461169002371539\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.5947712418300654,\n \"acc_stderr\": 0.028110928492809068,\n\ \ \"acc_norm\": 0.5947712418300654,\n \"acc_norm_stderr\": 0.028110928492809068\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.5884244372990354,\n\ \ \"acc_stderr\": 0.02795048149440127,\n \"acc_norm\": 0.5884244372990354,\n\ \ \"acc_norm_stderr\": 0.02795048149440127\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.6111111111111112,\n \"acc_stderr\": 0.02712511551316687,\n\ \ \"acc_norm\": 0.6111111111111112,\n \"acc_norm_stderr\": 0.02712511551316687\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.3900709219858156,\n \"acc_stderr\": 0.029097675599463926,\n \ \ \"acc_norm\": 0.3900709219858156,\n \"acc_norm_stderr\": 0.029097675599463926\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.3917861799217731,\n\ \ \"acc_stderr\": 0.012467564418145121,\n \"acc_norm\": 0.3917861799217731,\n\ \ \"acc_norm_stderr\": 0.012467564418145121\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.5,\n \"acc_stderr\": 0.030372836961539352,\n \ \ \"acc_norm\": 0.5,\n \"acc_norm_stderr\": 0.030372836961539352\n \ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"acc\"\ : 0.5441176470588235,\n \"acc_stderr\": 0.02014893942041574,\n \"\ acc_norm\": 0.5441176470588235,\n \"acc_norm_stderr\": 0.02014893942041574\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6636363636363637,\n\ \ \"acc_stderr\": 0.04525393596302505,\n \"acc_norm\": 0.6636363636363637,\n\ \ \"acc_norm_stderr\": 0.04525393596302505\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.636734693877551,\n \"acc_stderr\": 0.030789051139030802,\n\ \ \"acc_norm\": 0.636734693877551,\n \"acc_norm_stderr\": 0.030789051139030802\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7512437810945274,\n\ \ \"acc_stderr\": 0.030567675938916714,\n \"acc_norm\": 0.7512437810945274,\n\ \ \"acc_norm_stderr\": 0.030567675938916714\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.81,\n \"acc_stderr\": 0.03942772444036625,\n \ \ \"acc_norm\": 0.81,\n \"acc_norm_stderr\": 0.03942772444036625\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.4819277108433735,\n\ \ \"acc_stderr\": 0.038899512528272166,\n \"acc_norm\": 0.4819277108433735,\n\ \ \"acc_norm_stderr\": 0.038899512528272166\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.7309941520467836,\n \"acc_stderr\": 0.03401052620104089,\n\ \ \"acc_norm\": 0.7309941520467836,\n \"acc_norm_stderr\": 0.03401052620104089\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.28518971848225216,\n\ \ \"mc1_stderr\": 0.015805827874454895,\n \"mc2\": 0.44118181192718914,\n\ \ \"mc2_stderr\": 0.01575597129997008\n }\n}\n```" repo_url: https://huggingface.co/NewstaR/Morningstar-13b-hf leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|arc:challenge|25_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hellaswag|10_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-15T10-46-30.957408.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-management|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-virology|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T10-46-30.957408.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_15T10_46_30.957408 path: - '**/details_harness|truthfulqa:mc|0_2023-09-15T10-46-30.957408.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-09-15T10-46-30.957408.parquet' - config_name: results data_files: - split: 2023_09_15T10_46_30.957408 path: - results_2023-09-15T10-46-30.957408.parquet - split: latest path: - results_2023-09-15T10-46-30.957408.parquet --- # Dataset Card for Evaluation run of NewstaR/Morningstar-13b-hf ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/NewstaR/Morningstar-13b-hf - **Paper:** - **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - **Point of Contact:** clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [NewstaR/Morningstar-13b-hf](https://huggingface.co/NewstaR/Morningstar-13b-hf) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_NewstaR__Morningstar-13b-hf", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-15T10:46:30.957408](https://huggingface.co/datasets/open-llm-leaderboard/details_NewstaR__Morningstar-13b-hf/blob/main/results_2023-09-15T10-46-30.957408.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": 0.5478679055985619, "acc_stderr": 0.03451143209518346, "acc_norm": 0.551637824239685, "acc_norm_stderr": 0.03449240971096488, "mc1": 0.28518971848225216, "mc1_stderr": 0.015805827874454895, "mc2": 0.44118181192718914, "mc2_stderr": 0.01575597129997008 }, "harness|arc:challenge|25": { "acc": 0.5580204778156996, "acc_stderr": 0.014512682523128343, "acc_norm": 0.590443686006826, "acc_norm_stderr": 0.01437035863247244 }, "harness|hellaswag|10": { "acc": 0.6292571200955985, "acc_stderr": 0.0048201660022530795, "acc_norm": 0.819259111730731, "acc_norm_stderr": 0.0038401692240122715 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.046482319871173156, "acc_norm": 0.31, "acc_norm_stderr": 0.046482319871173156 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4740740740740741, "acc_stderr": 0.04313531696750574, "acc_norm": 0.4740740740740741, "acc_norm_stderr": 0.04313531696750574 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5460526315789473, "acc_stderr": 0.04051646342874142, "acc_norm": 0.5460526315789473, "acc_norm_stderr": 0.04051646342874142 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5849056603773585, "acc_stderr": 0.03032594578928611, "acc_norm": 0.5849056603773585, "acc_norm_stderr": 0.03032594578928611 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5833333333333334, "acc_stderr": 0.04122728707651282, "acc_norm": 0.5833333333333334, "acc_norm_stderr": 0.04122728707651282 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4682080924855491, "acc_stderr": 0.03804749744364763, "acc_norm": 0.4682080924855491, "acc_norm_stderr": 0.03804749744364763 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3137254901960784, "acc_stderr": 0.04617034827006717, "acc_norm": 0.3137254901960784, "acc_norm_stderr": 0.04617034827006717 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.68, "acc_stderr": 0.04688261722621505, "acc_norm": 0.68, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4, "acc_stderr": 0.03202563076101735, "acc_norm": 0.4, "acc_norm_stderr": 0.03202563076101735 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3157894736842105, "acc_stderr": 0.043727482902780064, "acc_norm": 0.3157894736842105, "acc_norm_stderr": 0.043727482902780064 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.503448275862069, "acc_stderr": 0.0416656757710158, "acc_norm": 0.503448275862069, "acc_norm_stderr": 0.0416656757710158 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3412698412698413, "acc_stderr": 0.024419234966819064, "acc_norm": 0.3412698412698413, "acc_norm_stderr": 0.024419234966819064 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.30158730158730157, "acc_stderr": 0.04104947269903394, "acc_norm": 0.30158730158730157, "acc_norm_stderr": 0.04104947269903394 }, "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": 0.6419354838709678, "acc_stderr": 0.02727389059430064, "acc_norm": 0.6419354838709678, "acc_norm_stderr": 0.02727389059430064 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.458128078817734, "acc_stderr": 0.03505630140785741, "acc_norm": 0.458128078817734, "acc_norm_stderr": 0.03505630140785741 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6787878787878788, "acc_stderr": 0.03646204963253811, "acc_norm": 0.6787878787878788, "acc_norm_stderr": 0.03646204963253811 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.702020202020202, "acc_stderr": 0.03258630383836556, "acc_norm": 0.702020202020202, "acc_norm_stderr": 0.03258630383836556 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7875647668393783, "acc_stderr": 0.029519282616817234, "acc_norm": 0.7875647668393783, "acc_norm_stderr": 0.029519282616817234 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4948717948717949, "acc_stderr": 0.02534967290683866, "acc_norm": 0.4948717948717949, "acc_norm_stderr": 0.02534967290683866 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3074074074074074, "acc_stderr": 0.02813325257881564, "acc_norm": 0.3074074074074074, "acc_norm_stderr": 0.02813325257881564 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.5294117647058824, "acc_stderr": 0.03242225027115007, "acc_norm": 0.5294117647058824, "acc_norm_stderr": 0.03242225027115007 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.33774834437086093, "acc_stderr": 0.038615575462551684, "acc_norm": 0.33774834437086093, "acc_norm_stderr": 0.038615575462551684 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.7321100917431193, "acc_stderr": 0.018987462257978652, "acc_norm": 0.7321100917431193, "acc_norm_stderr": 0.018987462257978652 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.3888888888888889, "acc_stderr": 0.03324708911809117, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.03324708911809117 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.7401960784313726, "acc_stderr": 0.03077855467869326, "acc_norm": 0.7401960784313726, "acc_norm_stderr": 0.03077855467869326 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.7172995780590717, "acc_stderr": 0.02931281415395592, "acc_norm": 0.7172995780590717, "acc_norm_stderr": 0.02931281415395592 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.6457399103139013, "acc_stderr": 0.032100621541349864, "acc_norm": 0.6457399103139013, "acc_norm_stderr": 0.032100621541349864 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.6335877862595419, "acc_stderr": 0.04225875451969637, "acc_norm": 0.6335877862595419, "acc_norm_stderr": 0.04225875451969637 }, "harness|hendrycksTest-international_law|5": { "acc": 0.768595041322314, "acc_stderr": 0.03849856098794089, "acc_norm": 0.768595041322314, "acc_norm_stderr": 0.03849856098794089 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.6944444444444444, "acc_stderr": 0.044531975073749834, "acc_norm": 0.6944444444444444, "acc_norm_stderr": 0.044531975073749834 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.6503067484662577, "acc_stderr": 0.037466683254700206, "acc_norm": 0.6503067484662577, "acc_norm_stderr": 0.037466683254700206 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.35714285714285715, "acc_stderr": 0.04547960999764376, "acc_norm": 0.35714285714285715, "acc_norm_stderr": 0.04547960999764376 }, "harness|hendrycksTest-management|5": { "acc": 0.7378640776699029, "acc_stderr": 0.04354631077260595, "acc_norm": 0.7378640776699029, "acc_norm_stderr": 0.04354631077260595 }, "harness|hendrycksTest-marketing|5": { "acc": 0.7863247863247863, "acc_stderr": 0.026853450377009175, "acc_norm": 0.7863247863247863, "acc_norm_stderr": 0.026853450377009175 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.57, "acc_stderr": 0.049756985195624284, "acc_norm": 0.57, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.7471264367816092, "acc_stderr": 0.015543377313719681, "acc_norm": 0.7471264367816092, "acc_norm_stderr": 0.015543377313719681 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.6127167630057804, "acc_stderr": 0.026226158605124655, "acc_norm": 0.6127167630057804, "acc_norm_stderr": 0.026226158605124655 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.3094972067039106, "acc_stderr": 0.015461169002371539, "acc_norm": 0.3094972067039106, "acc_norm_stderr": 0.015461169002371539 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.5947712418300654, "acc_stderr": 0.028110928492809068, "acc_norm": 0.5947712418300654, "acc_norm_stderr": 0.028110928492809068 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.5884244372990354, "acc_stderr": 0.02795048149440127, "acc_norm": 0.5884244372990354, "acc_norm_stderr": 0.02795048149440127 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.6111111111111112, "acc_stderr": 0.02712511551316687, "acc_norm": 0.6111111111111112, "acc_norm_stderr": 0.02712511551316687 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.3900709219858156, "acc_stderr": 0.029097675599463926, "acc_norm": 0.3900709219858156, "acc_norm_stderr": 0.029097675599463926 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.3917861799217731, "acc_stderr": 0.012467564418145121, "acc_norm": 0.3917861799217731, "acc_norm_stderr": 0.012467564418145121 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.5, "acc_stderr": 0.030372836961539352, "acc_norm": 0.5, "acc_norm_stderr": 0.030372836961539352 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.5441176470588235, "acc_stderr": 0.02014893942041574, "acc_norm": 0.5441176470588235, "acc_norm_stderr": 0.02014893942041574 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.6636363636363637, "acc_stderr": 0.04525393596302505, "acc_norm": 0.6636363636363637, "acc_norm_stderr": 0.04525393596302505 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.636734693877551, "acc_stderr": 0.030789051139030802, "acc_norm": 0.636734693877551, "acc_norm_stderr": 0.030789051139030802 }, "harness|hendrycksTest-sociology|5": { "acc": 0.7512437810945274, "acc_stderr": 0.030567675938916714, "acc_norm": 0.7512437810945274, "acc_norm_stderr": 0.030567675938916714 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.81, "acc_stderr": 0.03942772444036625, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036625 }, "harness|hendrycksTest-virology|5": { "acc": 0.4819277108433735, "acc_stderr": 0.038899512528272166, "acc_norm": 0.4819277108433735, "acc_norm_stderr": 0.038899512528272166 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.7309941520467836, "acc_stderr": 0.03401052620104089, "acc_norm": 0.7309941520467836, "acc_norm_stderr": 0.03401052620104089 }, "harness|truthfulqa:mc|0": { "mc1": 0.28518971848225216, "mc1_stderr": 0.015805827874454895, "mc2": 0.44118181192718914, "mc2_stderr": 0.01575597129997008 } } ``` ### 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]
HakaiNoRyuu/ds
2023-09-15T10:49:23.000Z
[ "region:us" ]
HakaiNoRyuu
null
null
null
0
0
Entry not found
maze/aigc
2023-09-23T11:33:09.000Z
[ "size_categories:10K<n<100K", "region:us" ]
maze
null
null
null
0
0
--- size_categories: - 10K<n<100K --- Asian photography dataset - [win3000](https://www.win3000.com/): about 18k asian celebrity photo. - [jiepaigou](http://www.jiepaigou.com/): streetsnap and celebrity - [cybesx](www.cybesx.com): about 13k street photography
BBGAME605065444/1
2023-09-15T11:12:50.000Z
[ "region:us" ]
BBGAME605065444
null
null
null
0
0
Entry not found
Juneuarie/QingqueEN
2023-09-15T11:14:56.000Z
[ "region:us" ]
Juneuarie
null
null
null
0
0
Entry not found
tiendung/chai
2023-09-15T22:31:13.000Z
[ "region:us" ]
tiendung
null
null
null
0
0
Entry not found
CyberHarem/ayase_honoka_idolmastercinderellagirls
2023-09-17T17:39:07.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of ayase_honoka (THE iDOLM@STER: Cinderella Girls) This is the dataset of ayase_honoka (THE iDOLM@STER: Cinderella Girls), containing 103 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 103 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 284 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 103 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 103 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 103 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 103 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 103 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 284 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 284 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 284 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset
2023-09-15T13:28:07.000Z
[ "license:other", "Movie Dialog", "Her The Movie", "Dialogs from the Her Movie (2013)", "region:us" ]
HaltiaAI
null
null
null
1
0
--- license: other tags: - Movie Dialog - Her The Movie - Dialogs from the Her Movie (2013) ---
CyberHarem/zaizen_tokiko_idolmastercinderellagirls
2023-09-17T17:39:09.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of zaizen_tokiko (THE iDOLM@STER: Cinderella Girls) This is the dataset of zaizen_tokiko (THE iDOLM@STER: Cinderella Girls), containing 145 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 145 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 374 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 145 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 145 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 145 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 145 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 145 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 374 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 374 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 374 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/yao_feifei_idolmastercinderellagirls
2023-09-17T17:39:11.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of yao_feifei (THE iDOLM@STER: Cinderella Girls) This is the dataset of yao_feifei (THE iDOLM@STER: Cinderella Girls), containing 37 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 37 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 103 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 37 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 37 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 37 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 37 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 37 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 103 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 103 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 103 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/koganeikoito_edomaeelf
2023-09-17T17:39:13.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of こがねいこいと This is the dataset of こがねいこいと, containing 300 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 300 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 631 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 300 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 300 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 300 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 300 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 300 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 631 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 631 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 631 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/kurokawa_chiaki_idolmastercinderellagirls
2023-09-17T17:39:15.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of kurokawa_chiaki (THE iDOLM@STER: Cinderella Girls) This is the dataset of kurokawa_chiaki (THE iDOLM@STER: Cinderella Girls), containing 64 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 64 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 162 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 64 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 64 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 64 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 64 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 64 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 162 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 162 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 162 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
Coroseven/KaguyaShinomiya
2023-09-17T12:42:16.000Z
[ "region:us" ]
Coroseven
null
null
null
0
0
Entry not found
DemiseKing/sdcos
2023-09-15T12:21:39.000Z
[ "license:openrail", "region:us" ]
DemiseKing
null
null
null
0
0
--- license: openrail ---
CyberHarem/eruda_edomaeelf
2023-09-17T17:39:17.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of エルダ This is the dataset of エルダ, containing 300 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 300 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 667 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 300 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 300 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 300 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 300 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 300 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 667 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 667 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 667 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/seki_hiromi_idolmastercinderellagirls
2023-09-17T17:39:19.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of seki_hiromi (THE iDOLM@STER: Cinderella Girls) This is the dataset of seki_hiromi (THE iDOLM@STER: Cinderella Girls), containing 115 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 115 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 297 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 115 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 115 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 115 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 115 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 115 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 297 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 297 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 297 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/saejima_kiyomi_idolmastercinderellagirls
2023-09-17T17:39:21.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of saejima_kiyomi (THE iDOLM@STER: Cinderella Girls) This is the dataset of saejima_kiyomi (THE iDOLM@STER: Cinderella Girls), containing 45 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 45 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 110 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 45 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 45 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 45 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 45 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 45 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 110 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 110 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 110 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/matsuyama_kumiko_idolmastercinderellagirls
2023-09-17T17:39:23.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of matsuyama_kumiko (THE iDOLM@STER: Cinderella Girls) This is the dataset of matsuyama_kumiko (THE iDOLM@STER: Cinderella Girls), containing 35 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 35 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 90 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 35 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 35 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 35 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 35 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 35 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 90 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 90 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 90 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/sakurabakoma_edomaeelf
2023-09-17T17:39:25.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of さくらばこま This is the dataset of さくらばこま, containing 94 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 94 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 209 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 94 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 94 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 94 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 94 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 94 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 209 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 209 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 209 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
open-llm-leaderboard/details_gpt2_public
2023-09-15T12:47:36.000Z
[ "region:us" ]
open-llm-leaderboard
null
null
null
0
0
--- pretty_name: Evaluation run of gpt2 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [gpt2](https://huggingface.co/gpt2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 1 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_gpt2_public\"\ ,\n\t\"harness_drop_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese\ \ are the [latest results from run 2023-09-15T12:47:31.231445](https://huggingface.co/datasets/open-llm-leaderboard/details_gpt2_public/blob/main/results_2023-09-15T12-47-31.231445.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\": 0.0,\n \"\ em_stderr\": 0.0,\n \"f1\": 0.039,\n \"f1_stderr\": 0.028301943396169812\n\ \ },\n \"harness|drop|0\": {\n \"em\": 0.0,\n \"em_stderr\"\ : 0.0,\n \"f1\": 0.039,\n \"f1_stderr\": 0.028301943396169812\n \ \ }\n}\n```" repo_url: https://huggingface.co/gpt2 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_drop_0 data_files: - split: 2023_09_15T12_47_31.231445 path: - '**/details_harness|drop|0_2023-09-15T12-47-31.231445.parquet' - split: latest path: - '**/details_harness|drop|0_2023-09-15T12-47-31.231445.parquet' - config_name: results data_files: - split: 2023_09_15T12_47_31.231445 path: - results_2023-09-15T12-47-31.231445.parquet - split: latest path: - results_2023-09-15T12-47-31.231445.parquet --- # Dataset Card for Evaluation run of gpt2 ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/gpt2 - **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 [gpt2](https://huggingface.co/gpt2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 1 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_gpt2_public", "harness_drop_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-15T12:47:31.231445](https://huggingface.co/datasets/open-llm-leaderboard/details_gpt2_public/blob/main/results_2023-09-15T12-47-31.231445.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": 0.0, "em_stderr": 0.0, "f1": 0.039, "f1_stderr": 0.028301943396169812 }, "harness|drop|0": { "em": 0.0, "em_stderr": 0.0, "f1": 0.039, "f1_stderr": 0.028301943396169812 } } ``` ### 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]
VanoInvestigations/BOE-1988-2022
2023-09-15T12:53:41.000Z
[ "region:us" ]
VanoInvestigations
null
null
null
0
0
Entry not found
CyberHarem/koganeikoyuzu_edomaeelf
2023-09-17T17:39:27.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of こがねいこゆず This is the dataset of こがねいこゆず, containing 80 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 80 | [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. | | 384x512 | 80 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 80 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 80 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 80 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 80 | [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. | | stage3-1200 | 182 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/nagatomi_hasumi_idolmastercinderellagirls
2023-09-17T17:39:30.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of nagatomi_hasumi (THE iDOLM@STER: Cinderella Girls) This is the dataset of nagatomi_hasumi (THE iDOLM@STER: Cinderella Girls), containing 42 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 42 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 111 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 42 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 42 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 42 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 42 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 42 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 111 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 111 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 111 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
bongo2112/diamondplatnumz-SDxl-output-images
2023-09-15T18:45:34.000Z
[ "region:us" ]
bongo2112
null
null
null
0
0
Entry not found
CyberHarem/wakiyama_tamami_idolmastercinderellagirls
2023-09-17T17:39:32.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of wakiyama_tamami (THE iDOLM@STER: Cinderella Girls) This is the dataset of wakiyama_tamami (THE iDOLM@STER: Cinderella Girls), containing 43 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 43 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 119 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 43 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 43 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 43 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 43 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 43 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 119 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 119 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 119 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
Ifra12/llama2
2023-09-15T13:28:09.000Z
[ "region:us" ]
Ifra12
null
null
null
0
0
Entry not found
CyberHarem/tsuchiya_ako_idolmastercinderellagirls
2023-09-17T17:39:34.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of tsuchiya_ako (THE iDOLM@STER: Cinderella Girls) This is the dataset of tsuchiya_ako (THE iDOLM@STER: Cinderella Girls), containing 33 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 33 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 88 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 33 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 33 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 33 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 33 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 33 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 88 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 88 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 88 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
TuningAI/Cover_letter_v2
2023-09-15T13:40:41.000Z
[ "region:us" ]
TuningAI
null
null
null
0
0
Entry not found
open-llm-leaderboard/details_elliotthwang__Elliott-Chinese-LLaMa-GPTQ-V1.0
2023-09-15T13:42:38.000Z
[ "region:us" ]
open-llm-leaderboard
null
null
null
0
0
--- pretty_name: Evaluation run of elliotthwang/Elliott-Chinese-LLaMa-GPTQ-V1.0 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [elliotthwang/Elliott-Chinese-LLaMa-GPTQ-V1.0](https://huggingface.co/elliotthwang/Elliott-Chinese-LLaMa-GPTQ-V1.0)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_elliotthwang__Elliott-Chinese-LLaMa-GPTQ-V1.0\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-15T13:41:24.143261](https://huggingface.co/datasets/open-llm-leaderboard/details_elliotthwang__Elliott-Chinese-LLaMa-GPTQ-V1.0/blob/main/results_2023-09-15T13-41-24.143261.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\": 0.49399597506549714,\n\ \ \"acc_stderr\": 0.03511123221635479,\n \"acc_norm\": 0.4979736893285183,\n\ \ \"acc_norm_stderr\": 0.03510066112158077,\n \"mc1\": 0.29253365973072215,\n\ \ \"mc1_stderr\": 0.015925597445286165,\n \"mc2\": 0.44703431694949036,\n\ \ \"mc2_stderr\": 0.014683290152252474\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.4667235494880546,\n \"acc_stderr\": 0.014578995859605813,\n\ \ \"acc_norm\": 0.5068259385665529,\n \"acc_norm_stderr\": 0.014610029151379813\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.5590519816769568,\n\ \ \"acc_stderr\": 0.0049548591067816545,\n \"acc_norm\": 0.7536347341167098,\n\ \ \"acc_norm_stderr\": 0.004300131223340694\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.27,\n \"acc_stderr\": 0.044619604333847415,\n \ \ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.044619604333847415\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.4444444444444444,\n\ \ \"acc_stderr\": 0.04292596718256981,\n \"acc_norm\": 0.4444444444444444,\n\ \ \"acc_norm_stderr\": 0.04292596718256981\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.5197368421052632,\n \"acc_stderr\": 0.04065771002562605,\n\ \ \"acc_norm\": 0.5197368421052632,\n \"acc_norm_stderr\": 0.04065771002562605\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.5,\n\ \ \"acc_stderr\": 0.050251890762960605,\n \"acc_norm\": 0.5,\n \ \ \"acc_norm_stderr\": 0.050251890762960605\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.5320754716981132,\n \"acc_stderr\": 0.03070948699255655,\n\ \ \"acc_norm\": 0.5320754716981132,\n \"acc_norm_stderr\": 0.03070948699255655\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.5069444444444444,\n\ \ \"acc_stderr\": 0.04180806750294938,\n \"acc_norm\": 0.5069444444444444,\n\ \ \"acc_norm_stderr\": 0.04180806750294938\n },\n \"harness|hendrycksTest-college_chemistry|5\"\ : {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \ \ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \ \ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\ : 0.45,\n \"acc_stderr\": 0.049999999999999996,\n \"acc_norm\": 0.45,\n\ \ \"acc_norm_stderr\": 0.049999999999999996\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.32,\n \"acc_stderr\": 0.04688261722621505,\n \ \ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.04688261722621505\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.4393063583815029,\n\ \ \"acc_stderr\": 0.037842719328874674,\n \"acc_norm\": 0.4393063583815029,\n\ \ \"acc_norm_stderr\": 0.037842719328874674\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.2549019607843137,\n \"acc_stderr\": 0.043364327079931785,\n\ \ \"acc_norm\": 0.2549019607843137,\n \"acc_norm_stderr\": 0.043364327079931785\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.58,\n \"acc_stderr\": 0.049604496374885836,\n \"acc_norm\": 0.58,\n\ \ \"acc_norm_stderr\": 0.049604496374885836\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.3702127659574468,\n \"acc_stderr\": 0.03156564682236784,\n\ \ \"acc_norm\": 0.3702127659574468,\n \"acc_norm_stderr\": 0.03156564682236784\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.3157894736842105,\n\ \ \"acc_stderr\": 0.04372748290278007,\n \"acc_norm\": 0.3157894736842105,\n\ \ \"acc_norm_stderr\": 0.04372748290278007\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.4482758620689655,\n \"acc_stderr\": 0.04144311810878152,\n\ \ \"acc_norm\": 0.4482758620689655,\n \"acc_norm_stderr\": 0.04144311810878152\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.29365079365079366,\n \"acc_stderr\": 0.023456037383982026,\n \"\ acc_norm\": 0.29365079365079366,\n \"acc_norm_stderr\": 0.023456037383982026\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.30952380952380953,\n\ \ \"acc_stderr\": 0.04134913018303316,\n \"acc_norm\": 0.30952380952380953,\n\ \ \"acc_norm_stderr\": 0.04134913018303316\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.04923659639173309,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.04923659639173309\n },\n\ \ \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.5612903225806452,\n\ \ \"acc_stderr\": 0.028229497320317213,\n \"acc_norm\": 0.5612903225806452,\n\ \ \"acc_norm_stderr\": 0.028229497320317213\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.3251231527093596,\n \"acc_stderr\": 0.032957975663112704,\n\ \ \"acc_norm\": 0.3251231527093596,\n \"acc_norm_stderr\": 0.032957975663112704\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \"acc_norm\"\ : 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.6545454545454545,\n \"acc_stderr\": 0.03713158067481913,\n\ \ \"acc_norm\": 0.6545454545454545,\n \"acc_norm_stderr\": 0.03713158067481913\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.6262626262626263,\n \"acc_stderr\": 0.03446897738659333,\n \"\ acc_norm\": 0.6262626262626263,\n \"acc_norm_stderr\": 0.03446897738659333\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.7202072538860104,\n \"acc_stderr\": 0.03239637046735704,\n\ \ \"acc_norm\": 0.7202072538860104,\n \"acc_norm_stderr\": 0.03239637046735704\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.4461538461538462,\n \"acc_stderr\": 0.02520357177302833,\n \ \ \"acc_norm\": 0.4461538461538462,\n \"acc_norm_stderr\": 0.02520357177302833\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.24444444444444444,\n \"acc_stderr\": 0.02620276653465215,\n \ \ \"acc_norm\": 0.24444444444444444,\n \"acc_norm_stderr\": 0.02620276653465215\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.4327731092436975,\n \"acc_stderr\": 0.03218358107742613,\n \ \ \"acc_norm\": 0.4327731092436975,\n \"acc_norm_stderr\": 0.03218358107742613\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.3443708609271523,\n \"acc_stderr\": 0.038796870240733264,\n \"\ acc_norm\": 0.3443708609271523,\n \"acc_norm_stderr\": 0.038796870240733264\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.6788990825688074,\n \"acc_stderr\": 0.02001814977273375,\n \"\ acc_norm\": 0.6788990825688074,\n \"acc_norm_stderr\": 0.02001814977273375\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.35185185185185186,\n \"acc_stderr\": 0.03256850570293647,\n \"\ acc_norm\": 0.35185185185185186,\n \"acc_norm_stderr\": 0.03256850570293647\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.6127450980392157,\n \"acc_stderr\": 0.03418931233833344,\n \"\ acc_norm\": 0.6127450980392157,\n \"acc_norm_stderr\": 0.03418931233833344\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.6666666666666666,\n \"acc_stderr\": 0.030685820596610795,\n \ \ \"acc_norm\": 0.6666666666666666,\n \"acc_norm_stderr\": 0.030685820596610795\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.5919282511210763,\n\ \ \"acc_stderr\": 0.03298574607842821,\n \"acc_norm\": 0.5919282511210763,\n\ \ \"acc_norm_stderr\": 0.03298574607842821\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.648854961832061,\n \"acc_stderr\": 0.04186445163013751,\n\ \ \"acc_norm\": 0.648854961832061,\n \"acc_norm_stderr\": 0.04186445163013751\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.6528925619834711,\n \"acc_stderr\": 0.043457245702925335,\n \"\ acc_norm\": 0.6528925619834711,\n \"acc_norm_stderr\": 0.043457245702925335\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.5555555555555556,\n\ \ \"acc_stderr\": 0.04803752235190193,\n \"acc_norm\": 0.5555555555555556,\n\ \ \"acc_norm_stderr\": 0.04803752235190193\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.5521472392638037,\n \"acc_stderr\": 0.03906947479456606,\n\ \ \"acc_norm\": 0.5521472392638037,\n \"acc_norm_stderr\": 0.03906947479456606\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.3392857142857143,\n\ \ \"acc_stderr\": 0.04493949068613539,\n \"acc_norm\": 0.3392857142857143,\n\ \ \"acc_norm_stderr\": 0.04493949068613539\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.6310679611650486,\n \"acc_stderr\": 0.0477761518115674,\n\ \ \"acc_norm\": 0.6310679611650486,\n \"acc_norm_stderr\": 0.0477761518115674\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.7521367521367521,\n\ \ \"acc_stderr\": 0.028286324075564393,\n \"acc_norm\": 0.7521367521367521,\n\ \ \"acc_norm_stderr\": 0.028286324075564393\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.59,\n \"acc_stderr\": 0.049431107042371025,\n \ \ \"acc_norm\": 0.59,\n \"acc_norm_stderr\": 0.049431107042371025\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.6896551724137931,\n\ \ \"acc_stderr\": 0.01654378502604831,\n \"acc_norm\": 0.6896551724137931,\n\ \ \"acc_norm_stderr\": 0.01654378502604831\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.5028901734104047,\n \"acc_stderr\": 0.026918645383239004,\n\ \ \"acc_norm\": 0.5028901734104047,\n \"acc_norm_stderr\": 0.026918645383239004\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.2770949720670391,\n\ \ \"acc_stderr\": 0.014968772435812145,\n \"acc_norm\": 0.2770949720670391,\n\ \ \"acc_norm_stderr\": 0.014968772435812145\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.5620915032679739,\n \"acc_stderr\": 0.02840830202033269,\n\ \ \"acc_norm\": 0.5620915032679739,\n \"acc_norm_stderr\": 0.02840830202033269\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.572347266881029,\n\ \ \"acc_stderr\": 0.02809924077580956,\n \"acc_norm\": 0.572347266881029,\n\ \ \"acc_norm_stderr\": 0.02809924077580956\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.5679012345679012,\n \"acc_stderr\": 0.027563010971606676,\n\ \ \"acc_norm\": 0.5679012345679012,\n \"acc_norm_stderr\": 0.027563010971606676\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.3546099290780142,\n \"acc_stderr\": 0.02853865002887864,\n \ \ \"acc_norm\": 0.3546099290780142,\n \"acc_norm_stderr\": 0.02853865002887864\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.34159061277705344,\n\ \ \"acc_stderr\": 0.012112391320842849,\n \"acc_norm\": 0.34159061277705344,\n\ \ \"acc_norm_stderr\": 0.012112391320842849\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.5110294117647058,\n \"acc_stderr\": 0.030365446477275675,\n\ \ \"acc_norm\": 0.5110294117647058,\n \"acc_norm_stderr\": 0.030365446477275675\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.47058823529411764,\n \"acc_stderr\": 0.02019280827143379,\n \ \ \"acc_norm\": 0.47058823529411764,\n \"acc_norm_stderr\": 0.02019280827143379\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.5,\n\ \ \"acc_stderr\": 0.04789131426105757,\n \"acc_norm\": 0.5,\n \ \ \"acc_norm_stderr\": 0.04789131426105757\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.5142857142857142,\n \"acc_stderr\": 0.03199615232806286,\n\ \ \"acc_norm\": 0.5142857142857142,\n \"acc_norm_stderr\": 0.03199615232806286\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.7014925373134329,\n\ \ \"acc_stderr\": 0.03235743789355041,\n \"acc_norm\": 0.7014925373134329,\n\ \ \"acc_norm_stderr\": 0.03235743789355041\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.68,\n \"acc_stderr\": 0.04688261722621505,\n \ \ \"acc_norm\": 0.68,\n \"acc_norm_stderr\": 0.04688261722621505\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.45180722891566266,\n\ \ \"acc_stderr\": 0.03874371556587953,\n \"acc_norm\": 0.45180722891566266,\n\ \ \"acc_norm_stderr\": 0.03874371556587953\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.7485380116959064,\n \"acc_stderr\": 0.033275044238468436,\n\ \ \"acc_norm\": 0.7485380116959064,\n \"acc_norm_stderr\": 0.033275044238468436\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.29253365973072215,\n\ \ \"mc1_stderr\": 0.015925597445286165,\n \"mc2\": 0.44703431694949036,\n\ \ \"mc2_stderr\": 0.014683290152252474\n }\n}\n```" repo_url: https://huggingface.co/elliotthwang/Elliott-Chinese-LLaMa-GPTQ-V1.0 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|arc:challenge|25_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hellaswag|10_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-15T13-41-24.143261.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-management|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-virology|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T13-41-24.143261.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_15T13_41_24.143261 path: - '**/details_harness|truthfulqa:mc|0_2023-09-15T13-41-24.143261.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-09-15T13-41-24.143261.parquet' - config_name: results data_files: - split: 2023_09_15T13_41_24.143261 path: - results_2023-09-15T13-41-24.143261.parquet - split: latest path: - results_2023-09-15T13-41-24.143261.parquet --- # Dataset Card for Evaluation run of elliotthwang/Elliott-Chinese-LLaMa-GPTQ-V1.0 ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/elliotthwang/Elliott-Chinese-LLaMa-GPTQ-V1.0 - **Paper:** - **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard - **Point of Contact:** clementine@hf.co ### Dataset Summary Dataset automatically created during the evaluation run of model [elliotthwang/Elliott-Chinese-LLaMa-GPTQ-V1.0](https://huggingface.co/elliotthwang/Elliott-Chinese-LLaMa-GPTQ-V1.0) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_elliotthwang__Elliott-Chinese-LLaMa-GPTQ-V1.0", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-15T13:41:24.143261](https://huggingface.co/datasets/open-llm-leaderboard/details_elliotthwang__Elliott-Chinese-LLaMa-GPTQ-V1.0/blob/main/results_2023-09-15T13-41-24.143261.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": 0.49399597506549714, "acc_stderr": 0.03511123221635479, "acc_norm": 0.4979736893285183, "acc_norm_stderr": 0.03510066112158077, "mc1": 0.29253365973072215, "mc1_stderr": 0.015925597445286165, "mc2": 0.44703431694949036, "mc2_stderr": 0.014683290152252474 }, "harness|arc:challenge|25": { "acc": 0.4667235494880546, "acc_stderr": 0.014578995859605813, "acc_norm": 0.5068259385665529, "acc_norm_stderr": 0.014610029151379813 }, "harness|hellaswag|10": { "acc": 0.5590519816769568, "acc_stderr": 0.0049548591067816545, "acc_norm": 0.7536347341167098, "acc_norm_stderr": 0.004300131223340694 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.27, "acc_stderr": 0.044619604333847415, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847415 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4444444444444444, "acc_stderr": 0.04292596718256981, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.04292596718256981 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5197368421052632, "acc_stderr": 0.04065771002562605, "acc_norm": 0.5197368421052632, "acc_norm_stderr": 0.04065771002562605 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5320754716981132, "acc_stderr": 0.03070948699255655, "acc_norm": 0.5320754716981132, "acc_norm_stderr": 0.03070948699255655 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5069444444444444, "acc_stderr": 0.04180806750294938, "acc_norm": 0.5069444444444444, "acc_norm_stderr": 0.04180806750294938 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.45, "acc_stderr": 0.049999999999999996, "acc_norm": 0.45, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621505, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4393063583815029, "acc_stderr": 0.037842719328874674, "acc_norm": 0.4393063583815029, "acc_norm_stderr": 0.037842719328874674 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.2549019607843137, "acc_stderr": 0.043364327079931785, "acc_norm": 0.2549019607843137, "acc_norm_stderr": 0.043364327079931785 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3702127659574468, "acc_stderr": 0.03156564682236784, "acc_norm": 0.3702127659574468, "acc_norm_stderr": 0.03156564682236784 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3157894736842105, "acc_stderr": 0.04372748290278007, "acc_norm": 0.3157894736842105, "acc_norm_stderr": 0.04372748290278007 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4482758620689655, "acc_stderr": 0.04144311810878152, "acc_norm": 0.4482758620689655, "acc_norm_stderr": 0.04144311810878152 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.29365079365079366, "acc_stderr": 0.023456037383982026, "acc_norm": 0.29365079365079366, "acc_norm_stderr": 0.023456037383982026 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.30952380952380953, "acc_stderr": 0.04134913018303316, "acc_norm": 0.30952380952380953, "acc_norm_stderr": 0.04134913018303316 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5612903225806452, "acc_stderr": 0.028229497320317213, "acc_norm": 0.5612903225806452, "acc_norm_stderr": 0.028229497320317213 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3251231527093596, "acc_stderr": 0.032957975663112704, "acc_norm": 0.3251231527093596, "acc_norm_stderr": 0.032957975663112704 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6545454545454545, "acc_stderr": 0.03713158067481913, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.03713158067481913 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6262626262626263, "acc_stderr": 0.03446897738659333, "acc_norm": 0.6262626262626263, "acc_norm_stderr": 0.03446897738659333 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7202072538860104, "acc_stderr": 0.03239637046735704, "acc_norm": 0.7202072538860104, "acc_norm_stderr": 0.03239637046735704 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4461538461538462, "acc_stderr": 0.02520357177302833, "acc_norm": 0.4461538461538462, "acc_norm_stderr": 0.02520357177302833 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.24444444444444444, "acc_stderr": 0.02620276653465215, "acc_norm": 0.24444444444444444, "acc_norm_stderr": 0.02620276653465215 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.4327731092436975, "acc_stderr": 0.03218358107742613, "acc_norm": 0.4327731092436975, "acc_norm_stderr": 0.03218358107742613 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.3443708609271523, "acc_stderr": 0.038796870240733264, "acc_norm": 0.3443708609271523, "acc_norm_stderr": 0.038796870240733264 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.6788990825688074, "acc_stderr": 0.02001814977273375, "acc_norm": 0.6788990825688074, "acc_norm_stderr": 0.02001814977273375 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.35185185185185186, "acc_stderr": 0.03256850570293647, "acc_norm": 0.35185185185185186, "acc_norm_stderr": 0.03256850570293647 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.6127450980392157, "acc_stderr": 0.03418931233833344, "acc_norm": 0.6127450980392157, "acc_norm_stderr": 0.03418931233833344 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.6666666666666666, "acc_stderr": 0.030685820596610795, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.030685820596610795 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.5919282511210763, "acc_stderr": 0.03298574607842821, "acc_norm": 0.5919282511210763, "acc_norm_stderr": 0.03298574607842821 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.648854961832061, "acc_stderr": 0.04186445163013751, "acc_norm": 0.648854961832061, "acc_norm_stderr": 0.04186445163013751 }, "harness|hendrycksTest-international_law|5": { "acc": 0.6528925619834711, "acc_stderr": 0.043457245702925335, "acc_norm": 0.6528925619834711, "acc_norm_stderr": 0.043457245702925335 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.5555555555555556, "acc_stderr": 0.04803752235190193, "acc_norm": 0.5555555555555556, "acc_norm_stderr": 0.04803752235190193 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.5521472392638037, "acc_stderr": 0.03906947479456606, "acc_norm": 0.5521472392638037, "acc_norm_stderr": 0.03906947479456606 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.3392857142857143, "acc_stderr": 0.04493949068613539, "acc_norm": 0.3392857142857143, "acc_norm_stderr": 0.04493949068613539 }, "harness|hendrycksTest-management|5": { "acc": 0.6310679611650486, "acc_stderr": 0.0477761518115674, "acc_norm": 0.6310679611650486, "acc_norm_stderr": 0.0477761518115674 }, "harness|hendrycksTest-marketing|5": { "acc": 0.7521367521367521, "acc_stderr": 0.028286324075564393, "acc_norm": 0.7521367521367521, "acc_norm_stderr": 0.028286324075564393 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.59, "acc_stderr": 0.049431107042371025, "acc_norm": 0.59, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.6896551724137931, "acc_stderr": 0.01654378502604831, "acc_norm": 0.6896551724137931, "acc_norm_stderr": 0.01654378502604831 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.5028901734104047, "acc_stderr": 0.026918645383239004, "acc_norm": 0.5028901734104047, "acc_norm_stderr": 0.026918645383239004 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.2770949720670391, "acc_stderr": 0.014968772435812145, "acc_norm": 0.2770949720670391, "acc_norm_stderr": 0.014968772435812145 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.5620915032679739, "acc_stderr": 0.02840830202033269, "acc_norm": 0.5620915032679739, "acc_norm_stderr": 0.02840830202033269 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.572347266881029, "acc_stderr": 0.02809924077580956, "acc_norm": 0.572347266881029, "acc_norm_stderr": 0.02809924077580956 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.5679012345679012, "acc_stderr": 0.027563010971606676, "acc_norm": 0.5679012345679012, "acc_norm_stderr": 0.027563010971606676 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.3546099290780142, "acc_stderr": 0.02853865002887864, "acc_norm": 0.3546099290780142, "acc_norm_stderr": 0.02853865002887864 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.34159061277705344, "acc_stderr": 0.012112391320842849, "acc_norm": 0.34159061277705344, "acc_norm_stderr": 0.012112391320842849 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.5110294117647058, "acc_stderr": 0.030365446477275675, "acc_norm": 0.5110294117647058, "acc_norm_stderr": 0.030365446477275675 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.47058823529411764, "acc_stderr": 0.02019280827143379, "acc_norm": 0.47058823529411764, "acc_norm_stderr": 0.02019280827143379 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.5, "acc_stderr": 0.04789131426105757, "acc_norm": 0.5, "acc_norm_stderr": 0.04789131426105757 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.5142857142857142, "acc_stderr": 0.03199615232806286, "acc_norm": 0.5142857142857142, "acc_norm_stderr": 0.03199615232806286 }, "harness|hendrycksTest-sociology|5": { "acc": 0.7014925373134329, "acc_stderr": 0.03235743789355041, "acc_norm": 0.7014925373134329, "acc_norm_stderr": 0.03235743789355041 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.68, "acc_stderr": 0.04688261722621505, "acc_norm": 0.68, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-virology|5": { "acc": 0.45180722891566266, "acc_stderr": 0.03874371556587953, "acc_norm": 0.45180722891566266, "acc_norm_stderr": 0.03874371556587953 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.7485380116959064, "acc_stderr": 0.033275044238468436, "acc_norm": 0.7485380116959064, "acc_norm_stderr": 0.033275044238468436 }, "harness|truthfulqa:mc|0": { "mc1": 0.29253365973072215, "mc1_stderr": 0.015925597445286165, "mc2": 0.44703431694949036, "mc2_stderr": 0.014683290152252474 } } ``` ### 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]
CyberHarem/wakui_rumi_idolmastercinderellagirls
2023-09-17T17:39:36.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of wakui_rumi (THE iDOLM@STER: Cinderella Girls) This is the dataset of wakui_rumi (THE iDOLM@STER: Cinderella Girls), containing 35 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 35 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 96 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 35 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 35 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 35 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 35 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 35 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 96 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 96 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 96 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
Krinx/edm.txt
2023-09-15T13:58:31.000Z
[ "region:us" ]
Krinx
null
null
null
0
0
Entry not found
CyberHarem/kitami_yuzu_idolmastercinderellagirls
2023-09-17T17:39:38.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of kitami_yuzu (THE iDOLM@STER: Cinderella Girls) This is the dataset of kitami_yuzu (THE iDOLM@STER: Cinderella Girls), containing 156 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 156 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 422 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 156 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 156 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 156 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 156 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 156 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 422 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 422 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 422 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/ebihara_naho_idolmastercinderellagirls
2023-09-17T17:39:40.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of ebihara_naho (THE iDOLM@STER: Cinderella Girls) This is the dataset of ebihara_naho (THE iDOLM@STER: Cinderella Girls), containing 78 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 78 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 222 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 78 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 78 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 78 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 78 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 78 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 222 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 222 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 222 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/kudou_shinobu_idolmastercinderellagirls
2023-09-17T17:39:42.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of kudou_shinobu (THE iDOLM@STER: Cinderella Girls) This is the dataset of kudou_shinobu (THE iDOLM@STER: Cinderella Girls), containing 30 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 30 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 81 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 30 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 30 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 30 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 30 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 30 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 81 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 81 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 81 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/matsumoto_sarina_idolmastercinderellagirls
2023-09-17T17:39:44.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of matsumoto_sarina (THE iDOLM@STER: Cinderella Girls) This is the dataset of matsumoto_sarina (THE iDOLM@STER: Cinderella Girls), containing 69 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 69 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 180 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 69 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 69 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 69 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 69 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 69 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 180 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 180 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 180 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
rkparalian/autotrain-data-12
2023-09-15T14:49:42.000Z
[ "region:us" ]
rkparalian
null
null
null
0
0
Entry not found
CyberHarem/namiki_meiko_idolmastercinderellagirls
2023-09-17T17:39:46.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of namiki_meiko (THE iDOLM@STER: Cinderella Girls) This is the dataset of namiki_meiko (THE iDOLM@STER: Cinderella Girls), containing 34 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 34 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 91 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 34 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 34 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 34 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 34 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 34 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 91 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 91 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 91 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
dabdib/collections
2023-09-21T14:38:25.000Z
[ "region:us" ]
dabdib
null
null
null
0
0
Entry not found
CyberHarem/fujii_tomo_idolmastercinderellagirls
2023-09-17T17:39:48.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of fujii_tomo (THE iDOLM@STER: Cinderella Girls) This is the dataset of fujii_tomo (THE iDOLM@STER: Cinderella Girls), containing 50 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 50 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 127 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 50 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 50 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 50 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 50 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 50 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 127 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 127 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 127 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/nishikawa_honami_idolmastercinderellagirls
2023-09-17T17:39:50.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of nishikawa_honami (THE iDOLM@STER: Cinderella Girls) This is the dataset of nishikawa_honami (THE iDOLM@STER: Cinderella Girls), containing 25 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 25 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 63 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 25 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 25 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 25 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 25 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 25 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 63 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 63 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 63 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/eve_santaclaus_idolmastercinderellagirls
2023-09-17T17:39:52.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of eve_santaclaus (THE iDOLM@STER: Cinderella Girls) This is the dataset of eve_santaclaus (THE iDOLM@STER: Cinderella Girls), containing 98 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 98 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 269 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 98 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 98 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 98 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 98 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 98 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 269 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 269 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 269 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/hiiragi_shino_idolmastercinderellagirls
2023-09-17T17:39:54.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of hiiragi_shino (THE iDOLM@STER: Cinderella Girls) This is the dataset of hiiragi_shino (THE iDOLM@STER: Cinderella Girls), containing 42 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 42 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 112 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 42 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 42 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 42 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 42 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 42 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 112 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 112 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 112 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
anton-l/swh_missing_repos
2023-09-15T15:46:10.000Z
[ "region:us" ]
anton-l
null
null
null
0
0
Entry not found
fffiloni/new_dataset
2023-09-15T15:46:59.000Z
[ "region:us" ]
fffiloni
null
null
null
0
0
--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 848679.0 num_examples: 2 download_size: 848790 dataset_size: 848679.0 --- # Dataset Card for "new_dataset" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
CyberHarem/saitou_youko_idolmastercinderellagirls
2023-09-17T17:39:57.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of saitou_youko (THE iDOLM@STER: Cinderella Girls) This is the dataset of saitou_youko (THE iDOLM@STER: Cinderella Girls), containing 22 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 22 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 61 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 22 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 22 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 22 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 22 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 22 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 61 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 61 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 61 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/kitagawa_mahiro_idolmastercinderellagirls
2023-09-17T17:39:59.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of kitagawa_mahiro (THE iDOLM@STER: Cinderella Girls) This is the dataset of kitagawa_mahiro (THE iDOLM@STER: Cinderella Girls), containing 22 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 22 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 60 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 22 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 22 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 22 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 22 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 22 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 60 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 60 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 60 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
shijli/wmt14-deen
2023-09-16T15:44:08.000Z
[ "region:us" ]
shijli
null
null
null
0
0
# WMT 2014 German-English Translation Dataset This dataset was built with the fairseq's processing script, which can be original found [here](https://github.com/facebookresearch/fairseq/blob/main/examples/translation/prepare-wmt14en2de.sh) You can create this dataset by simply run: ```commandline git clone https://huggingface.co/datasets/shijli/wmt14-deen cd wmt14-deen/data bash prepare-wmt14.sh ``` `binarized.dist.de-en.zip` and `binarized.dist.en-de.zip` are distilled datasets generated by a transformer base model. It can be built by running: ```commandline bash prepare-wmt14-distill.sh /path/to/fairseq/model source-lang target-lang ``` To build this dataset, you need to create `binarized.zip` first. Note that the distilled dataset only uses model-generated target sentences, which means that different translation directions result in different datasets. Therefore, you need to specify `source-lang` and `target-lang` explicitly. Also, you need to replace `/path/to/fairseq/model` with the path of your pretrained model.
open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v2
2023-09-15T16:07:38.000Z
[ "region:us" ]
open-llm-leaderboard
null
null
null
0
0
--- pretty_name: Evaluation run of oh-yeontaek/llama-2-70B-LoRA-assemble-v2 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [oh-yeontaek/llama-2-70B-LoRA-assemble-v2](https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v2)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v2\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-15T16:06:18.387785](https://huggingface.co/datasets/open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v2/blob/main/results_2023-09-15T16-06-18.387785.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\": 0.6931761249212157,\n\ \ \"acc_stderr\": 0.031300161246260914,\n \"acc_norm\": 0.6971025131327819,\n\ \ \"acc_norm_stderr\": 0.03127024725201448,\n \"mc1\": 0.4663402692778458,\n\ \ \"mc1_stderr\": 0.01746379386716811,\n \"mc2\": 0.6478807414957388,\n\ \ \"mc2_stderr\": 0.014914964973799093\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6834470989761092,\n \"acc_stderr\": 0.013592431519068079,\n\ \ \"acc_norm\": 0.7184300341296929,\n \"acc_norm_stderr\": 0.013143376735009022\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6721768571997611,\n\ \ \"acc_stderr\": 0.0046846063106423304,\n \"acc_norm\": 0.8688508265285799,\n\ \ \"acc_norm_stderr\": 0.00336873543416138\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.43,\n \"acc_stderr\": 0.049756985195624284,\n \ \ \"acc_norm\": 0.43,\n \"acc_norm_stderr\": 0.049756985195624284\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6148148148148148,\n\ \ \"acc_stderr\": 0.042039210401562783,\n \"acc_norm\": 0.6148148148148148,\n\ \ \"acc_norm_stderr\": 0.042039210401562783\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.7828947368421053,\n \"acc_stderr\": 0.03355045304882924,\n\ \ \"acc_norm\": 0.7828947368421053,\n \"acc_norm_stderr\": 0.03355045304882924\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.75,\n\ \ \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\": 0.75,\n \ \ \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.7433962264150943,\n \"acc_stderr\": 0.02688064788905199,\n\ \ \"acc_norm\": 0.7433962264150943,\n \"acc_norm_stderr\": 0.02688064788905199\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8194444444444444,\n\ \ \"acc_stderr\": 0.03216600808802267,\n \"acc_norm\": 0.8194444444444444,\n\ \ \"acc_norm_stderr\": 0.03216600808802267\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\": 0.61,\n \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\"\ : 0.61,\n \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.36,\n \"acc_stderr\": 0.048241815132442176,\n \ \ \"acc_norm\": 0.36,\n \"acc_norm_stderr\": 0.048241815132442176\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6589595375722543,\n\ \ \"acc_stderr\": 0.036146654241808254,\n \"acc_norm\": 0.6589595375722543,\n\ \ \"acc_norm_stderr\": 0.036146654241808254\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\":\ \ 0.74,\n \"acc_stderr\": 0.04408440022768078,\n \"acc_norm\": 0.74,\n\ \ \"acc_norm_stderr\": 0.04408440022768078\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.6553191489361702,\n \"acc_stderr\": 0.031068985963122145,\n\ \ \"acc_norm\": 0.6553191489361702,\n \"acc_norm_stderr\": 0.031068985963122145\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.41228070175438597,\n\ \ \"acc_stderr\": 0.04630653203366595,\n \"acc_norm\": 0.41228070175438597,\n\ \ \"acc_norm_stderr\": 0.04630653203366595\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.6344827586206897,\n \"acc_stderr\": 0.04013124195424386,\n\ \ \"acc_norm\": 0.6344827586206897,\n \"acc_norm_stderr\": 0.04013124195424386\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.4656084656084656,\n \"acc_stderr\": 0.02569032176249384,\n \"\ acc_norm\": 0.4656084656084656,\n \"acc_norm_stderr\": 0.02569032176249384\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.4603174603174603,\n\ \ \"acc_stderr\": 0.04458029125470973,\n \"acc_norm\": 0.4603174603174603,\n\ \ \"acc_norm_stderr\": 0.04458029125470973\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.47,\n \"acc_stderr\": 0.05016135580465919,\n \ \ \"acc_norm\": 0.47,\n \"acc_norm_stderr\": 0.05016135580465919\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.832258064516129,\n\ \ \"acc_stderr\": 0.021255464065371314,\n \"acc_norm\": 0.832258064516129,\n\ \ \"acc_norm_stderr\": 0.021255464065371314\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.5467980295566502,\n \"acc_stderr\": 0.03502544650845872,\n\ \ \"acc_norm\": 0.5467980295566502,\n \"acc_norm_stderr\": 0.03502544650845872\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|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-high_school_european_history|5\"\ : {\n \"acc\": 0.8303030303030303,\n \"acc_stderr\": 0.02931118867498312,\n\ \ \"acc_norm\": 0.8303030303030303,\n \"acc_norm_stderr\": 0.02931118867498312\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.9040404040404041,\n \"acc_stderr\": 0.020984808610047933,\n \"\ acc_norm\": 0.9040404040404041,\n \"acc_norm_stderr\": 0.020984808610047933\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.927461139896373,\n \"acc_stderr\": 0.018718998520678178,\n\ \ \"acc_norm\": 0.927461139896373,\n \"acc_norm_stderr\": 0.018718998520678178\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6974358974358974,\n \"acc_stderr\": 0.02329088805377272,\n \ \ \"acc_norm\": 0.6974358974358974,\n \"acc_norm_stderr\": 0.02329088805377272\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.32592592592592595,\n \"acc_stderr\": 0.028578348365473072,\n \ \ \"acc_norm\": 0.32592592592592595,\n \"acc_norm_stderr\": 0.028578348365473072\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.7815126050420168,\n \"acc_stderr\": 0.026841514322958934,\n\ \ \"acc_norm\": 0.7815126050420168,\n \"acc_norm_stderr\": 0.026841514322958934\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.47019867549668876,\n \"acc_stderr\": 0.040752249922169775,\n \"\ acc_norm\": 0.47019867549668876,\n \"acc_norm_stderr\": 0.040752249922169775\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8844036697247707,\n \"acc_stderr\": 0.013708749534172636,\n \"\ acc_norm\": 0.8844036697247707,\n \"acc_norm_stderr\": 0.013708749534172636\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5648148148148148,\n \"acc_stderr\": 0.033812000056435254,\n \"\ acc_norm\": 0.5648148148148148,\n \"acc_norm_stderr\": 0.033812000056435254\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.8970588235294118,\n \"acc_stderr\": 0.021328337570804365,\n \"\ acc_norm\": 0.8970588235294118,\n \"acc_norm_stderr\": 0.021328337570804365\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.8776371308016878,\n \"acc_stderr\": 0.02133174182974679,\n \ \ \"acc_norm\": 0.8776371308016878,\n \"acc_norm_stderr\": 0.02133174182974679\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7668161434977578,\n\ \ \"acc_stderr\": 0.028380391147094706,\n \"acc_norm\": 0.7668161434977578,\n\ \ \"acc_norm_stderr\": 0.028380391147094706\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.8244274809160306,\n \"acc_stderr\": 0.03336820338476073,\n\ \ \"acc_norm\": 0.8244274809160306,\n \"acc_norm_stderr\": 0.03336820338476073\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.8512396694214877,\n \"acc_stderr\": 0.03248470083807194,\n \"\ acc_norm\": 0.8512396694214877,\n \"acc_norm_stderr\": 0.03248470083807194\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8333333333333334,\n\ \ \"acc_stderr\": 0.03602814176392645,\n \"acc_norm\": 0.8333333333333334,\n\ \ \"acc_norm_stderr\": 0.03602814176392645\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.8220858895705522,\n \"acc_stderr\": 0.03004735765580663,\n\ \ \"acc_norm\": 0.8220858895705522,\n \"acc_norm_stderr\": 0.03004735765580663\n\ \ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.49107142857142855,\n\ \ \"acc_stderr\": 0.04745033255489123,\n \"acc_norm\": 0.49107142857142855,\n\ \ \"acc_norm_stderr\": 0.04745033255489123\n },\n \"harness|hendrycksTest-management|5\"\ : {\n \"acc\": 0.8252427184466019,\n \"acc_stderr\": 0.0376017800602662,\n\ \ \"acc_norm\": 0.8252427184466019,\n \"acc_norm_stderr\": 0.0376017800602662\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8888888888888888,\n\ \ \"acc_stderr\": 0.02058849131609238,\n \"acc_norm\": 0.8888888888888888,\n\ \ \"acc_norm_stderr\": 0.02058849131609238\n },\n \"harness|hendrycksTest-medical_genetics|5\"\ : {\n \"acc\": 0.71,\n \"acc_stderr\": 0.04560480215720684,\n \ \ \"acc_norm\": 0.71,\n \"acc_norm_stderr\": 0.04560480215720684\n \ \ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8659003831417624,\n\ \ \"acc_stderr\": 0.012185528166499983,\n \"acc_norm\": 0.8659003831417624,\n\ \ \"acc_norm_stderr\": 0.012185528166499983\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7774566473988439,\n \"acc_stderr\": 0.02239421566194282,\n\ \ \"acc_norm\": 0.7774566473988439,\n \"acc_norm_stderr\": 0.02239421566194282\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.5597765363128492,\n\ \ \"acc_stderr\": 0.01660256461504993,\n \"acc_norm\": 0.5597765363128492,\n\ \ \"acc_norm_stderr\": 0.01660256461504993\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7352941176470589,\n \"acc_stderr\": 0.02526169121972949,\n\ \ \"acc_norm\": 0.7352941176470589,\n \"acc_norm_stderr\": 0.02526169121972949\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7588424437299035,\n\ \ \"acc_stderr\": 0.024296594034763426,\n \"acc_norm\": 0.7588424437299035,\n\ \ \"acc_norm_stderr\": 0.024296594034763426\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.7962962962962963,\n \"acc_stderr\": 0.022409674547304168,\n\ \ \"acc_norm\": 0.7962962962962963,\n \"acc_norm_stderr\": 0.022409674547304168\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.5531914893617021,\n \"acc_stderr\": 0.02965823509766691,\n \ \ \"acc_norm\": 0.5531914893617021,\n \"acc_norm_stderr\": 0.02965823509766691\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.5586701434159062,\n\ \ \"acc_stderr\": 0.012682016335646678,\n \"acc_norm\": 0.5586701434159062,\n\ \ \"acc_norm_stderr\": 0.012682016335646678\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.7352941176470589,\n \"acc_stderr\": 0.026799562024887653,\n\ \ \"acc_norm\": 0.7352941176470589,\n \"acc_norm_stderr\": 0.026799562024887653\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.7434640522875817,\n \"acc_stderr\": 0.017667841612379005,\n \ \ \"acc_norm\": 0.7434640522875817,\n \"acc_norm_stderr\": 0.017667841612379005\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7454545454545455,\n\ \ \"acc_stderr\": 0.041723430387053825,\n \"acc_norm\": 0.7454545454545455,\n\ \ \"acc_norm_stderr\": 0.041723430387053825\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7795918367346939,\n \"acc_stderr\": 0.026537045312145298,\n\ \ \"acc_norm\": 0.7795918367346939,\n \"acc_norm_stderr\": 0.026537045312145298\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8855721393034826,\n\ \ \"acc_stderr\": 0.022509345325101706,\n \"acc_norm\": 0.8855721393034826,\n\ \ \"acc_norm_stderr\": 0.022509345325101706\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\ : {\n \"acc\": 0.88,\n \"acc_stderr\": 0.03265986323710906,\n \ \ \"acc_norm\": 0.88,\n \"acc_norm_stderr\": 0.03265986323710906\n \ \ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5240963855421686,\n\ \ \"acc_stderr\": 0.03887971849597264,\n \"acc_norm\": 0.5240963855421686,\n\ \ \"acc_norm_stderr\": 0.03887971849597264\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8596491228070176,\n \"acc_stderr\": 0.0266405825391332,\n\ \ \"acc_norm\": 0.8596491228070176,\n \"acc_norm_stderr\": 0.0266405825391332\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.4663402692778458,\n\ \ \"mc1_stderr\": 0.01746379386716811,\n \"mc2\": 0.6478807414957388,\n\ \ \"mc2_stderr\": 0.014914964973799093\n }\n}\n```" repo_url: https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v2 leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard point_of_contact: clementine@hf.co configs: - config_name: harness_arc_challenge_25 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|arc:challenge|25_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hellaswag|10_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-15T16-06-18.387785.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-management|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-virology|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T16-06-18.387785.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_15T16_06_18.387785 path: - '**/details_harness|truthfulqa:mc|0_2023-09-15T16-06-18.387785.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-09-15T16-06-18.387785.parquet' - config_name: results data_files: - split: 2023_09_15T16_06_18.387785 path: - results_2023-09-15T16-06-18.387785.parquet - split: latest path: - results_2023-09-15T16-06-18.387785.parquet --- # Dataset Card for Evaluation run of oh-yeontaek/llama-2-70B-LoRA-assemble-v2 ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v2 - **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 [oh-yeontaek/llama-2-70B-LoRA-assemble-v2](https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v2) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v2", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-15T16:06:18.387785](https://huggingface.co/datasets/open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v2/blob/main/results_2023-09-15T16-06-18.387785.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": 0.6931761249212157, "acc_stderr": 0.031300161246260914, "acc_norm": 0.6971025131327819, "acc_norm_stderr": 0.03127024725201448, "mc1": 0.4663402692778458, "mc1_stderr": 0.01746379386716811, "mc2": 0.6478807414957388, "mc2_stderr": 0.014914964973799093 }, "harness|arc:challenge|25": { "acc": 0.6834470989761092, "acc_stderr": 0.013592431519068079, "acc_norm": 0.7184300341296929, "acc_norm_stderr": 0.013143376735009022 }, "harness|hellaswag|10": { "acc": 0.6721768571997611, "acc_stderr": 0.0046846063106423304, "acc_norm": 0.8688508265285799, "acc_norm_stderr": 0.00336873543416138 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6148148148148148, "acc_stderr": 0.042039210401562783, "acc_norm": 0.6148148148148148, "acc_norm_stderr": 0.042039210401562783 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7828947368421053, "acc_stderr": 0.03355045304882924, "acc_norm": 0.7828947368421053, "acc_norm_stderr": 0.03355045304882924 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7433962264150943, "acc_stderr": 0.02688064788905199, "acc_norm": 0.7433962264150943, "acc_norm_stderr": 0.02688064788905199 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8194444444444444, "acc_stderr": 0.03216600808802267, "acc_norm": 0.8194444444444444, "acc_norm_stderr": 0.03216600808802267 }, "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": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.36, "acc_stderr": 0.048241815132442176, "acc_norm": 0.36, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6589595375722543, "acc_stderr": 0.036146654241808254, "acc_norm": 0.6589595375722543, "acc_norm_stderr": 0.036146654241808254 }, "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": 0.74, "acc_stderr": 0.04408440022768078, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768078 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6553191489361702, "acc_stderr": 0.031068985963122145, "acc_norm": 0.6553191489361702, "acc_norm_stderr": 0.031068985963122145 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.41228070175438597, "acc_stderr": 0.04630653203366595, "acc_norm": 0.41228070175438597, "acc_norm_stderr": 0.04630653203366595 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6344827586206897, "acc_stderr": 0.04013124195424386, "acc_norm": 0.6344827586206897, "acc_norm_stderr": 0.04013124195424386 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4656084656084656, "acc_stderr": 0.02569032176249384, "acc_norm": 0.4656084656084656, "acc_norm_stderr": 0.02569032176249384 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.832258064516129, "acc_stderr": 0.021255464065371314, "acc_norm": 0.832258064516129, "acc_norm_stderr": 0.021255464065371314 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5467980295566502, "acc_stderr": 0.03502544650845872, "acc_norm": 0.5467980295566502, "acc_norm_stderr": 0.03502544650845872 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.78, "acc_stderr": 0.04163331998932262, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932262 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8303030303030303, "acc_stderr": 0.02931118867498312, "acc_norm": 0.8303030303030303, "acc_norm_stderr": 0.02931118867498312 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9040404040404041, "acc_stderr": 0.020984808610047933, "acc_norm": 0.9040404040404041, "acc_norm_stderr": 0.020984808610047933 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.927461139896373, "acc_stderr": 0.018718998520678178, "acc_norm": 0.927461139896373, "acc_norm_stderr": 0.018718998520678178 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6974358974358974, "acc_stderr": 0.02329088805377272, "acc_norm": 0.6974358974358974, "acc_norm_stderr": 0.02329088805377272 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.32592592592592595, "acc_stderr": 0.028578348365473072, "acc_norm": 0.32592592592592595, "acc_norm_stderr": 0.028578348365473072 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.7815126050420168, "acc_stderr": 0.026841514322958934, "acc_norm": 0.7815126050420168, "acc_norm_stderr": 0.026841514322958934 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.47019867549668876, "acc_stderr": 0.040752249922169775, "acc_norm": 0.47019867549668876, "acc_norm_stderr": 0.040752249922169775 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8844036697247707, "acc_stderr": 0.013708749534172636, "acc_norm": 0.8844036697247707, "acc_norm_stderr": 0.013708749534172636 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5648148148148148, "acc_stderr": 0.033812000056435254, "acc_norm": 0.5648148148148148, "acc_norm_stderr": 0.033812000056435254 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.8970588235294118, "acc_stderr": 0.021328337570804365, "acc_norm": 0.8970588235294118, "acc_norm_stderr": 0.021328337570804365 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.8776371308016878, "acc_stderr": 0.02133174182974679, "acc_norm": 0.8776371308016878, "acc_norm_stderr": 0.02133174182974679 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.7668161434977578, "acc_stderr": 0.028380391147094706, "acc_norm": 0.7668161434977578, "acc_norm_stderr": 0.028380391147094706 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.8244274809160306, "acc_stderr": 0.03336820338476073, "acc_norm": 0.8244274809160306, "acc_norm_stderr": 0.03336820338476073 }, "harness|hendrycksTest-international_law|5": { "acc": 0.8512396694214877, "acc_stderr": 0.03248470083807194, "acc_norm": 0.8512396694214877, "acc_norm_stderr": 0.03248470083807194 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.8333333333333334, "acc_stderr": 0.03602814176392645, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.03602814176392645 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.8220858895705522, "acc_stderr": 0.03004735765580663, "acc_norm": 0.8220858895705522, "acc_norm_stderr": 0.03004735765580663 }, "harness|hendrycksTest-machine_learning|5": { "acc": 0.49107142857142855, "acc_stderr": 0.04745033255489123, "acc_norm": 0.49107142857142855, "acc_norm_stderr": 0.04745033255489123 }, "harness|hendrycksTest-management|5": { "acc": 0.8252427184466019, "acc_stderr": 0.0376017800602662, "acc_norm": 0.8252427184466019, "acc_norm_stderr": 0.0376017800602662 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8888888888888888, "acc_stderr": 0.02058849131609238, "acc_norm": 0.8888888888888888, "acc_norm_stderr": 0.02058849131609238 }, "harness|hendrycksTest-medical_genetics|5": { "acc": 0.71, "acc_stderr": 0.04560480215720684, "acc_norm": 0.71, "acc_norm_stderr": 0.04560480215720684 }, "harness|hendrycksTest-miscellaneous|5": { "acc": 0.8659003831417624, "acc_stderr": 0.012185528166499983, "acc_norm": 0.8659003831417624, "acc_norm_stderr": 0.012185528166499983 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7774566473988439, "acc_stderr": 0.02239421566194282, "acc_norm": 0.7774566473988439, "acc_norm_stderr": 0.02239421566194282 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.5597765363128492, "acc_stderr": 0.01660256461504993, "acc_norm": 0.5597765363128492, "acc_norm_stderr": 0.01660256461504993 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7352941176470589, "acc_stderr": 0.02526169121972949, "acc_norm": 0.7352941176470589, "acc_norm_stderr": 0.02526169121972949 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7588424437299035, "acc_stderr": 0.024296594034763426, "acc_norm": 0.7588424437299035, "acc_norm_stderr": 0.024296594034763426 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.7962962962962963, "acc_stderr": 0.022409674547304168, "acc_norm": 0.7962962962962963, "acc_norm_stderr": 0.022409674547304168 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.5531914893617021, "acc_stderr": 0.02965823509766691, "acc_norm": 0.5531914893617021, "acc_norm_stderr": 0.02965823509766691 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.5586701434159062, "acc_stderr": 0.012682016335646678, "acc_norm": 0.5586701434159062, "acc_norm_stderr": 0.012682016335646678 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.7352941176470589, "acc_stderr": 0.026799562024887653, "acc_norm": 0.7352941176470589, "acc_norm_stderr": 0.026799562024887653 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.7434640522875817, "acc_stderr": 0.017667841612379005, "acc_norm": 0.7434640522875817, "acc_norm_stderr": 0.017667841612379005 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.7454545454545455, "acc_stderr": 0.041723430387053825, "acc_norm": 0.7454545454545455, "acc_norm_stderr": 0.041723430387053825 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7795918367346939, "acc_stderr": 0.026537045312145298, "acc_norm": 0.7795918367346939, "acc_norm_stderr": 0.026537045312145298 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8855721393034826, "acc_stderr": 0.022509345325101706, "acc_norm": 0.8855721393034826, "acc_norm_stderr": 0.022509345325101706 }, "harness|hendrycksTest-us_foreign_policy|5": { "acc": 0.88, "acc_stderr": 0.03265986323710906, "acc_norm": 0.88, "acc_norm_stderr": 0.03265986323710906 }, "harness|hendrycksTest-virology|5": { "acc": 0.5240963855421686, "acc_stderr": 0.03887971849597264, "acc_norm": 0.5240963855421686, "acc_norm_stderr": 0.03887971849597264 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8596491228070176, "acc_stderr": 0.0266405825391332, "acc_norm": 0.8596491228070176, "acc_norm_stderr": 0.0266405825391332 }, "harness|truthfulqa:mc|0": { "mc1": 0.4663402692778458, "mc1_stderr": 0.01746379386716811, "mc2": 0.6478807414957388, "mc2_stderr": 0.014914964973799093 } } ``` ### 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]
CyberHarem/senzaki_ema_idolmastercinderellagirls
2023-09-17T17:40:01.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of senzaki_ema (THE iDOLM@STER: Cinderella Girls) This is the dataset of senzaki_ema (THE iDOLM@STER: Cinderella Girls), containing 43 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 43 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 118 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 43 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 43 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 43 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 43 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 43 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 118 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 118 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 118 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/yamato_aki_idolmastercinderellagirls
2023-09-17T17:40:03.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of yamato_aki (THE iDOLM@STER: Cinderella Girls) This is the dataset of yamato_aki (THE iDOLM@STER: Cinderella Girls), containing 108 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 108 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 286 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 108 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 108 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 108 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 108 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 108 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 286 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 286 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 286 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/hyoudou_rena_idolmastercinderellagirls
2023-09-17T17:40:05.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of hyoudou_rena (THE iDOLM@STER: Cinderella Girls) This is the dataset of hyoudou_rena (THE iDOLM@STER: Cinderella Girls), containing 42 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 42 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 118 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 42 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 42 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 42 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 42 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 42 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 118 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 118 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 118 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/aozaki_touko_karanokyoukai
2023-09-17T17:40:07.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of Aozaki Touko This is the dataset of Aozaki Touko, containing 156 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 156 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 338 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 156 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 156 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 156 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 156 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 156 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 338 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 338 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 338 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/yoshioka_saki_idolmastercinderellagirls
2023-09-17T17:40:09.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of yoshioka_saki (THE iDOLM@STER: Cinderella Girls) This is the dataset of yoshioka_saki (THE iDOLM@STER: Cinderella Girls), containing 37 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 37 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 95 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 37 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 37 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 37 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 37 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 37 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 95 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 95 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 95 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/matsubara_saya_idolmastercinderellagirls
2023-09-17T17:40:12.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of matsubara_saya (THE iDOLM@STER: Cinderella Girls) This is the dataset of matsubara_saya (THE iDOLM@STER: Cinderella Girls), containing 19 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 19 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 47 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 19 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 19 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 19 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 19 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 19 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 47 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 47 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 47 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
Zerenidel/mayjjkbl
2023-09-15T16:58:23.000Z
[ "region:us" ]
Zerenidel
null
null
null
0
0
Entry not found
CyberHarem/nanjou_hikaru_idolmastercinderellagirls
2023-09-17T17:40:15.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of nanjou_hikaru (THE iDOLM@STER: Cinderella Girls) This is the dataset of nanjou_hikaru (THE iDOLM@STER: Cinderella Girls), containing 71 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 71 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 195 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 71 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 71 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 71 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 71 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 71 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 195 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 195 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 195 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
KyonBS/data
2023-09-15T17:19:25.000Z
[ "region:us" ]
KyonBS
null
null
null
0
0
Entry not found
kuronomiki/anjeg
2023-09-15T17:34:26.000Z
[ "license:other", "region:us" ]
kuronomiki
null
null
null
0
0
--- license: other ---
JOSEDURANisc/vit-model
2023-09-15T17:33:46.000Z
[ "region:us" ]
JOSEDURANisc
null
null
null
0
0
Entry not found
open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3
2023-09-15T17:37:50.000Z
[ "region:us" ]
open-llm-leaderboard
null
null
null
0
0
--- pretty_name: Evaluation run of oh-yeontaek/llama-2-70B-LoRA-assemble-v3 dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [oh-yeontaek/llama-2-70B-LoRA-assemble-v3](https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v3)\ \ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\ \nThe dataset is composed of 61 configuration, each one coresponding to one of the\ \ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\ \ found as a specific split in each configuration, the split being named using the\ \ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\ \nAn additional configuration \"results\" store all the aggregated results of the\ \ run (and is used to compute and display the agregated metrics on the [Open LLM\ \ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\ \nTo load the details from a run, you can for instance do the following:\n```python\n\ from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3\"\ ,\n\t\"harness_truthfulqa_mc_0\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\ \nThese are the [latest results from run 2023-09-15T17:36:30.757691](https://huggingface.co/datasets/open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3/blob/main/results_2023-09-15T17-36-30.757691.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\": 0.6985803552112708,\n\ \ \"acc_stderr\": 0.03118492094070661,\n \"acc_norm\": 0.7024274155828159,\n\ \ \"acc_norm_stderr\": 0.031154550420018332,\n \"mc1\": 0.47980416156670747,\n\ \ \"mc1_stderr\": 0.01748921684973705,\n \"mc2\": 0.658093697491632,\n\ \ \"mc2_stderr\": 0.014747866760131165\n },\n \"harness|arc:challenge|25\"\ : {\n \"acc\": 0.6860068259385665,\n \"acc_stderr\": 0.013562691224726291,\n\ \ \"acc_norm\": 0.7209897610921502,\n \"acc_norm_stderr\": 0.013106784883601334\n\ \ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6820354511053575,\n\ \ \"acc_stderr\": 0.004647338877642188,\n \"acc_norm\": 0.8740290778729337,\n\ \ \"acc_norm_stderr\": 0.0033113844981586464\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\ : {\n \"acc\": 0.4,\n \"acc_stderr\": 0.049236596391733084,\n \ \ \"acc_norm\": 0.4,\n \"acc_norm_stderr\": 0.049236596391733084\n \ \ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6370370370370371,\n\ \ \"acc_stderr\": 0.041539484047424,\n \"acc_norm\": 0.6370370370370371,\n\ \ \"acc_norm_stderr\": 0.041539484047424\n },\n \"harness|hendrycksTest-astronomy|5\"\ : {\n \"acc\": 0.7828947368421053,\n \"acc_stderr\": 0.03355045304882924,\n\ \ \"acc_norm\": 0.7828947368421053,\n \"acc_norm_stderr\": 0.03355045304882924\n\ \ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.76,\n\ \ \"acc_stderr\": 0.04292346959909284,\n \"acc_norm\": 0.76,\n \ \ \"acc_norm_stderr\": 0.04292346959909284\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\ : {\n \"acc\": 0.7547169811320755,\n \"acc_stderr\": 0.026480357179895695,\n\ \ \"acc_norm\": 0.7547169811320755,\n \"acc_norm_stderr\": 0.026480357179895695\n\ \ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8194444444444444,\n\ \ \"acc_stderr\": 0.03216600808802267,\n \"acc_norm\": 0.8194444444444444,\n\ \ \"acc_norm_stderr\": 0.03216600808802267\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\": 0.62,\n \"acc_stderr\": 0.04878317312145632,\n \"acc_norm\"\ : 0.62,\n \"acc_norm_stderr\": 0.04878317312145632\n },\n \"harness|hendrycksTest-college_mathematics|5\"\ : {\n \"acc\": 0.38,\n \"acc_stderr\": 0.048783173121456316,\n \ \ \"acc_norm\": 0.38,\n \"acc_norm_stderr\": 0.048783173121456316\n \ \ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.6647398843930635,\n\ \ \"acc_stderr\": 0.03599586301247077,\n \"acc_norm\": 0.6647398843930635,\n\ \ \"acc_norm_stderr\": 0.03599586301247077\n },\n \"harness|hendrycksTest-college_physics|5\"\ : {\n \"acc\": 0.3431372549019608,\n \"acc_stderr\": 0.04724007352383888,\n\ \ \"acc_norm\": 0.3431372549019608,\n \"acc_norm_stderr\": 0.04724007352383888\n\ \ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\ \ 0.74,\n \"acc_stderr\": 0.04408440022768078,\n \"acc_norm\": 0.74,\n\ \ \"acc_norm_stderr\": 0.04408440022768078\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\ : {\n \"acc\": 0.676595744680851,\n \"acc_stderr\": 0.03057944277361034,\n\ \ \"acc_norm\": 0.676595744680851,\n \"acc_norm_stderr\": 0.03057944277361034\n\ \ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.4649122807017544,\n\ \ \"acc_stderr\": 0.04692008381368909,\n \"acc_norm\": 0.4649122807017544,\n\ \ \"acc_norm_stderr\": 0.04692008381368909\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\ : {\n \"acc\": 0.6413793103448275,\n \"acc_stderr\": 0.03996629574876719,\n\ \ \"acc_norm\": 0.6413793103448275,\n \"acc_norm_stderr\": 0.03996629574876719\n\ \ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\ : 0.47354497354497355,\n \"acc_stderr\": 0.025715239811346758,\n \"\ acc_norm\": 0.47354497354497355,\n \"acc_norm_stderr\": 0.025715239811346758\n\ \ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.49206349206349204,\n\ \ \"acc_stderr\": 0.044715725362943486,\n \"acc_norm\": 0.49206349206349204,\n\ \ \"acc_norm_stderr\": 0.044715725362943486\n },\n \"harness|hendrycksTest-global_facts|5\"\ : {\n \"acc\": 0.49,\n \"acc_stderr\": 0.05024183937956912,\n \ \ \"acc_norm\": 0.49,\n \"acc_norm_stderr\": 0.05024183937956912\n \ \ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.8193548387096774,\n\ \ \"acc_stderr\": 0.02188617856717253,\n \"acc_norm\": 0.8193548387096774,\n\ \ \"acc_norm_stderr\": 0.02188617856717253\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\ : {\n \"acc\": 0.541871921182266,\n \"acc_stderr\": 0.03505630140785741,\n\ \ \"acc_norm\": 0.541871921182266,\n \"acc_norm_stderr\": 0.03505630140785741\n\ \ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \ \ \"acc\": 0.79,\n \"acc_stderr\": 0.040936018074033256,\n \"acc_norm\"\ : 0.79,\n \"acc_norm_stderr\": 0.040936018074033256\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\ : {\n \"acc\": 0.8484848484848485,\n \"acc_stderr\": 0.027998073798781675,\n\ \ \"acc_norm\": 0.8484848484848485,\n \"acc_norm_stderr\": 0.027998073798781675\n\ \ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\ : 0.8888888888888888,\n \"acc_stderr\": 0.022390787638216763,\n \"\ acc_norm\": 0.8888888888888888,\n \"acc_norm_stderr\": 0.022390787638216763\n\ \ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\ \ \"acc\": 0.927461139896373,\n \"acc_stderr\": 0.018718998520678178,\n\ \ \"acc_norm\": 0.927461139896373,\n \"acc_norm_stderr\": 0.018718998520678178\n\ \ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \ \ \"acc\": 0.6974358974358974,\n \"acc_stderr\": 0.02329088805377272,\n \ \ \"acc_norm\": 0.6974358974358974,\n \"acc_norm_stderr\": 0.02329088805377272\n\ \ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\ acc\": 0.32592592592592595,\n \"acc_stderr\": 0.028578348365473072,\n \ \ \"acc_norm\": 0.32592592592592595,\n \"acc_norm_stderr\": 0.028578348365473072\n\ \ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \ \ \"acc\": 0.773109243697479,\n \"acc_stderr\": 0.02720537153827947,\n \ \ \"acc_norm\": 0.773109243697479,\n \"acc_norm_stderr\": 0.02720537153827947\n\ \ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\ : 0.4966887417218543,\n \"acc_stderr\": 0.04082393379449654,\n \"\ acc_norm\": 0.4966887417218543,\n \"acc_norm_stderr\": 0.04082393379449654\n\ \ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\ : 0.8954128440366973,\n \"acc_stderr\": 0.013120530245265586,\n \"\ acc_norm\": 0.8954128440366973,\n \"acc_norm_stderr\": 0.013120530245265586\n\ \ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\ : 0.5833333333333334,\n \"acc_stderr\": 0.03362277436608043,\n \"\ acc_norm\": 0.5833333333333334,\n \"acc_norm_stderr\": 0.03362277436608043\n\ \ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\ : 0.9019607843137255,\n \"acc_stderr\": 0.020871118455552097,\n \"\ acc_norm\": 0.9019607843137255,\n \"acc_norm_stderr\": 0.020871118455552097\n\ \ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\ acc\": 0.890295358649789,\n \"acc_stderr\": 0.020343400734868837,\n \ \ \"acc_norm\": 0.890295358649789,\n \"acc_norm_stderr\": 0.020343400734868837\n\ \ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.7623318385650224,\n\ \ \"acc_stderr\": 0.028568079464714274,\n \"acc_norm\": 0.7623318385650224,\n\ \ \"acc_norm_stderr\": 0.028568079464714274\n },\n \"harness|hendrycksTest-human_sexuality|5\"\ : {\n \"acc\": 0.8396946564885496,\n \"acc_stderr\": 0.03217829420744632,\n\ \ \"acc_norm\": 0.8396946564885496,\n \"acc_norm_stderr\": 0.03217829420744632\n\ \ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\ \ 0.8512396694214877,\n \"acc_stderr\": 0.03248470083807194,\n \"\ acc_norm\": 0.8512396694214877,\n \"acc_norm_stderr\": 0.03248470083807194\n\ \ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8333333333333334,\n\ \ \"acc_stderr\": 0.03602814176392645,\n \"acc_norm\": 0.8333333333333334,\n\ \ \"acc_norm_stderr\": 0.03602814176392645\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\ : {\n \"acc\": 0.8282208588957055,\n \"acc_stderr\": 0.02963471727237104,\n\ \ \"acc_norm\": 0.8282208588957055,\n \"acc_norm_stderr\": 0.02963471727237104\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\": 0.8349514563106796,\n \"acc_stderr\": 0.03675668832233188,\n\ \ \"acc_norm\": 0.8349514563106796,\n \"acc_norm_stderr\": 0.03675668832233188\n\ \ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8974358974358975,\n\ \ \"acc_stderr\": 0.01987565502786745,\n \"acc_norm\": 0.8974358974358975,\n\ \ \"acc_norm_stderr\": 0.01987565502786745\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\": 0.859514687100894,\n\ \ \"acc_stderr\": 0.012426211353093448,\n \"acc_norm\": 0.859514687100894,\n\ \ \"acc_norm_stderr\": 0.012426211353093448\n },\n \"harness|hendrycksTest-moral_disputes|5\"\ : {\n \"acc\": 0.7658959537572254,\n \"acc_stderr\": 0.022797110278071128,\n\ \ \"acc_norm\": 0.7658959537572254,\n \"acc_norm_stderr\": 0.022797110278071128\n\ \ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.582122905027933,\n\ \ \"acc_stderr\": 0.016495400635820084,\n \"acc_norm\": 0.582122905027933,\n\ \ \"acc_norm_stderr\": 0.016495400635820084\n },\n \"harness|hendrycksTest-nutrition|5\"\ : {\n \"acc\": 0.7483660130718954,\n \"acc_stderr\": 0.024848018263875195,\n\ \ \"acc_norm\": 0.7483660130718954,\n \"acc_norm_stderr\": 0.024848018263875195\n\ \ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.7427652733118971,\n\ \ \"acc_stderr\": 0.024826171289250888,\n \"acc_norm\": 0.7427652733118971,\n\ \ \"acc_norm_stderr\": 0.024826171289250888\n },\n \"harness|hendrycksTest-prehistory|5\"\ : {\n \"acc\": 0.8117283950617284,\n \"acc_stderr\": 0.021751866060815882,\n\ \ \"acc_norm\": 0.8117283950617284,\n \"acc_norm_stderr\": 0.021751866060815882\n\ \ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\ acc\": 0.574468085106383,\n \"acc_stderr\": 0.02949482760014436,\n \ \ \"acc_norm\": 0.574468085106383,\n \"acc_norm_stderr\": 0.02949482760014436\n\ \ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.5788787483702738,\n\ \ \"acc_stderr\": 0.012610325733489905,\n \"acc_norm\": 0.5788787483702738,\n\ \ \"acc_norm_stderr\": 0.012610325733489905\n },\n \"harness|hendrycksTest-professional_medicine|5\"\ : {\n \"acc\": 0.7242647058823529,\n \"acc_stderr\": 0.027146271936625162,\n\ \ \"acc_norm\": 0.7242647058823529,\n \"acc_norm_stderr\": 0.027146271936625162\n\ \ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\ acc\": 0.7565359477124183,\n \"acc_stderr\": 0.017362473762146613,\n \ \ \"acc_norm\": 0.7565359477124183,\n \"acc_norm_stderr\": 0.017362473762146613\n\ \ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7454545454545455,\n\ \ \"acc_stderr\": 0.04172343038705383,\n \"acc_norm\": 0.7454545454545455,\n\ \ \"acc_norm_stderr\": 0.04172343038705383\n },\n \"harness|hendrycksTest-security_studies|5\"\ : {\n \"acc\": 0.7959183673469388,\n \"acc_stderr\": 0.025801283475090496,\n\ \ \"acc_norm\": 0.7959183673469388,\n \"acc_norm_stderr\": 0.025801283475090496\n\ \ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8905472636815921,\n\ \ \"acc_stderr\": 0.02207632610182466,\n \"acc_norm\": 0.8905472636815921,\n\ \ \"acc_norm_stderr\": 0.02207632610182466\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\": 0.03891364495835817,\n \"acc_norm\": 0.5120481927710844,\n\ \ \"acc_norm_stderr\": 0.03891364495835817\n },\n \"harness|hendrycksTest-world_religions|5\"\ : {\n \"acc\": 0.8596491228070176,\n \"acc_stderr\": 0.0266405825391332,\n\ \ \"acc_norm\": 0.8596491228070176,\n \"acc_norm_stderr\": 0.0266405825391332\n\ \ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.47980416156670747,\n\ \ \"mc1_stderr\": 0.01748921684973705,\n \"mc2\": 0.658093697491632,\n\ \ \"mc2_stderr\": 0.014747866760131165\n }\n}\n```" repo_url: https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v3 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_15T17_36_30.757691 path: - '**/details_harness|arc:challenge|25_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|arc:challenge|25_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hellaswag_10 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hellaswag|10_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hellaswag|10_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-management|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-virology|5_2023-09-15T17-36-30.757691.parquet' - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_abstract_algebra_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-abstract_algebra|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_anatomy_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-anatomy|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_astronomy_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-astronomy|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_business_ethics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-business_ethics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_clinical_knowledge_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_biology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_biology|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_chemistry_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_chemistry|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_computer_science_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_computer_science|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_mathematics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_mathematics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_medicine_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_medicine|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_college_physics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-college_physics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_computer_security_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-computer_security|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_conceptual_physics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-conceptual_physics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_econometrics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-econometrics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_electrical_engineering_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-electrical_engineering|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_elementary_mathematics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_formal_logic_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-formal_logic|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_global_facts_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-global_facts|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_biology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_biology|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_chemistry_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_computer_science_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_european_history_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_european_history|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_geography_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_geography|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_government_and_politics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_macroeconomics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_mathematics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_microeconomics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_physics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_physics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_psychology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_psychology|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_statistics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_statistics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_us_history_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_us_history|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_high_school_world_history_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-high_school_world_history|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_human_aging_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_aging|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_human_sexuality_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-human_sexuality|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_international_law_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-international_law|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_jurisprudence_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-jurisprudence|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_logical_fallacies_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-logical_fallacies|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_machine_learning_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-machine_learning|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_management_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-management|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-management|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_marketing_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-marketing|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_medical_genetics_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-medical_genetics|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_miscellaneous_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-miscellaneous|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_moral_disputes_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_disputes|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_moral_scenarios_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-moral_scenarios|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_nutrition_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-nutrition|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_philosophy_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-philosophy|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_prehistory_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-prehistory|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_professional_accounting_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_accounting|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_professional_law_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_law|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_professional_medicine_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_medicine|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_professional_psychology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-professional_psychology|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_public_relations_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-public_relations|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_security_studies_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-security_studies|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_sociology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-sociology|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_us_foreign_policy_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_virology_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-virology|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-virology|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_hendrycksTest_world_religions_5 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|hendrycksTest-world_religions|5_2023-09-15T17-36-30.757691.parquet' - config_name: harness_truthfulqa_mc_0 data_files: - split: 2023_09_15T17_36_30.757691 path: - '**/details_harness|truthfulqa:mc|0_2023-09-15T17-36-30.757691.parquet' - split: latest path: - '**/details_harness|truthfulqa:mc|0_2023-09-15T17-36-30.757691.parquet' - config_name: results data_files: - split: 2023_09_15T17_36_30.757691 path: - results_2023-09-15T17-36-30.757691.parquet - split: latest path: - results_2023-09-15T17-36-30.757691.parquet --- # Dataset Card for Evaluation run of oh-yeontaek/llama-2-70B-LoRA-assemble-v3 ## Dataset Description - **Homepage:** - **Repository:** https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v3 - **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 [oh-yeontaek/llama-2-70B-LoRA-assemble-v3](https://huggingface.co/oh-yeontaek/llama-2-70B-LoRA-assemble-v3) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset is composed of 61 configuration, each one coresponding to one of the evaluated task. The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results. An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)). To load the details from a run, you can for instance do the following: ```python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3", "harness_truthfulqa_mc_0", split="train") ``` ## Latest results These are the [latest results from run 2023-09-15T17:36:30.757691](https://huggingface.co/datasets/open-llm-leaderboard/details_oh-yeontaek__llama-2-70B-LoRA-assemble-v3/blob/main/results_2023-09-15T17-36-30.757691.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": 0.6985803552112708, "acc_stderr": 0.03118492094070661, "acc_norm": 0.7024274155828159, "acc_norm_stderr": 0.031154550420018332, "mc1": 0.47980416156670747, "mc1_stderr": 0.01748921684973705, "mc2": 0.658093697491632, "mc2_stderr": 0.014747866760131165 }, "harness|arc:challenge|25": { "acc": 0.6860068259385665, "acc_stderr": 0.013562691224726291, "acc_norm": 0.7209897610921502, "acc_norm_stderr": 0.013106784883601334 }, "harness|hellaswag|10": { "acc": 0.6820354511053575, "acc_stderr": 0.004647338877642188, "acc_norm": 0.8740290778729337, "acc_norm_stderr": 0.0033113844981586464 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6370370370370371, "acc_stderr": 0.041539484047424, "acc_norm": 0.6370370370370371, "acc_norm_stderr": 0.041539484047424 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7828947368421053, "acc_stderr": 0.03355045304882924, "acc_norm": 0.7828947368421053, "acc_norm_stderr": 0.03355045304882924 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.76, "acc_stderr": 0.04292346959909284, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909284 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7547169811320755, "acc_stderr": 0.026480357179895695, "acc_norm": 0.7547169811320755, "acc_norm_stderr": 0.026480357179895695 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8194444444444444, "acc_stderr": 0.03216600808802267, "acc_norm": 0.8194444444444444, "acc_norm_stderr": 0.03216600808802267 }, "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": 0.62, "acc_stderr": 0.04878317312145632, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145632 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6647398843930635, "acc_stderr": 0.03599586301247077, "acc_norm": 0.6647398843930635, "acc_norm_stderr": 0.03599586301247077 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3431372549019608, "acc_stderr": 0.04724007352383888, "acc_norm": 0.3431372549019608, "acc_norm_stderr": 0.04724007352383888 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.74, "acc_stderr": 0.04408440022768078, "acc_norm": 0.74, "acc_norm_stderr": 0.04408440022768078 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.676595744680851, "acc_stderr": 0.03057944277361034, "acc_norm": 0.676595744680851, "acc_norm_stderr": 0.03057944277361034 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.4649122807017544, "acc_stderr": 0.04692008381368909, "acc_norm": 0.4649122807017544, "acc_norm_stderr": 0.04692008381368909 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6413793103448275, "acc_stderr": 0.03996629574876719, "acc_norm": 0.6413793103448275, "acc_norm_stderr": 0.03996629574876719 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.47354497354497355, "acc_stderr": 0.025715239811346758, "acc_norm": 0.47354497354497355, "acc_norm_stderr": 0.025715239811346758 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.49206349206349204, "acc_stderr": 0.044715725362943486, "acc_norm": 0.49206349206349204, "acc_norm_stderr": 0.044715725362943486 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8193548387096774, "acc_stderr": 0.02188617856717253, "acc_norm": 0.8193548387096774, "acc_norm_stderr": 0.02188617856717253 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.541871921182266, "acc_stderr": 0.03505630140785741, "acc_norm": 0.541871921182266, "acc_norm_stderr": 0.03505630140785741 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.79, "acc_stderr": 0.040936018074033256, "acc_norm": 0.79, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8484848484848485, "acc_stderr": 0.027998073798781675, "acc_norm": 0.8484848484848485, "acc_norm_stderr": 0.027998073798781675 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8888888888888888, "acc_stderr": 0.022390787638216763, "acc_norm": 0.8888888888888888, "acc_norm_stderr": 0.022390787638216763 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.927461139896373, "acc_stderr": 0.018718998520678178, "acc_norm": 0.927461139896373, "acc_norm_stderr": 0.018718998520678178 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6974358974358974, "acc_stderr": 0.02329088805377272, "acc_norm": 0.6974358974358974, "acc_norm_stderr": 0.02329088805377272 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.32592592592592595, "acc_stderr": 0.028578348365473072, "acc_norm": 0.32592592592592595, "acc_norm_stderr": 0.028578348365473072 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.773109243697479, "acc_stderr": 0.02720537153827947, "acc_norm": 0.773109243697479, "acc_norm_stderr": 0.02720537153827947 }, "harness|hendrycksTest-high_school_physics|5": { "acc": 0.4966887417218543, "acc_stderr": 0.04082393379449654, "acc_norm": 0.4966887417218543, "acc_norm_stderr": 0.04082393379449654 }, "harness|hendrycksTest-high_school_psychology|5": { "acc": 0.8954128440366973, "acc_stderr": 0.013120530245265586, "acc_norm": 0.8954128440366973, "acc_norm_stderr": 0.013120530245265586 }, "harness|hendrycksTest-high_school_statistics|5": { "acc": 0.5833333333333334, "acc_stderr": 0.03362277436608043, "acc_norm": 0.5833333333333334, "acc_norm_stderr": 0.03362277436608043 }, "harness|hendrycksTest-high_school_us_history|5": { "acc": 0.9019607843137255, "acc_stderr": 0.020871118455552097, "acc_norm": 0.9019607843137255, "acc_norm_stderr": 0.020871118455552097 }, "harness|hendrycksTest-high_school_world_history|5": { "acc": 0.890295358649789, "acc_stderr": 0.020343400734868837, "acc_norm": 0.890295358649789, "acc_norm_stderr": 0.020343400734868837 }, "harness|hendrycksTest-human_aging|5": { "acc": 0.7623318385650224, "acc_stderr": 0.028568079464714274, "acc_norm": 0.7623318385650224, "acc_norm_stderr": 0.028568079464714274 }, "harness|hendrycksTest-human_sexuality|5": { "acc": 0.8396946564885496, "acc_stderr": 0.03217829420744632, "acc_norm": 0.8396946564885496, "acc_norm_stderr": 0.03217829420744632 }, "harness|hendrycksTest-international_law|5": { "acc": 0.8512396694214877, "acc_stderr": 0.03248470083807194, "acc_norm": 0.8512396694214877, "acc_norm_stderr": 0.03248470083807194 }, "harness|hendrycksTest-jurisprudence|5": { "acc": 0.8333333333333334, "acc_stderr": 0.03602814176392645, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.03602814176392645 }, "harness|hendrycksTest-logical_fallacies|5": { "acc": 0.8282208588957055, "acc_stderr": 0.02963471727237104, "acc_norm": 0.8282208588957055, "acc_norm_stderr": 0.02963471727237104 }, "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": 0.8349514563106796, "acc_stderr": 0.03675668832233188, "acc_norm": 0.8349514563106796, "acc_norm_stderr": 0.03675668832233188 }, "harness|hendrycksTest-marketing|5": { "acc": 0.8974358974358975, "acc_stderr": 0.01987565502786745, "acc_norm": 0.8974358974358975, "acc_norm_stderr": 0.01987565502786745 }, "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": 0.859514687100894, "acc_stderr": 0.012426211353093448, "acc_norm": 0.859514687100894, "acc_norm_stderr": 0.012426211353093448 }, "harness|hendrycksTest-moral_disputes|5": { "acc": 0.7658959537572254, "acc_stderr": 0.022797110278071128, "acc_norm": 0.7658959537572254, "acc_norm_stderr": 0.022797110278071128 }, "harness|hendrycksTest-moral_scenarios|5": { "acc": 0.582122905027933, "acc_stderr": 0.016495400635820084, "acc_norm": 0.582122905027933, "acc_norm_stderr": 0.016495400635820084 }, "harness|hendrycksTest-nutrition|5": { "acc": 0.7483660130718954, "acc_stderr": 0.024848018263875195, "acc_norm": 0.7483660130718954, "acc_norm_stderr": 0.024848018263875195 }, "harness|hendrycksTest-philosophy|5": { "acc": 0.7427652733118971, "acc_stderr": 0.024826171289250888, "acc_norm": 0.7427652733118971, "acc_norm_stderr": 0.024826171289250888 }, "harness|hendrycksTest-prehistory|5": { "acc": 0.8117283950617284, "acc_stderr": 0.021751866060815882, "acc_norm": 0.8117283950617284, "acc_norm_stderr": 0.021751866060815882 }, "harness|hendrycksTest-professional_accounting|5": { "acc": 0.574468085106383, "acc_stderr": 0.02949482760014436, "acc_norm": 0.574468085106383, "acc_norm_stderr": 0.02949482760014436 }, "harness|hendrycksTest-professional_law|5": { "acc": 0.5788787483702738, "acc_stderr": 0.012610325733489905, "acc_norm": 0.5788787483702738, "acc_norm_stderr": 0.012610325733489905 }, "harness|hendrycksTest-professional_medicine|5": { "acc": 0.7242647058823529, "acc_stderr": 0.027146271936625162, "acc_norm": 0.7242647058823529, "acc_norm_stderr": 0.027146271936625162 }, "harness|hendrycksTest-professional_psychology|5": { "acc": 0.7565359477124183, "acc_stderr": 0.017362473762146613, "acc_norm": 0.7565359477124183, "acc_norm_stderr": 0.017362473762146613 }, "harness|hendrycksTest-public_relations|5": { "acc": 0.7454545454545455, "acc_stderr": 0.04172343038705383, "acc_norm": 0.7454545454545455, "acc_norm_stderr": 0.04172343038705383 }, "harness|hendrycksTest-security_studies|5": { "acc": 0.7959183673469388, "acc_stderr": 0.025801283475090496, "acc_norm": 0.7959183673469388, "acc_norm_stderr": 0.025801283475090496 }, "harness|hendrycksTest-sociology|5": { "acc": 0.8905472636815921, "acc_stderr": 0.02207632610182466, "acc_norm": 0.8905472636815921, "acc_norm_stderr": 0.02207632610182466 }, "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": 0.03891364495835817, "acc_norm": 0.5120481927710844, "acc_norm_stderr": 0.03891364495835817 }, "harness|hendrycksTest-world_religions|5": { "acc": 0.8596491228070176, "acc_stderr": 0.0266405825391332, "acc_norm": 0.8596491228070176, "acc_norm_stderr": 0.0266405825391332 }, "harness|truthfulqa:mc|0": { "mc1": 0.47980416156670747, "mc1_stderr": 0.01748921684973705, "mc2": 0.658093697491632, "mc2_stderr": 0.014747866760131165 } } ``` ### 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]
CyberHarem/kusakabe_wakaba_idolmastercinderellagirls
2023-09-17T17:40:17.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of kusakabe_wakaba (THE iDOLM@STER: Cinderella Girls) This is the dataset of kusakabe_wakaba (THE iDOLM@STER: Cinderella Girls), containing 97 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 97 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 261 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 97 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 97 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 97 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 97 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 97 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 261 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 261 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 261 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
deepghs/anime_regular_dataset
2023-09-15T17:57:42.000Z
[ "size_categories:1K<n<10K", "license:mit", "art", "region:us" ]
deepghs
null
null
null
0
0
--- license: mit tags: - art size_categories: - 1K<n<10K --- A dataset for regularization during training was created using NAI and [7eu7d7/HCP-Diffusion-datas](https://huggingface.co/datasets/7eu7d7/HCP-Diffusion-datas). The dataset has dimensions of 512x512 and consists of 2000 images.
CyberHarem/ujiie_mutsumi_idolmastercinderellagirls
2023-09-17T17:40:19.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of ujiie_mutsumi (THE iDOLM@STER: Cinderella Girls) This is the dataset of ujiie_mutsumi (THE iDOLM@STER: Cinderella Girls), containing 11 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 11 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 31 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 11 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 11 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 11 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 11 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 11 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 31 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 31 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 31 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/narumiya_yume_idolmastercinderellagirls
2023-09-17T17:40:21.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of narumiya_yume (THE iDOLM@STER: Cinderella Girls) This is the dataset of narumiya_yume (THE iDOLM@STER: Cinderella Girls), containing 90 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 90 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 237 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 90 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 90 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 90 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 90 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 90 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 237 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 237 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 237 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/sawada_marina_idolmastercinderellagirls
2023-09-17T17:40:23.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of sawada_marina (THE iDOLM@STER: Cinderella Girls) This is the dataset of sawada_marina (THE iDOLM@STER: Cinderella Girls), containing 21 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 21 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 57 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 21 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 21 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 21 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 21 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 21 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 57 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 57 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 57 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/oohara_michiru_idolmastercinderellagirls
2023-09-17T17:40:25.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of oohara_michiru (THE iDOLM@STER: Cinderella Girls) This is the dataset of oohara_michiru (THE iDOLM@STER: Cinderella Girls), containing 34 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 34 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 86 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 34 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 34 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 34 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 34 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 34 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 86 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 86 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 86 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/sakakibara_satomi_idolmastercinderellagirls
2023-09-17T17:40:27.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of sakakibara_satomi (THE iDOLM@STER: Cinderella Girls) This is the dataset of sakakibara_satomi (THE iDOLM@STER: Cinderella Girls), containing 62 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 62 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 166 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 62 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 62 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 62 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 62 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 62 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 166 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 166 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 166 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
LDD5522/Rock_Vocals
2023-09-15T18:21:08.000Z
[ "region:us" ]
LDD5522
null
null
null
0
0
Entry not found
CyberHarem/kiba_manami_idolmastercinderellagirls
2023-09-17T17:40:29.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of kiba_manami (THE iDOLM@STER: Cinderella Girls) This is the dataset of kiba_manami (THE iDOLM@STER: Cinderella Girls), containing 56 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 56 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 139 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 56 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 56 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 56 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 56 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 56 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 139 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 139 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 139 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/nonomura_sora_idolmastercinderellagirls
2023-09-17T17:40:31.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of nonomura_sora (THE iDOLM@STER: Cinderella Girls) This is the dataset of nonomura_sora (THE iDOLM@STER: Cinderella Girls), containing 47 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 47 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 123 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 47 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 47 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 47 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 47 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 47 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 123 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 123 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 123 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
bongo2112/diamondplatnumz-SDxl-openpose-output-images
2023-09-16T07:48:10.000Z
[ "region:us" ]
bongo2112
null
null
null
0
0
Entry not found
CyberHarem/munakata_atsumi_idolmastercinderellagirls
2023-09-17T17:40:33.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of munakata_atsumi (THE iDOLM@STER: Cinderella Girls) This is the dataset of munakata_atsumi (THE iDOLM@STER: Cinderella Girls), containing 97 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 97 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 263 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 97 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 97 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 97 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 97 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 97 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 263 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 263 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 263 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |
CyberHarem/helen_idolmastercinderellagirls
2023-09-17T17:40:35.000Z
[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]
CyberHarem
null
null
null
0
0
--- license: mit task_categories: - text-to-image tags: - art - not-for-all-audiences size_categories: - n<1K --- # Dataset of helen (THE iDOLM@STER: Cinderella Girls) This is the dataset of helen (THE iDOLM@STER: Cinderella Girls), containing 27 images and their tags. Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)). | Name | Images | Download | Description | |:------------|---------:|:------------------------------------|:-------------------------------------------------------------------------| | raw | 27 | [Download](dataset-raw.zip) | Raw data with meta information. | | raw-stage3 | 75 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. | | 384x512 | 27 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. | | 512x512 | 27 | [Download](dataset-512x512.zip) | 512x512 aligned dataset. | | 512x704 | 27 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. | | 640x640 | 27 | [Download](dataset-640x640.zip) | 640x640 aligned dataset. | | 640x880 | 27 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. | | stage3-640 | 75 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. | | stage3-800 | 75 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. | | stage3-1200 | 75 | [Download](dataset-stage3-1200.zip) | 3-stage cropped dataset with the shorter side not exceeding 1200 pixels. |