Datasets:

librarian-bots

/

dataset_cards_with_metadata

like 11

Goldeath/Gow

Goldeath

--- license: openrail ---

Gdzinhos/gabrieldearo

Gdzinhos

--- license: openrail ---

kakasher/house-plant-species

kakasher

--- license: cc-by-3.0 task_categories: - image-classification language: - en tags: - biology pretty_name: House Plant Species size_categories: - 10K<n<100K --- This plant image dataset consists of 14,790 images categorized into 47 distinct plant species classes. The dataset was compiled by collecting images from Bing Images and manually curating them, although not by professional biologist. I collected this images for a project aimed at classifying plant species as either toxic or safe for cats. Key Features: - Total Images: 14,790 - Number of Classes: 47 - Image Source: Collected from Bing Images - Curation Method: Manual cleaning by non-expert Dataset Composition: - The number of images per class varies significantly, ranging from 66 (Yucca) to 547 (Monstera Deliciosa). - Some well-represented classes include Chinese evergreen (514 images), Dumb Cane (541 images), and Monstera Deliciosa (547 images). - Classes with fewer images include Yucca (66 images), Kalanchoe (130 images), and Asparagus Fern (169 images). Image Characteristics: - Images vary in quality and resolution. - The dataset includes both whole plant images and close-ups of specific plant parts. - Plants are placed indoor and outdoors - Images are organized into separate folders for each plant category. The current dataset is for personal use only due to copyright considerations

DrNicefellow/Llama_3.1_cri_thinking_qset3_da_r2_labeled

DrNicefellow

--- dataset_info: features: - name: question dtype: string - name: answer1 dtype: string - name: answer2 dtype: string - name: prefernce dtype: string - name: reason dtype: string splits: - name: train num_bytes: 815679 num_examples: 104 download_size: 401008 dataset_size: 815679 configs: - config_name: default data_files: - split: train path: data/train-* ---

kywch/mimicgen_coffee_preparation

kywch

--- dataset_info: features: - name: observation.state sequence: float32 length: 145 - name: action sequence: float32 length: 7 - name: next.done dtype: bool - name: next.reward dtype: float32 - name: next.success dtype: bool - name: frame_index dtype: int64 - name: timestamp dtype: float32 - name: episode_index dtype: int64 - name: observation.images.agentview dtype: video_frame - name: observation.images.agentview_lowres dtype: video_frame - name: observation.images.robot0_eye_in_hand dtype: video_frame - name: observation.images.robot0_eye_in_hand_lowres dtype: video_frame - name: index dtype: int64 splits: - name: train num_bytes: 5825326 num_examples: 6900 download_size: 5920547 dataset_size: 5825326 configs: - config_name: default data_files: - split: train path: data/train-* ---

mjschock/chat_threads

mjschock

--- dataset_info: features: - name: documents sequence: 'null' - name: messages list: - name: content dtype: string - name: name dtype: string - name: role dtype: string - name: tool_call_id dtype: string - name: tool_calls list: - name: function struct: - name: arguments dtype: string - name: name dtype: string - name: id dtype: string - name: type dtype: string - name: tools list: - name: function struct: - name: description dtype: string - name: name dtype: string - name: parameters struct: - name: properties struct: - name: altitude struct: - name: type dtype: string - name: color struct: - name: enum sequence: string - name: type dtype: string - name: coordinates struct: - name: type dtype: string - name: direction struct: - name: enum sequence: string - name: type dtype: string - name: distance struct: - name: type dtype: string - name: duration struct: - name: type dtype: string - name: format struct: - name: enum sequence: string - name: type dtype: string - name: location struct: - name: description dtype: string - name: enum sequence: string - name: type dtype: string - name: mode struct: - name: enum sequence: string - name: type dtype: string - name: pan struct: - name: type dtype: string - name: pattern struct: - name: enum sequence: string - name: type dtype: string - name: speed struct: - name: minimum dtype: int64 - name: type dtype: string - name: status struct: - name: enum sequence: string - name: type dtype: string - name: tilt struct: - name: type dtype: string - name: required sequence: string - name: type dtype: string - name: type dtype: string splits: - name: train num_bytes: 281278.2211538461 num_examples: 83 - name: test num_bytes: 37277.83653846154 num_examples: 11 - name: validation num_bytes: 33888.942307692305 num_examples: 10 download_size: 86696 dataset_size: 352445.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - split: validation path: data/validation-* ---

amuvarma/6_layer_interleave-102345-500k-1

amuvarma

--- dataset_info: features: - name: transcript dtype: string - name: facodec_0 sequence: int64 - name: facodec_1 sequence: int64 - name: facodec_2 sequence: int64 - name: facodec_3 sequence: int64 - name: facodec_4 sequence: int64 - name: facodec_5 sequence: int64 - name: tokenised_text sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 82113428235 num_examples: 500000 download_size: 16807790915 dataset_size: 82113428235 configs: - config_name: default data_files: - split: train path: data/train-* ---

JMMMU/JMMMU

JMMMU

--- language: - ja license: mit size_categories: - 1K<n<10K task_categories: - question-answering - visual-question-answering - multiple-choice pretty_name: JMMMU dataset_info: - config_name: Accounting features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 1745326 num_examples: 30 download_size: 1755488 dataset_size: 1745326 - config_name: Agriculture features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 119223364 num_examples: 30 download_size: 119235669 dataset_size: 119223364 - config_name: Architecture_and_Engineering features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 1098801 num_examples: 30 download_size: 1111702 dataset_size: 1098801 - config_name: Basic_Medical_Science features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 4187246 num_examples: 30 download_size: 4206073 dataset_size: 4187246 - config_name: Biology features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 8631133.0 num_examples: 30 download_size: 8641581 dataset_size: 8631133.0 - config_name: Chemistry features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 1429635 num_examples: 30 download_size: 1442400 dataset_size: 1429635 - config_name: Clinical_Medicine features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 10885064 num_examples: 30 download_size: 10900204 dataset_size: 10885064 - config_name: Computer_Science features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 2241115 num_examples: 30 download_size: 2258448 dataset_size: 2241115 - config_name: Design features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 17932660 num_examples: 30 download_size: 16244765 dataset_size: 17932660 - config_name: Diagnostics_and_Laboratory_Medicine features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 37109516 num_examples: 30 download_size: 37099650 dataset_size: 37109516 - config_name: Economics features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 1927531 num_examples: 30 download_size: 1907159 dataset_size: 1927531 - config_name: Electronics features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 611753 num_examples: 30 download_size: 623002 dataset_size: 611753 - config_name: Energy_and_Power features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 2064610 num_examples: 30 download_size: 2077963 dataset_size: 2064610 - config_name: Finance features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 1766246 num_examples: 30 download_size: 1728074 dataset_size: 1766246 - config_name: Japanese_Art features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 158152012.0 num_examples: 150 download_size: 93900262 dataset_size: 158152012.0 - config_name: Japanese_Heritage features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 89568638.0 num_examples: 150 download_size: 48206821 dataset_size: 89568638.0 - config_name: Japanese_History features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 201841322.0 num_examples: 150 download_size: 99922433 dataset_size: 201841322.0 - config_name: Manage features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 3469889 num_examples: 30 download_size: 3479364 dataset_size: 3469889 - config_name: Marketing features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 1999418 num_examples: 30 download_size: 1996428 dataset_size: 1999418 - config_name: Materials features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 2464475 num_examples: 30 download_size: 2479248 dataset_size: 2464475 - config_name: Math features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 1670610 num_examples: 30 download_size: 1681621 dataset_size: 1670610 - config_name: Mechanical_Engineering features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 974336 num_examples: 30 download_size: 984949 dataset_size: 974336 - config_name: Music features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 9099677 num_examples: 30 download_size: 9111911 dataset_size: 9099677 - config_name: Pharmacy features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 1753886 num_examples: 30 download_size: 1657737 dataset_size: 1753886 - config_name: Physics features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 1119745 num_examples: 30 download_size: 1131424 dataset_size: 1119745 - config_name: Psychology features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 4825377 num_examples: 30 download_size: 4843680 dataset_size: 4825377 - config_name: Public_Health features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 1922749 num_examples: 30 download_size: 1913479 dataset_size: 1922749 - config_name: World_History features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_1_license dtype: string - name: image_1_attribution dtype: string - name: image_1_use_original_mmmu dtype: bool - name: image_2 dtype: image - name: image_2_license dtype: string - name: image_2_attribution dtype: string - name: image_2_use_original_mmmu dtype: bool - name: image_3 dtype: image - name: image_3_license dtype: string - name: image_3_attribution dtype: string - name: image_3_use_original_mmmu dtype: bool - name: image_4 dtype: image - name: image_4_license dtype: string - name: image_4_attribution dtype: string - name: image_4_use_original_mmmu dtype: bool - name: image_5 dtype: image - name: image_5_license dtype: string - name: image_5_attribution dtype: string - name: image_5_use_original_mmmu dtype: bool - name: image_6 dtype: image - name: image_6_license dtype: string - name: image_6_attribution dtype: string - name: image_6_use_original_mmmu dtype: bool - name: image_7 dtype: image - name: image_7_license dtype: string - name: image_7_attribution dtype: string - name: image_7_use_original_mmmu dtype: bool - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: test num_bytes: 206972521.0 num_examples: 150 download_size: 170275817 dataset_size: 206972521.0 configs: - config_name: Accounting data_files: - split: test path: Accounting/test-* - config_name: Agriculture data_files: - split: test path: Agriculture/test-* - config_name: Architecture_and_Engineering data_files: - split: test path: Architecture_and_Engineering/test-* - config_name: Basic_Medical_Science data_files: - split: test path: Basic_Medical_Science/test-* - config_name: Biology data_files: - split: test path: Biology/test-* - config_name: Chemistry data_files: - split: test path: Chemistry/test-* - config_name: Clinical_Medicine data_files: - split: test path: Clinical_Medicine/test-* - config_name: Computer_Science data_files: - split: test path: Computer_Science/test-* - config_name: Design data_files: - split: test path: Design/test-* - config_name: Diagnostics_and_Laboratory_Medicine data_files: - split: test path: Diagnostics_and_Laboratory_Medicine/test-* - config_name: Economics data_files: - split: test path: Economics/test-* - config_name: Electronics data_files: - split: test path: Electronics/test-* - config_name: Energy_and_Power data_files: - split: test path: Energy_and_Power/test-* - config_name: Finance data_files: - split: test path: Finance/test-* - config_name: Japanese_Art data_files: - split: test path: Japanese_Art/test-* - config_name: Japanese_Heritage data_files: - split: test path: Japanese_Heritage/test-* - config_name: Japanese_History data_files: - split: test path: Japanese_History/test-* - config_name: Manage data_files: - split: test path: Manage/test-* - config_name: Marketing data_files: - split: test path: Marketing/test-* - config_name: Materials data_files: - split: test path: Materials/test-* - config_name: Math data_files: - split: test path: Math/test-* - config_name: Mechanical_Engineering data_files: - split: test path: Mechanical_Engineering/test-* - config_name: Music data_files: - split: test path: Music/test-* - config_name: Pharmacy data_files: - split: test path: Pharmacy/test-* - config_name: Physics data_files: - split: test path: Physics/test-* - config_name: Psychology data_files: - split: test path: Psychology/test-* - config_name: Public_Health data_files: - split: test path: Public_Health/test-* - config_name: World_History data_files: - split: test path: World_History/test-* --- # JMMMU: A Japanese Massive Multi-discipline Multimodal Understanding Benchmark [**🌐 Homepage**](https://mmmu-japanese-benchmark.github.io/JMMMU/) | [**🤗 Dataset**](https://huggingface.co/datasets/JMMMU/JMMMU/) | [**🏆 HF Leaderboard**](https://huggingface.co/spaces/JMMMU/JMMMU_Leaderboard) | [**📖 arXiv (coming soon)**]() | [**💻 Code**](https://github.com/EvolvingLMMs-Lab/lmms-eval) ## Introduction We introduce **JMMMU** (***Japanese MMMU***), a multimodal benchmark that can truly evaluate LMM performance in Japanese. To create JMMMU, we first carefully analyzed the existing [MMMU benchmark](https://huggingface.co/datasets/MMMU/MMMU) and examined its cultural dependencies. Then, for questions in culture-agnostic subjects, we employed native Japanese speakers who are experts for each subject, and asked to translate ***both the texts and images*** (e.g. the title of a graph) into Japanese. Further, we replaced culture-dependent subjects with new subjects that are well aligned with Japanese culture. As a result, JMMMU consists of **720 translation-based (Culture Agnostic)** and **600 brand-new questions (Culture Specific)**, for a **total of 1,320 questions**, updating the size of the existing culture-aware Japanese benchmark by >10x. ## 🔔News - **🚀[2024-09-30]: We released JMMMU dataset🌟** ## 🏆 Mini-Leaderboard We show a mini-leaderboard here and please find more information in [**🏆 HF Leaderboard**](https://huggingface.co/spaces/JMMMU/JMMMU_Leaderboard). | Model | Overall (1,320) | Culture Specific (600) | Culture Agnostic (720) | |:----------------------------------------------------------------------------------------------------|:---------------:|:----------------------:|:----------------------:| | GPT-4o* | **58.0** | **65.8** | **51.5** | | [LLaVA-OneVision 7B](https://huggingface.co/lmms-lab/llava-onevision-qwen2-7b-ov)* | *40.5* | 42.7 | *38.6* | | [LLaVA-NeXT 34B](https://huggingface.co/liuhaotian/llava-v1.6-34b)* | 40.1 | *43.0* | 37.6 | | [InternVL2 8B](https://huggingface.co/OpenGVLab/InternVL2-8B)* | 38.0 | 42.0 | 34.7 | | [EvoVLM-JP v2](https://huggingface.co/SakanaAI/Llama-3-EvoVLM-JP-v2)* | 35.5 | 41.3 | 30.6 | | [Phi-3.5 Vision](https://huggingface.co/microsoft/Phi-3.5-vision-instruct)* | 32.5 | 34.3 | 31.0 | | [LLaVA CALM2](https://huggingface.co/cyberagent/llava-calm2-siglip)* | 32.2 | 38.5 | 26.9 | | [LLaVA-NeXT 13B](https://huggingface.co/liuhaotian/llava-v1.6-vicuna-13b)* | 31.3 | 33.7 | 29.3 | | [Phi-3 Vision](https://huggingface.co/microsoft/Phi-3-vision-128k-instruct)* | 29.2 | 25.8 | 32.1 | | [xGen-MM (BLIP-3)](https://huggingface.co/Salesforce/xgen-mm-phi3-mini-instruct-interleave-r-v1.5)* | 28.6 | 28.3 | 28.7 | | [LLaVA-OneVision 0.5B](https://huggingface.co/lmms-lab/llava-onevision-qwen2-0.5b-ov)* | 25.5 | 23.5 | 27.2 | | | | | | | GPT-4o (only text)* | 38.0 | 33.0 | 42.2 | | Random Choice* | 24.8 | 25.0 | 24.6 | *: results provided by the authors. ## Limitations Despite its comprehensive nature, both JMMMU and the original MMMU, like any benchmark, have their limitations. While the manual curation process is thorough, it may still introduce human biases. In addition, the focus on college-level subjects might not be enough to fully test an Expert AGI for Japanese. However, we believe that achieving strong performance on JMMMU is crucial for an Expert AGI to demonstrate broad and deep subject knowledge, expert-level understanding, and reasoning abilities in Japanese. We hope that our efforts will inspire research not only in Japanese but also in other non-English languages and accelerate a promising and exciting future research field, *the creation of AI systems for everyone*. ## Disclaimers Regarding the newly used images in JMMMU, please refer to the licenses and citations specified in the dataset. For images used from MMMU, please refer to original dataset ([MMMU/MMMU](https://huggingface.co/datasets/MMMU/MMMU)). Should you encounter any data samples potentially breaching the copyright or licensing regulations of any site, we encourage you to notify us. Upon verification, such samples will be promptly removed. ## Contact - Shota Onohara: onohara@hal.t.u-tokyo.ac.jp - Atsuyuki Miyai: miyai@cvm.t.u-tokyo.ac.jp - Yuki Imajuku: imajuku@hal.t.u-tokyo.ac.jp - Kazuki Egashira: egashira@hal.t.u-tokyo.ac.jp - Jeonghun Baek: beak@hal.t.u-tokyo.ac.jp ## Citation **BibTeX:** ```bibtex @misc{onohara2024jmmmu, title={JMMMU: A Japanese Massive Multi-discipline Multimodal Understanding Benchmark}, author={Shota Onohara and Atsuyuki Miyai and Yuki Imajuku and Kazuki Egashira and Jeonghun Baek and Xiang Yue and Graham Neubig and Kiyoharu Aizawa}, url={https://huggingface.co/datasets/JMMMU/JMMMU}, year={2024} } ```

tukey/sampled-arxiv-ocr001_validation

tukey

--- dataset_info: features: - name: id dtype: string - name: messages list: - name: content dtype: string - name: role dtype: string - name: images list: - name: bytes dtype: binary - name: path dtype: 'null' splits: - name: train num_bytes: 409473011 num_examples: 500 download_size: 371703757 dataset_size: 409473011 configs: - config_name: default data_files: - split: train path: data/train-* ---

Kortix/FastApply-v1

Kortix

--- license: apache-2.0 ---

nophin-psr/nex-dev

nophin-psr

--- dataset_info: features: - name: image sequence: image - name: ground_truth dtype: string - name: instruction dtype: string splits: - name: train num_bytes: 56.0 num_examples: 1 - name: validation num_bytes: 56.0 num_examples: 1 download_size: 4672 dataset_size: 112.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

Nophin/nex-dev

Nophin

--- dataset_info: features: - name: image sequence: image - name: ground_truth dtype: string - name: instruction dtype: string splits: - name: train num_bytes: 56.0 num_examples: 1 - name: validation num_bytes: 56.0 num_examples: 1 download_size: 4672 dataset_size: 112.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

Nophin/nrrqa-dev

Nophin

--- dataset_info: features: - name: image dtype: image - name: ground_truth dtype: string - name: instruction dtype: string splits: - name: train num_bytes: 3944753.0 num_examples: 10 - name: validation num_bytes: 3944753.0 num_examples: 10 download_size: 1569260 dataset_size: 7889506.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

Nophin/nex_dev

Nophin

--- dataset_info: features: - name: image sequence: image - name: ground_truth dtype: string - name: instruction dtype: string splits: - name: train num_bytes: 56.0 num_examples: 1 - name: validation num_bytes: 56.0 num_examples: 1 download_size: 4672 dataset_size: 112.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

0xBreath/holistic

0xBreath

--- dataset_info: features: - name: text dtype: string - name: input_ids sequence: int32 - name: token_type_ids sequence: int8 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 973491 num_examples: 3 download_size: 563400 dataset_size: 973491 configs: - config_name: default data_files: - split: train path: data/train-* ---

tukey/document_ocr_sharegpt

tukey

--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string - name: images list: - name: bytes dtype: binary - name: path dtype: 'null' splits: - name: train num_bytes: 20480711 num_examples: 27 download_size: 20180498 dataset_size: 20480711 configs: - config_name: default data_files: - split: train path: data/train-* ---

nurungzi/custom_data_v1

nurungzi

--- dataset_info: features: - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 3366 num_examples: 10 download_size: 5115 dataset_size: 3366 configs: - config_name: default data_files: - split: train path: data/train-* ---

open-llm-leaderboard/MaziyarPanahi__calme-2.6-qwen2-7b-details

open-llm-leaderboard

--- pretty_name: Evaluation run of MaziyarPanahi/calme-2.6-qwen2-7b dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [MaziyarPanahi/calme-2.6-qwen2-7b](https://huggingface.co/MaziyarPanahi/calme-2.6-qwen2-7b)\n\ The dataset is composed of 38 configuration(s), each one corresponding 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.\n\nTo load the details from a run, you can for instance do the following:\n\ ```python\nfrom datasets import load_dataset\ndata = load_dataset(\n\t\"open-llm-leaderboard/MaziyarPanahi__calme-2.6-qwen2-7b-details\"\ ,\n\tname=\"MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_boolean_expressions\"\ ,\n\tsplit=\"latest\"\n)\n```\n\n## Latest results\n\nThese are the [latest results\ \ from run 2024-09-29T23-22-32.652583](https://huggingface.co/datasets/open-llm-leaderboard/MaziyarPanahi__calme-2.6-qwen2-7b-details/blob/main/MaziyarPanahi__calme-2.6-qwen2-7b/results_2024-09-29T23-22-32.652583.json)\ \ (note that there 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 \"leaderboard\": {\n\ \ \"inst_level_loose_acc,none\": 0.4364508393285372,\n \"\ inst_level_loose_acc_stderr,none\": \"N/A\",\n \"inst_level_strict_acc,none\"\ : 0.41127098321342925,\n \"inst_level_strict_acc_stderr,none\": \"N/A\"\ ,\n \"prompt_level_loose_acc,none\": 0.31053604436229204,\n \ \ \"prompt_level_loose_acc_stderr,none\": 0.019912001290591244,\n \"\ acc_norm,none\": 0.45453366195356076,\n \"acc_norm_stderr,none\": 0.0053168263981244425,\n\ \ \"prompt_level_strict_acc,none\": 0.27726432532347506,\n \ \ \"prompt_level_strict_acc_stderr,none\": 0.019263706963479364,\n \"\ acc,none\": 0.3731715425531915,\n \"acc_stderr,none\": 0.004409382233559137,\n\ \ \"exact_match,none\": 0.11253776435045318,\n \"exact_match_stderr,none\"\ : 0.008319732099704257,\n \"alias\": \"leaderboard\"\n },\n \ \ \"leaderboard_bbh\": {\n \"acc_norm,none\": 0.4893247700052074,\n\ \ \"acc_norm_stderr,none\": 0.006146856128835226,\n \"alias\"\ : \" - leaderboard_bbh\"\n },\n \"leaderboard_bbh_boolean_expressions\"\ : {\n \"acc_norm,none\": 0.832,\n \"acc_norm_stderr,none\"\ : 0.0236928132054926,\n \"alias\": \" - leaderboard_bbh_boolean_expressions\"\ \n },\n \"leaderboard_bbh_causal_judgement\": {\n \"acc_norm,none\"\ : 0.6577540106951871,\n \"acc_norm_stderr,none\": 0.034789201769068225,\n\ \ \"alias\": \" - leaderboard_bbh_causal_judgement\"\n },\n \ \ \"leaderboard_bbh_date_understanding\": {\n \"acc_norm,none\"\ : 0.416,\n \"acc_norm_stderr,none\": 0.031235856237014574,\n \ \ \"alias\": \" - leaderboard_bbh_date_understanding\"\n },\n \ \ \"leaderboard_bbh_disambiguation_qa\": {\n \"acc_norm,none\": 0.588,\n\ \ \"acc_norm_stderr,none\": 0.031191596026022894,\n \"alias\"\ : \" - leaderboard_bbh_disambiguation_qa\"\n },\n \"leaderboard_bbh_formal_fallacies\"\ : {\n \"acc_norm,none\": 0.568,\n \"acc_norm_stderr,none\"\ : 0.031391810765429407,\n \"alias\": \" - leaderboard_bbh_formal_fallacies\"\ \n },\n \"leaderboard_bbh_geometric_shapes\": {\n \"acc_norm,none\"\ : 0.472,\n \"acc_norm_stderr,none\": 0.0316364895315444,\n \ \ \"alias\": \" - leaderboard_bbh_geometric_shapes\"\n },\n \"leaderboard_bbh_hyperbaton\"\ : {\n \"acc_norm,none\": 0.656,\n \"acc_norm_stderr,none\"\ : 0.030104503392316385,\n \"alias\": \" - leaderboard_bbh_hyperbaton\"\ \n },\n \"leaderboard_bbh_logical_deduction_five_objects\": {\n \ \ \"acc_norm,none\": 0.412,\n \"acc_norm_stderr,none\": 0.031191596026022898,\n\ \ \"alias\": \" - leaderboard_bbh_logical_deduction_five_objects\"\n\ \ },\n \"leaderboard_bbh_logical_deduction_seven_objects\": {\n \ \ \"acc_norm,none\": 0.364,\n \"acc_norm_stderr,none\": 0.03049155522040555,\n\ \ \"alias\": \" - leaderboard_bbh_logical_deduction_seven_objects\"\n\ \ },\n \"leaderboard_bbh_logical_deduction_three_objects\": {\n \ \ \"acc_norm,none\": 0.592,\n \"acc_norm_stderr,none\": 0.0311452098465485,\n\ \ \"alias\": \" - leaderboard_bbh_logical_deduction_three_objects\"\n\ \ },\n \"leaderboard_bbh_movie_recommendation\": {\n \"\ acc_norm,none\": 0.672,\n \"acc_norm_stderr,none\": 0.029752391824475363,\n\ \ \"alias\": \" - leaderboard_bbh_movie_recommendation\"\n },\n\ \ \"leaderboard_bbh_navigate\": {\n \"acc_norm,none\": 0.64,\n\ \ \"acc_norm_stderr,none\": 0.030418764025174995,\n \"alias\"\ : \" - leaderboard_bbh_navigate\"\n },\n \"leaderboard_bbh_object_counting\"\ : {\n \"acc_norm,none\": 0.332,\n \"acc_norm_stderr,none\"\ : 0.0298440390474659,\n \"alias\": \" - leaderboard_bbh_object_counting\"\ \n },\n \"leaderboard_bbh_penguins_in_a_table\": {\n \"\ acc_norm,none\": 0.5,\n \"acc_norm_stderr,none\": 0.041522739926869986,\n\ \ \"alias\": \" - leaderboard_bbh_penguins_in_a_table\"\n },\n\ \ \"leaderboard_bbh_reasoning_about_colored_objects\": {\n \"\ acc_norm,none\": 0.444,\n \"acc_norm_stderr,none\": 0.03148684942554574,\n\ \ \"alias\": \" - leaderboard_bbh_reasoning_about_colored_objects\"\n\ \ },\n \"leaderboard_bbh_ruin_names\": {\n \"acc_norm,none\"\ : 0.568,\n \"acc_norm_stderr,none\": 0.0313918107654294,\n \ \ \"alias\": \" - leaderboard_bbh_ruin_names\"\n },\n \"leaderboard_bbh_salient_translation_error_detection\"\ : {\n \"acc_norm,none\": 0.408,\n \"acc_norm_stderr,none\"\ : 0.031145209846548505,\n \"alias\": \" - leaderboard_bbh_salient_translation_error_detection\"\ \n },\n \"leaderboard_bbh_snarks\": {\n \"acc_norm,none\"\ : 0.6348314606741573,\n \"acc_norm_stderr,none\": 0.03619005678691265,\n\ \ \"alias\": \" - leaderboard_bbh_snarks\"\n },\n \"leaderboard_bbh_sports_understanding\"\ : {\n \"acc_norm,none\": 0.776,\n \"acc_norm_stderr,none\"\ : 0.0264213616873479,\n \"alias\": \" - leaderboard_bbh_sports_understanding\"\ \n },\n \"leaderboard_bbh_temporal_sequences\": {\n \"\ acc_norm,none\": 0.276,\n \"acc_norm_stderr,none\": 0.02832853727421135,\n\ \ \"alias\": \" - leaderboard_bbh_temporal_sequences\"\n },\n\ \ \"leaderboard_bbh_tracking_shuffled_objects_five_objects\": {\n \ \ \"acc_norm,none\": 0.152,\n \"acc_norm_stderr,none\": 0.022752024491765464,\n\ \ \"alias\": \" - leaderboard_bbh_tracking_shuffled_objects_five_objects\"\ \n },\n \"leaderboard_bbh_tracking_shuffled_objects_seven_objects\"\ : {\n \"acc_norm,none\": 0.104,\n \"acc_norm_stderr,none\"\ : 0.01934510097484389,\n \"alias\": \" - leaderboard_bbh_tracking_shuffled_objects_seven_objects\"\ \n },\n \"leaderboard_bbh_tracking_shuffled_objects_three_objects\"\ : {\n \"acc_norm,none\": 0.284,\n \"acc_norm_stderr,none\"\ : 0.028576958730437408,\n \"alias\": \" - leaderboard_bbh_tracking_shuffled_objects_three_objects\"\ \n },\n \"leaderboard_bbh_web_of_lies\": {\n \"acc_norm,none\"\ : 0.484,\n \"acc_norm_stderr,none\": 0.031669985030107414,\n \ \ \"alias\": \" - leaderboard_bbh_web_of_lies\"\n },\n \"leaderboard_gpqa\"\ : {\n \"acc_norm,none\": 0.2843959731543625,\n \"acc_norm_stderr,none\"\ : 0.013081070677064183,\n \"alias\": \" - leaderboard_gpqa\"\n \ \ },\n \"leaderboard_gpqa_diamond\": {\n \"acc_norm,none\": 0.29292929292929293,\n\ \ \"acc_norm_stderr,none\": 0.03242497958178817,\n \"alias\"\ : \" - leaderboard_gpqa_diamond\"\n },\n \"leaderboard_gpqa_extended\"\ : {\n \"acc_norm,none\": 0.2893772893772894,\n \"acc_norm_stderr,none\"\ : 0.01942466387226183,\n \"alias\": \" - leaderboard_gpqa_extended\"\ \n },\n \"leaderboard_gpqa_main\": {\n \"acc_norm,none\"\ : 0.27455357142857145,\n \"acc_norm_stderr,none\": 0.02110874729063386,\n\ \ \"alias\": \" - leaderboard_gpqa_main\"\n },\n \"leaderboard_ifeval\"\ : {\n \"prompt_level_strict_acc,none\": 0.27726432532347506,\n \ \ \"prompt_level_strict_acc_stderr,none\": 0.019263706963479364,\n \ \ \"inst_level_strict_acc,none\": 0.41127098321342925,\n \"inst_level_strict_acc_stderr,none\"\ : \"N/A\",\n \"prompt_level_loose_acc,none\": 0.31053604436229204,\n\ \ \"prompt_level_loose_acc_stderr,none\": 0.019912001290591244,\n \ \ \"inst_level_loose_acc,none\": 0.4364508393285372,\n \"inst_level_loose_acc_stderr,none\"\ : \"N/A\",\n \"alias\": \" - leaderboard_ifeval\"\n },\n \ \ \"leaderboard_math_hard\": {\n \"exact_match,none\": 0.11253776435045318,\n\ \ \"exact_match_stderr,none\": 0.008319732099704257,\n \"\ alias\": \" - leaderboard_math_hard\"\n },\n \"leaderboard_math_algebra_hard\"\ : {\n \"exact_match,none\": 0.2182410423452769,\n \"exact_match_stderr,none\"\ : 0.02361260670412736,\n \"alias\": \" - leaderboard_math_algebra_hard\"\ \n },\n \"leaderboard_math_counting_and_prob_hard\": {\n \ \ \"exact_match,none\": 0.06504065040650407,\n \"exact_match_stderr,none\"\ : 0.022325895462591887,\n \"alias\": \" - leaderboard_math_counting_and_prob_hard\"\ \n },\n \"leaderboard_math_geometry_hard\": {\n \"exact_match,none\"\ : 0.015151515151515152,\n \"exact_match_stderr,none\": 0.010672768637174743,\n\ \ \"alias\": \" - leaderboard_math_geometry_hard\"\n },\n \ \ \"leaderboard_math_intermediate_algebra_hard\": {\n \"exact_match,none\"\ : 0.03214285714285714,\n \"exact_match_stderr,none\": 0.010559558661753189,\n\ \ \"alias\": \" - leaderboard_math_intermediate_algebra_hard\"\n \ \ },\n \"leaderboard_math_num_theory_hard\": {\n \"exact_match,none\"\ : 0.07142857142857142,\n \"exact_match_stderr,none\": 0.020820824576076362,\n\ \ \"alias\": \" - leaderboard_math_num_theory_hard\"\n },\n \ \ \"leaderboard_math_prealgebra_hard\": {\n \"exact_match,none\"\ : 0.24870466321243523,\n \"exact_match_stderr,none\": 0.03119584087770031,\n\ \ \"alias\": \" - leaderboard_math_prealgebra_hard\"\n },\n \ \ \"leaderboard_math_precalculus_hard\": {\n \"exact_match,none\"\ : 0.02962962962962963,\n \"exact_match_stderr,none\": 0.014648038602753778,\n\ \ \"alias\": \" - leaderboard_math_precalculus_hard\"\n },\n\ \ \"leaderboard_mmlu_pro\": {\n \"acc,none\": 0.3731715425531915,\n\ \ \"acc_stderr,none\": 0.004409382233559137,\n \"alias\":\ \ \" - leaderboard_mmlu_pro\"\n },\n \"leaderboard_musr\": {\n \ \ \"acc_norm,none\": 0.4576719576719577,\n \"acc_norm_stderr,none\"\ : 0.01788578586514914,\n \"alias\": \" - leaderboard_musr\"\n \ \ },\n \"leaderboard_musr_murder_mysteries\": {\n \"acc_norm,none\"\ : 0.536,\n \"acc_norm_stderr,none\": 0.031603975145223735,\n \ \ \"alias\": \" - leaderboard_musr_murder_mysteries\"\n },\n \"\ leaderboard_musr_object_placements\": {\n \"acc_norm,none\": 0.33984375,\n\ \ \"acc_norm_stderr,none\": 0.029661487249077814,\n \"alias\"\ : \" - leaderboard_musr_object_placements\"\n },\n \"leaderboard_musr_team_allocation\"\ : {\n \"acc_norm,none\": 0.5,\n \"acc_norm_stderr,none\":\ \ 0.031686212526223896,\n \"alias\": \" - leaderboard_musr_team_allocation\"\ \n }\n },\n \"leaderboard\": {\n \"inst_level_loose_acc,none\"\ : 0.4364508393285372,\n \"inst_level_loose_acc_stderr,none\": \"N/A\",\n\ \ \"inst_level_strict_acc,none\": 0.41127098321342925,\n \"inst_level_strict_acc_stderr,none\"\ : \"N/A\",\n \"prompt_level_loose_acc,none\": 0.31053604436229204,\n \ \ \"prompt_level_loose_acc_stderr,none\": 0.019912001290591244,\n \"acc_norm,none\"\ : 0.45453366195356076,\n \"acc_norm_stderr,none\": 0.0053168263981244425,\n\ \ \"prompt_level_strict_acc,none\": 0.27726432532347506,\n \"prompt_level_strict_acc_stderr,none\"\ : 0.019263706963479364,\n \"acc,none\": 0.3731715425531915,\n \"acc_stderr,none\"\ : 0.004409382233559137,\n \"exact_match,none\": 0.11253776435045318,\n \ \ \"exact_match_stderr,none\": 0.008319732099704257,\n \"alias\": \"\ leaderboard\"\n },\n \"leaderboard_bbh\": {\n \"acc_norm,none\": 0.4893247700052074,\n\ \ \"acc_norm_stderr,none\": 0.006146856128835226,\n \"alias\": \"\ \ - leaderboard_bbh\"\n },\n \"leaderboard_bbh_boolean_expressions\": {\n\ \ \"acc_norm,none\": 0.832,\n \"acc_norm_stderr,none\": 0.0236928132054926,\n\ \ \"alias\": \" - leaderboard_bbh_boolean_expressions\"\n },\n \"\ leaderboard_bbh_causal_judgement\": {\n \"acc_norm,none\": 0.6577540106951871,\n\ \ \"acc_norm_stderr,none\": 0.034789201769068225,\n \"alias\": \"\ \ - leaderboard_bbh_causal_judgement\"\n },\n \"leaderboard_bbh_date_understanding\"\ : {\n \"acc_norm,none\": 0.416,\n \"acc_norm_stderr,none\": 0.031235856237014574,\n\ \ \"alias\": \" - leaderboard_bbh_date_understanding\"\n },\n \"leaderboard_bbh_disambiguation_qa\"\ : {\n \"acc_norm,none\": 0.588,\n \"acc_norm_stderr,none\": 0.031191596026022894,\n\ \ \"alias\": \" - leaderboard_bbh_disambiguation_qa\"\n },\n \"leaderboard_bbh_formal_fallacies\"\ : {\n \"acc_norm,none\": 0.568,\n \"acc_norm_stderr,none\": 0.031391810765429407,\n\ \ \"alias\": \" - leaderboard_bbh_formal_fallacies\"\n },\n \"leaderboard_bbh_geometric_shapes\"\ : {\n \"acc_norm,none\": 0.472,\n \"acc_norm_stderr,none\": 0.0316364895315444,\n\ \ \"alias\": \" - leaderboard_bbh_geometric_shapes\"\n },\n \"leaderboard_bbh_hyperbaton\"\ : {\n \"acc_norm,none\": 0.656,\n \"acc_norm_stderr,none\": 0.030104503392316385,\n\ \ \"alias\": \" - leaderboard_bbh_hyperbaton\"\n },\n \"leaderboard_bbh_logical_deduction_five_objects\"\ : {\n \"acc_norm,none\": 0.412,\n \"acc_norm_stderr,none\": 0.031191596026022898,\n\ \ \"alias\": \" - leaderboard_bbh_logical_deduction_five_objects\"\n \ \ },\n \"leaderboard_bbh_logical_deduction_seven_objects\": {\n \"acc_norm,none\"\ : 0.364,\n \"acc_norm_stderr,none\": 0.03049155522040555,\n \"alias\"\ : \" - leaderboard_bbh_logical_deduction_seven_objects\"\n },\n \"leaderboard_bbh_logical_deduction_three_objects\"\ : {\n \"acc_norm,none\": 0.592,\n \"acc_norm_stderr,none\": 0.0311452098465485,\n\ \ \"alias\": \" - leaderboard_bbh_logical_deduction_three_objects\"\n \ \ },\n \"leaderboard_bbh_movie_recommendation\": {\n \"acc_norm,none\"\ : 0.672,\n \"acc_norm_stderr,none\": 0.029752391824475363,\n \"alias\"\ : \" - leaderboard_bbh_movie_recommendation\"\n },\n \"leaderboard_bbh_navigate\"\ : {\n \"acc_norm,none\": 0.64,\n \"acc_norm_stderr,none\": 0.030418764025174995,\n\ \ \"alias\": \" - leaderboard_bbh_navigate\"\n },\n \"leaderboard_bbh_object_counting\"\ : {\n \"acc_norm,none\": 0.332,\n \"acc_norm_stderr,none\": 0.0298440390474659,\n\ \ \"alias\": \" - leaderboard_bbh_object_counting\"\n },\n \"leaderboard_bbh_penguins_in_a_table\"\ : {\n \"acc_norm,none\": 0.5,\n \"acc_norm_stderr,none\": 0.041522739926869986,\n\ \ \"alias\": \" - leaderboard_bbh_penguins_in_a_table\"\n },\n \"\ leaderboard_bbh_reasoning_about_colored_objects\": {\n \"acc_norm,none\"\ : 0.444,\n \"acc_norm_stderr,none\": 0.03148684942554574,\n \"alias\"\ : \" - leaderboard_bbh_reasoning_about_colored_objects\"\n },\n \"leaderboard_bbh_ruin_names\"\ : {\n \"acc_norm,none\": 0.568,\n \"acc_norm_stderr,none\": 0.0313918107654294,\n\ \ \"alias\": \" - leaderboard_bbh_ruin_names\"\n },\n \"leaderboard_bbh_salient_translation_error_detection\"\ : {\n \"acc_norm,none\": 0.408,\n \"acc_norm_stderr,none\": 0.031145209846548505,\n\ \ \"alias\": \" - leaderboard_bbh_salient_translation_error_detection\"\n\ \ },\n \"leaderboard_bbh_snarks\": {\n \"acc_norm,none\": 0.6348314606741573,\n\ \ \"acc_norm_stderr,none\": 0.03619005678691265,\n \"alias\": \" \ \ - leaderboard_bbh_snarks\"\n },\n \"leaderboard_bbh_sports_understanding\"\ : {\n \"acc_norm,none\": 0.776,\n \"acc_norm_stderr,none\": 0.0264213616873479,\n\ \ \"alias\": \" - leaderboard_bbh_sports_understanding\"\n },\n \"\ leaderboard_bbh_temporal_sequences\": {\n \"acc_norm,none\": 0.276,\n \ \ \"acc_norm_stderr,none\": 0.02832853727421135,\n \"alias\": \" - leaderboard_bbh_temporal_sequences\"\ \n },\n \"leaderboard_bbh_tracking_shuffled_objects_five_objects\": {\n \ \ \"acc_norm,none\": 0.152,\n \"acc_norm_stderr,none\": 0.022752024491765464,\n\ \ \"alias\": \" - leaderboard_bbh_tracking_shuffled_objects_five_objects\"\ \n },\n \"leaderboard_bbh_tracking_shuffled_objects_seven_objects\": {\n \ \ \"acc_norm,none\": 0.104,\n \"acc_norm_stderr,none\": 0.01934510097484389,\n\ \ \"alias\": \" - leaderboard_bbh_tracking_shuffled_objects_seven_objects\"\ \n },\n \"leaderboard_bbh_tracking_shuffled_objects_three_objects\": {\n \ \ \"acc_norm,none\": 0.284,\n \"acc_norm_stderr,none\": 0.028576958730437408,\n\ \ \"alias\": \" - leaderboard_bbh_tracking_shuffled_objects_three_objects\"\ \n },\n \"leaderboard_bbh_web_of_lies\": {\n \"acc_norm,none\": 0.484,\n\ \ \"acc_norm_stderr,none\": 0.031669985030107414,\n \"alias\": \"\ \ - leaderboard_bbh_web_of_lies\"\n },\n \"leaderboard_gpqa\": {\n \ \ \"acc_norm,none\": 0.2843959731543625,\n \"acc_norm_stderr,none\": 0.013081070677064183,\n\ \ \"alias\": \" - leaderboard_gpqa\"\n },\n \"leaderboard_gpqa_diamond\"\ : {\n \"acc_norm,none\": 0.29292929292929293,\n \"acc_norm_stderr,none\"\ : 0.03242497958178817,\n \"alias\": \" - leaderboard_gpqa_diamond\"\n \ \ },\n \"leaderboard_gpqa_extended\": {\n \"acc_norm,none\": 0.2893772893772894,\n\ \ \"acc_norm_stderr,none\": 0.01942466387226183,\n \"alias\": \" \ \ - leaderboard_gpqa_extended\"\n },\n \"leaderboard_gpqa_main\": {\n \ \ \"acc_norm,none\": 0.27455357142857145,\n \"acc_norm_stderr,none\":\ \ 0.02110874729063386,\n \"alias\": \" - leaderboard_gpqa_main\"\n },\n\ \ \"leaderboard_ifeval\": {\n \"prompt_level_strict_acc,none\": 0.27726432532347506,\n\ \ \"prompt_level_strict_acc_stderr,none\": 0.019263706963479364,\n \ \ \"inst_level_strict_acc,none\": 0.41127098321342925,\n \"inst_level_strict_acc_stderr,none\"\ : \"N/A\",\n \"prompt_level_loose_acc,none\": 0.31053604436229204,\n \ \ \"prompt_level_loose_acc_stderr,none\": 0.019912001290591244,\n \"inst_level_loose_acc,none\"\ : 0.4364508393285372,\n \"inst_level_loose_acc_stderr,none\": \"N/A\",\n\ \ \"alias\": \" - leaderboard_ifeval\"\n },\n \"leaderboard_math_hard\"\ : {\n \"exact_match,none\": 0.11253776435045318,\n \"exact_match_stderr,none\"\ : 0.008319732099704257,\n \"alias\": \" - leaderboard_math_hard\"\n },\n\ \ \"leaderboard_math_algebra_hard\": {\n \"exact_match,none\": 0.2182410423452769,\n\ \ \"exact_match_stderr,none\": 0.02361260670412736,\n \"alias\": \"\ \ - leaderboard_math_algebra_hard\"\n },\n \"leaderboard_math_counting_and_prob_hard\"\ : {\n \"exact_match,none\": 0.06504065040650407,\n \"exact_match_stderr,none\"\ : 0.022325895462591887,\n \"alias\": \" - leaderboard_math_counting_and_prob_hard\"\ \n },\n \"leaderboard_math_geometry_hard\": {\n \"exact_match,none\"\ : 0.015151515151515152,\n \"exact_match_stderr,none\": 0.010672768637174743,\n\ \ \"alias\": \" - leaderboard_math_geometry_hard\"\n },\n \"leaderboard_math_intermediate_algebra_hard\"\ : {\n \"exact_match,none\": 0.03214285714285714,\n \"exact_match_stderr,none\"\ : 0.010559558661753189,\n \"alias\": \" - leaderboard_math_intermediate_algebra_hard\"\ \n },\n \"leaderboard_math_num_theory_hard\": {\n \"exact_match,none\"\ : 0.07142857142857142,\n \"exact_match_stderr,none\": 0.020820824576076362,\n\ \ \"alias\": \" - leaderboard_math_num_theory_hard\"\n },\n \"leaderboard_math_prealgebra_hard\"\ : {\n \"exact_match,none\": 0.24870466321243523,\n \"exact_match_stderr,none\"\ : 0.03119584087770031,\n \"alias\": \" - leaderboard_math_prealgebra_hard\"\ \n },\n \"leaderboard_math_precalculus_hard\": {\n \"exact_match,none\"\ : 0.02962962962962963,\n \"exact_match_stderr,none\": 0.014648038602753778,\n\ \ \"alias\": \" - leaderboard_math_precalculus_hard\"\n },\n \"leaderboard_mmlu_pro\"\ : {\n \"acc,none\": 0.3731715425531915,\n \"acc_stderr,none\": 0.004409382233559137,\n\ \ \"alias\": \" - leaderboard_mmlu_pro\"\n },\n \"leaderboard_musr\"\ : {\n \"acc_norm,none\": 0.4576719576719577,\n \"acc_norm_stderr,none\"\ : 0.01788578586514914,\n \"alias\": \" - leaderboard_musr\"\n },\n \ \ \"leaderboard_musr_murder_mysteries\": {\n \"acc_norm,none\": 0.536,\n\ \ \"acc_norm_stderr,none\": 0.031603975145223735,\n \"alias\": \"\ \ - leaderboard_musr_murder_mysteries\"\n },\n \"leaderboard_musr_object_placements\"\ : {\n \"acc_norm,none\": 0.33984375,\n \"acc_norm_stderr,none\": 0.029661487249077814,\n\ \ \"alias\": \" - leaderboard_musr_object_placements\"\n },\n \"leaderboard_musr_team_allocation\"\ : {\n \"acc_norm,none\": 0.5,\n \"acc_norm_stderr,none\": 0.031686212526223896,\n\ \ \"alias\": \" - leaderboard_musr_team_allocation\"\n }\n}\n```" repo_url: https://huggingface.co/MaziyarPanahi/calme-2.6-qwen2-7b leaderboard_url: '' point_of_contact: '' configs: - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_boolean_expressions data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_boolean_expressions_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_boolean_expressions_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_causal_judgement data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_causal_judgement_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_causal_judgement_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_date_understanding data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_date_understanding_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_date_understanding_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_disambiguation_qa data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_disambiguation_qa_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_disambiguation_qa_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_formal_fallacies data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_formal_fallacies_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_formal_fallacies_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_geometric_shapes data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_geometric_shapes_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_geometric_shapes_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_hyperbaton data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_hyperbaton_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_hyperbaton_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_logical_deduction_five_objects data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_logical_deduction_five_objects_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_logical_deduction_five_objects_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_logical_deduction_seven_objects data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_logical_deduction_seven_objects_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_logical_deduction_seven_objects_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_logical_deduction_three_objects data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_logical_deduction_three_objects_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_logical_deduction_three_objects_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_movie_recommendation data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_movie_recommendation_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_movie_recommendation_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_navigate data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_navigate_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_navigate_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_object_counting data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_object_counting_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_object_counting_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_penguins_in_a_table data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_penguins_in_a_table_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_penguins_in_a_table_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_reasoning_about_colored_objects data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_reasoning_about_colored_objects_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_reasoning_about_colored_objects_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_ruin_names data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_ruin_names_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_ruin_names_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_salient_translation_error_detection data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_salient_translation_error_detection_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_salient_translation_error_detection_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_snarks data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_snarks_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_snarks_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_sports_understanding data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_sports_understanding_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_sports_understanding_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_temporal_sequences data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_temporal_sequences_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_temporal_sequences_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_tracking_shuffled_objects_five_objects data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_tracking_shuffled_objects_five_objects_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_tracking_shuffled_objects_five_objects_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_tracking_shuffled_objects_seven_objects data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_tracking_shuffled_objects_seven_objects_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_tracking_shuffled_objects_seven_objects_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_tracking_shuffled_objects_three_objects data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_tracking_shuffled_objects_three_objects_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_tracking_shuffled_objects_three_objects_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_web_of_lies data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_bbh_web_of_lies_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_web_of_lies_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_gpqa_diamond data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_gpqa_diamond_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_gpqa_diamond_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_gpqa_extended data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_gpqa_extended_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_gpqa_extended_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_gpqa_main data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_gpqa_main_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_gpqa_main_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_ifeval data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_ifeval_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_ifeval_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_math_algebra_hard data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_math_algebra_hard_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_math_algebra_hard_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_math_counting_and_prob_hard data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_math_counting_and_prob_hard_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_math_counting_and_prob_hard_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_math_geometry_hard data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_math_geometry_hard_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_math_geometry_hard_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_math_intermediate_algebra_hard data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_math_intermediate_algebra_hard_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_math_intermediate_algebra_hard_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_math_num_theory_hard data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_math_num_theory_hard_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_math_num_theory_hard_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_math_prealgebra_hard data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_math_prealgebra_hard_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_math_prealgebra_hard_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_math_precalculus_hard data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_math_precalculus_hard_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_math_precalculus_hard_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_mmlu_pro data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_mmlu_pro_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_mmlu_pro_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_musr_murder_mysteries data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_musr_murder_mysteries_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_musr_murder_mysteries_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_musr_object_placements data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_musr_object_placements_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_musr_object_placements_2024-09-29T23-22-32.652583.jsonl' - config_name: MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_musr_team_allocation data_files: - split: 2024_09_29T23_22_32.652583 path: - '**/samples_leaderboard_musr_team_allocation_2024-09-29T23-22-32.652583.jsonl' - split: latest path: - '**/samples_leaderboard_musr_team_allocation_2024-09-29T23-22-32.652583.jsonl' --- # Dataset Card for Evaluation run of MaziyarPanahi/calme-2.6-qwen2-7b <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [MaziyarPanahi/calme-2.6-qwen2-7b](https://huggingface.co/MaziyarPanahi/calme-2.6-qwen2-7b) The dataset is composed of 38 configuration(s), each one corresponding 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. 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/MaziyarPanahi__calme-2.6-qwen2-7b-details", name="MaziyarPanahi__calme-2.6-qwen2-7b__leaderboard_bbh_boolean_expressions", split="latest" ) ``` ## Latest results These are the [latest results from run 2024-09-29T23-22-32.652583](https://huggingface.co/datasets/open-llm-leaderboard/MaziyarPanahi__calme-2.6-qwen2-7b-details/blob/main/MaziyarPanahi__calme-2.6-qwen2-7b/results_2024-09-29T23-22-32.652583.json) (note that there 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": { "leaderboard": { "inst_level_loose_acc,none": 0.4364508393285372, "inst_level_loose_acc_stderr,none": "N/A", "inst_level_strict_acc,none": 0.41127098321342925, "inst_level_strict_acc_stderr,none": "N/A", "prompt_level_loose_acc,none": 0.31053604436229204, "prompt_level_loose_acc_stderr,none": 0.019912001290591244, "acc_norm,none": 0.45453366195356076, "acc_norm_stderr,none": 0.0053168263981244425, "prompt_level_strict_acc,none": 0.27726432532347506, "prompt_level_strict_acc_stderr,none": 0.019263706963479364, "acc,none": 0.3731715425531915, "acc_stderr,none": 0.004409382233559137, "exact_match,none": 0.11253776435045318, "exact_match_stderr,none": 0.008319732099704257, "alias": "leaderboard" }, "leaderboard_bbh": { "acc_norm,none": 0.4893247700052074, "acc_norm_stderr,none": 0.006146856128835226, "alias": " - leaderboard_bbh" }, "leaderboard_bbh_boolean_expressions": { "acc_norm,none": 0.832, "acc_norm_stderr,none": 0.0236928132054926, "alias": " - leaderboard_bbh_boolean_expressions" }, "leaderboard_bbh_causal_judgement": { "acc_norm,none": 0.6577540106951871, "acc_norm_stderr,none": 0.034789201769068225, "alias": " - leaderboard_bbh_causal_judgement" }, "leaderboard_bbh_date_understanding": { "acc_norm,none": 0.416, "acc_norm_stderr,none": 0.031235856237014574, "alias": " - leaderboard_bbh_date_understanding" }, "leaderboard_bbh_disambiguation_qa": { "acc_norm,none": 0.588, "acc_norm_stderr,none": 0.031191596026022894, "alias": " - leaderboard_bbh_disambiguation_qa" }, "leaderboard_bbh_formal_fallacies": { "acc_norm,none": 0.568, "acc_norm_stderr,none": 0.031391810765429407, "alias": " - leaderboard_bbh_formal_fallacies" }, "leaderboard_bbh_geometric_shapes": { "acc_norm,none": 0.472, "acc_norm_stderr,none": 0.0316364895315444, "alias": " - leaderboard_bbh_geometric_shapes" }, "leaderboard_bbh_hyperbaton": { "acc_norm,none": 0.656, "acc_norm_stderr,none": 0.030104503392316385, "alias": " - leaderboard_bbh_hyperbaton" }, "leaderboard_bbh_logical_deduction_five_objects": { "acc_norm,none": 0.412, "acc_norm_stderr,none": 0.031191596026022898, "alias": " - leaderboard_bbh_logical_deduction_five_objects" }, "leaderboard_bbh_logical_deduction_seven_objects": { "acc_norm,none": 0.364, "acc_norm_stderr,none": 0.03049155522040555, "alias": " - leaderboard_bbh_logical_deduction_seven_objects" }, "leaderboard_bbh_logical_deduction_three_objects": { "acc_norm,none": 0.592, "acc_norm_stderr,none": 0.0311452098465485, "alias": " - leaderboard_bbh_logical_deduction_three_objects" }, "leaderboard_bbh_movie_recommendation": { "acc_norm,none": 0.672, "acc_norm_stderr,none": 0.029752391824475363, "alias": " - leaderboard_bbh_movie_recommendation" }, "leaderboard_bbh_navigate": { "acc_norm,none": 0.64, "acc_norm_stderr,none": 0.030418764025174995, "alias": " - leaderboard_bbh_navigate" }, "leaderboard_bbh_object_counting": { "acc_norm,none": 0.332, "acc_norm_stderr,none": 0.0298440390474659, "alias": " - leaderboard_bbh_object_counting" }, "leaderboard_bbh_penguins_in_a_table": { "acc_norm,none": 0.5, "acc_norm_stderr,none": 0.041522739926869986, "alias": " - leaderboard_bbh_penguins_in_a_table" }, "leaderboard_bbh_reasoning_about_colored_objects": { "acc_norm,none": 0.444, "acc_norm_stderr,none": 0.03148684942554574, "alias": " - leaderboard_bbh_reasoning_about_colored_objects" }, "leaderboard_bbh_ruin_names": { "acc_norm,none": 0.568, "acc_norm_stderr,none": 0.0313918107654294, "alias": " - leaderboard_bbh_ruin_names" }, "leaderboard_bbh_salient_translation_error_detection": { "acc_norm,none": 0.408, "acc_norm_stderr,none": 0.031145209846548505, "alias": " - leaderboard_bbh_salient_translation_error_detection" }, "leaderboard_bbh_snarks": { "acc_norm,none": 0.6348314606741573, "acc_norm_stderr,none": 0.03619005678691265, "alias": " - leaderboard_bbh_snarks" }, "leaderboard_bbh_sports_understanding": { "acc_norm,none": 0.776, "acc_norm_stderr,none": 0.0264213616873479, "alias": " - leaderboard_bbh_sports_understanding" }, "leaderboard_bbh_temporal_sequences": { "acc_norm,none": 0.276, "acc_norm_stderr,none": 0.02832853727421135, "alias": " - leaderboard_bbh_temporal_sequences" }, "leaderboard_bbh_tracking_shuffled_objects_five_objects": { "acc_norm,none": 0.152, "acc_norm_stderr,none": 0.022752024491765464, "alias": " - leaderboard_bbh_tracking_shuffled_objects_five_objects" }, "leaderboard_bbh_tracking_shuffled_objects_seven_objects": { "acc_norm,none": 0.104, "acc_norm_stderr,none": 0.01934510097484389, "alias": " - leaderboard_bbh_tracking_shuffled_objects_seven_objects" }, "leaderboard_bbh_tracking_shuffled_objects_three_objects": { "acc_norm,none": 0.284, "acc_norm_stderr,none": 0.028576958730437408, "alias": " - leaderboard_bbh_tracking_shuffled_objects_three_objects" }, "leaderboard_bbh_web_of_lies": { "acc_norm,none": 0.484, "acc_norm_stderr,none": 0.031669985030107414, "alias": " - leaderboard_bbh_web_of_lies" }, "leaderboard_gpqa": { "acc_norm,none": 0.2843959731543625, "acc_norm_stderr,none": 0.013081070677064183, "alias": " - leaderboard_gpqa" }, "leaderboard_gpqa_diamond": { "acc_norm,none": 0.29292929292929293, "acc_norm_stderr,none": 0.03242497958178817, "alias": " - leaderboard_gpqa_diamond" }, "leaderboard_gpqa_extended": { "acc_norm,none": 0.2893772893772894, "acc_norm_stderr,none": 0.01942466387226183, "alias": " - leaderboard_gpqa_extended" }, "leaderboard_gpqa_main": { "acc_norm,none": 0.27455357142857145, "acc_norm_stderr,none": 0.02110874729063386, "alias": " - leaderboard_gpqa_main" }, "leaderboard_ifeval": { "prompt_level_strict_acc,none": 0.27726432532347506, "prompt_level_strict_acc_stderr,none": 0.019263706963479364, "inst_level_strict_acc,none": 0.41127098321342925, "inst_level_strict_acc_stderr,none": "N/A", "prompt_level_loose_acc,none": 0.31053604436229204, "prompt_level_loose_acc_stderr,none": 0.019912001290591244, "inst_level_loose_acc,none": 0.4364508393285372, "inst_level_loose_acc_stderr,none": "N/A", "alias": " - leaderboard_ifeval" }, "leaderboard_math_hard": { "exact_match,none": 0.11253776435045318, "exact_match_stderr,none": 0.008319732099704257, "alias": " - leaderboard_math_hard" }, "leaderboard_math_algebra_hard": { "exact_match,none": 0.2182410423452769, "exact_match_stderr,none": 0.02361260670412736, "alias": " - leaderboard_math_algebra_hard" }, "leaderboard_math_counting_and_prob_hard": { "exact_match,none": 0.06504065040650407, "exact_match_stderr,none": 0.022325895462591887, "alias": " - leaderboard_math_counting_and_prob_hard" }, "leaderboard_math_geometry_hard": { "exact_match,none": 0.015151515151515152, "exact_match_stderr,none": 0.010672768637174743, "alias": " - leaderboard_math_geometry_hard" }, "leaderboard_math_intermediate_algebra_hard": { "exact_match,none": 0.03214285714285714, "exact_match_stderr,none": 0.010559558661753189, "alias": " - leaderboard_math_intermediate_algebra_hard" }, "leaderboard_math_num_theory_hard": { "exact_match,none": 0.07142857142857142, "exact_match_stderr,none": 0.020820824576076362, "alias": " - leaderboard_math_num_theory_hard" }, "leaderboard_math_prealgebra_hard": { "exact_match,none": 0.24870466321243523, "exact_match_stderr,none": 0.03119584087770031, "alias": " - leaderboard_math_prealgebra_hard" }, "leaderboard_math_precalculus_hard": { "exact_match,none": 0.02962962962962963, "exact_match_stderr,none": 0.014648038602753778, "alias": " - leaderboard_math_precalculus_hard" }, "leaderboard_mmlu_pro": { "acc,none": 0.3731715425531915, "acc_stderr,none": 0.004409382233559137, "alias": " - leaderboard_mmlu_pro" }, "leaderboard_musr": { "acc_norm,none": 0.4576719576719577, "acc_norm_stderr,none": 0.01788578586514914, "alias": " - leaderboard_musr" }, "leaderboard_musr_murder_mysteries": { "acc_norm,none": 0.536, "acc_norm_stderr,none": 0.031603975145223735, "alias": " - leaderboard_musr_murder_mysteries" }, "leaderboard_musr_object_placements": { "acc_norm,none": 0.33984375, "acc_norm_stderr,none": 0.029661487249077814, "alias": " - leaderboard_musr_object_placements" }, "leaderboard_musr_team_allocation": { "acc_norm,none": 0.5, "acc_norm_stderr,none": 0.031686212526223896, "alias": " - leaderboard_musr_team_allocation" } }, "leaderboard": { "inst_level_loose_acc,none": 0.4364508393285372, "inst_level_loose_acc_stderr,none": "N/A", "inst_level_strict_acc,none": 0.41127098321342925, "inst_level_strict_acc_stderr,none": "N/A", "prompt_level_loose_acc,none": 0.31053604436229204, "prompt_level_loose_acc_stderr,none": 0.019912001290591244, "acc_norm,none": 0.45453366195356076, "acc_norm_stderr,none": 0.0053168263981244425, "prompt_level_strict_acc,none": 0.27726432532347506, "prompt_level_strict_acc_stderr,none": 0.019263706963479364, "acc,none": 0.3731715425531915, "acc_stderr,none": 0.004409382233559137, "exact_match,none": 0.11253776435045318, "exact_match_stderr,none": 0.008319732099704257, "alias": "leaderboard" }, "leaderboard_bbh": { "acc_norm,none": 0.4893247700052074, "acc_norm_stderr,none": 0.006146856128835226, "alias": " - leaderboard_bbh" }, "leaderboard_bbh_boolean_expressions": { "acc_norm,none": 0.832, "acc_norm_stderr,none": 0.0236928132054926, "alias": " - leaderboard_bbh_boolean_expressions" }, "leaderboard_bbh_causal_judgement": { "acc_norm,none": 0.6577540106951871, "acc_norm_stderr,none": 0.034789201769068225, "alias": " - leaderboard_bbh_causal_judgement" }, "leaderboard_bbh_date_understanding": { "acc_norm,none": 0.416, "acc_norm_stderr,none": 0.031235856237014574, "alias": " - leaderboard_bbh_date_understanding" }, "leaderboard_bbh_disambiguation_qa": { "acc_norm,none": 0.588, "acc_norm_stderr,none": 0.031191596026022894, "alias": " - leaderboard_bbh_disambiguation_qa" }, "leaderboard_bbh_formal_fallacies": { "acc_norm,none": 0.568, "acc_norm_stderr,none": 0.031391810765429407, "alias": " - leaderboard_bbh_formal_fallacies" }, "leaderboard_bbh_geometric_shapes": { "acc_norm,none": 0.472, "acc_norm_stderr,none": 0.0316364895315444, "alias": " - leaderboard_bbh_geometric_shapes" }, "leaderboard_bbh_hyperbaton": { "acc_norm,none": 0.656, "acc_norm_stderr,none": 0.030104503392316385, "alias": " - leaderboard_bbh_hyperbaton" }, "leaderboard_bbh_logical_deduction_five_objects": { "acc_norm,none": 0.412, "acc_norm_stderr,none": 0.031191596026022898, "alias": " - leaderboard_bbh_logical_deduction_five_objects" }, "leaderboard_bbh_logical_deduction_seven_objects": { "acc_norm,none": 0.364, "acc_norm_stderr,none": 0.03049155522040555, "alias": " - leaderboard_bbh_logical_deduction_seven_objects" }, "leaderboard_bbh_logical_deduction_three_objects": { "acc_norm,none": 0.592, "acc_norm_stderr,none": 0.0311452098465485, "alias": " - leaderboard_bbh_logical_deduction_three_objects" }, "leaderboard_bbh_movie_recommendation": { "acc_norm,none": 0.672, "acc_norm_stderr,none": 0.029752391824475363, "alias": " - leaderboard_bbh_movie_recommendation" }, "leaderboard_bbh_navigate": { "acc_norm,none": 0.64, "acc_norm_stderr,none": 0.030418764025174995, "alias": " - leaderboard_bbh_navigate" }, "leaderboard_bbh_object_counting": { "acc_norm,none": 0.332, "acc_norm_stderr,none": 0.0298440390474659, "alias": " - leaderboard_bbh_object_counting" }, "leaderboard_bbh_penguins_in_a_table": { "acc_norm,none": 0.5, "acc_norm_stderr,none": 0.041522739926869986, "alias": " - leaderboard_bbh_penguins_in_a_table" }, "leaderboard_bbh_reasoning_about_colored_objects": { "acc_norm,none": 0.444, "acc_norm_stderr,none": 0.03148684942554574, "alias": " - leaderboard_bbh_reasoning_about_colored_objects" }, "leaderboard_bbh_ruin_names": { "acc_norm,none": 0.568, "acc_norm_stderr,none": 0.0313918107654294, "alias": " - leaderboard_bbh_ruin_names" }, "leaderboard_bbh_salient_translation_error_detection": { "acc_norm,none": 0.408, "acc_norm_stderr,none": 0.031145209846548505, "alias": " - leaderboard_bbh_salient_translation_error_detection" }, "leaderboard_bbh_snarks": { "acc_norm,none": 0.6348314606741573, "acc_norm_stderr,none": 0.03619005678691265, "alias": " - leaderboard_bbh_snarks" }, "leaderboard_bbh_sports_understanding": { "acc_norm,none": 0.776, "acc_norm_stderr,none": 0.0264213616873479, "alias": " - leaderboard_bbh_sports_understanding" }, "leaderboard_bbh_temporal_sequences": { "acc_norm,none": 0.276, "acc_norm_stderr,none": 0.02832853727421135, "alias": " - leaderboard_bbh_temporal_sequences" }, "leaderboard_bbh_tracking_shuffled_objects_five_objects": { "acc_norm,none": 0.152, "acc_norm_stderr,none": 0.022752024491765464, "alias": " - leaderboard_bbh_tracking_shuffled_objects_five_objects" }, "leaderboard_bbh_tracking_shuffled_objects_seven_objects": { "acc_norm,none": 0.104, "acc_norm_stderr,none": 0.01934510097484389, "alias": " - leaderboard_bbh_tracking_shuffled_objects_seven_objects" }, "leaderboard_bbh_tracking_shuffled_objects_three_objects": { "acc_norm,none": 0.284, "acc_norm_stderr,none": 0.028576958730437408, "alias": " - leaderboard_bbh_tracking_shuffled_objects_three_objects" }, "leaderboard_bbh_web_of_lies": { "acc_norm,none": 0.484, "acc_norm_stderr,none": 0.031669985030107414, "alias": " - leaderboard_bbh_web_of_lies" }, "leaderboard_gpqa": { "acc_norm,none": 0.2843959731543625, "acc_norm_stderr,none": 0.013081070677064183, "alias": " - leaderboard_gpqa" }, "leaderboard_gpqa_diamond": { "acc_norm,none": 0.29292929292929293, "acc_norm_stderr,none": 0.03242497958178817, "alias": " - leaderboard_gpqa_diamond" }, "leaderboard_gpqa_extended": { "acc_norm,none": 0.2893772893772894, "acc_norm_stderr,none": 0.01942466387226183, "alias": " - leaderboard_gpqa_extended" }, "leaderboard_gpqa_main": { "acc_norm,none": 0.27455357142857145, "acc_norm_stderr,none": 0.02110874729063386, "alias": " - leaderboard_gpqa_main" }, "leaderboard_ifeval": { "prompt_level_strict_acc,none": 0.27726432532347506, "prompt_level_strict_acc_stderr,none": 0.019263706963479364, "inst_level_strict_acc,none": 0.41127098321342925, "inst_level_strict_acc_stderr,none": "N/A", "prompt_level_loose_acc,none": 0.31053604436229204, "prompt_level_loose_acc_stderr,none": 0.019912001290591244, "inst_level_loose_acc,none": 0.4364508393285372, "inst_level_loose_acc_stderr,none": "N/A", "alias": " - leaderboard_ifeval" }, "leaderboard_math_hard": { "exact_match,none": 0.11253776435045318, "exact_match_stderr,none": 0.008319732099704257, "alias": " - leaderboard_math_hard" }, "leaderboard_math_algebra_hard": { "exact_match,none": 0.2182410423452769, "exact_match_stderr,none": 0.02361260670412736, "alias": " - leaderboard_math_algebra_hard" }, "leaderboard_math_counting_and_prob_hard": { "exact_match,none": 0.06504065040650407, "exact_match_stderr,none": 0.022325895462591887, "alias": " - leaderboard_math_counting_and_prob_hard" }, "leaderboard_math_geometry_hard": { "exact_match,none": 0.015151515151515152, "exact_match_stderr,none": 0.010672768637174743, "alias": " - leaderboard_math_geometry_hard" }, "leaderboard_math_intermediate_algebra_hard": { "exact_match,none": 0.03214285714285714, "exact_match_stderr,none": 0.010559558661753189, "alias": " - leaderboard_math_intermediate_algebra_hard" }, "leaderboard_math_num_theory_hard": { "exact_match,none": 0.07142857142857142, "exact_match_stderr,none": 0.020820824576076362, "alias": " - leaderboard_math_num_theory_hard" }, "leaderboard_math_prealgebra_hard": { "exact_match,none": 0.24870466321243523, "exact_match_stderr,none": 0.03119584087770031, "alias": " - leaderboard_math_prealgebra_hard" }, "leaderboard_math_precalculus_hard": { "exact_match,none": 0.02962962962962963, "exact_match_stderr,none": 0.014648038602753778, "alias": " - leaderboard_math_precalculus_hard" }, "leaderboard_mmlu_pro": { "acc,none": 0.3731715425531915, "acc_stderr,none": 0.004409382233559137, "alias": " - leaderboard_mmlu_pro" }, "leaderboard_musr": { "acc_norm,none": 0.4576719576719577, "acc_norm_stderr,none": 0.01788578586514914, "alias": " - leaderboard_musr" }, "leaderboard_musr_murder_mysteries": { "acc_norm,none": 0.536, "acc_norm_stderr,none": 0.031603975145223735, "alias": " - leaderboard_musr_murder_mysteries" }, "leaderboard_musr_object_placements": { "acc_norm,none": 0.33984375, "acc_norm_stderr,none": 0.029661487249077814, "alias": " - leaderboard_musr_object_placements" }, "leaderboard_musr_team_allocation": { "acc_norm,none": 0.5, "acc_norm_stderr,none": 0.031686212526223896, "alias": " - leaderboard_musr_team_allocation" } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. 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AlienKevin/BabyLM_2024_10M

AlienKevin

--- dataset_info: features: - name: text dtype: string - name: origin dtype: string splits: - name: train num_bytes: 74111623 num_examples: 1179014 - name: dev num_bytes: 76563925 num_examples: 1168153 - name: test num_bytes: 70379531 num_examples: 1110083 download_size: 101465918 dataset_size: 221055079 configs: - config_name: default data_files: - split: train path: data/train-* - split: dev path: data/dev-* - split: test path: data/test-* ---

fanyin3639/BingoGuardTrain-wo-severity

fanyin3639

--- dataset_info: features: - name: prompt dtype: string - name: response dtype: string - name: label dtype: string - name: prompt_label dtype: string splits: - name: train num_bytes: 53416876.0 num_examples: 53826 download_size: 30272516 dataset_size: 53416876.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

pbevan11/aya_redteaming_mcai_eval

pbevan11

--- dataset_info: features: - name: prompt dtype: string - name: language dtype: string - name: harm_category dtype: string - name: global_or_local dtype: string - name: literal_translation dtype: 'null' - name: semantic_translation dtype: 'null' - name: explanation dtype: string - name: source_language dtype: string - name: all_critiques_eng sequence: string - name: all_revisions_eng sequence: string - name: all_critiques_translated dtype: 'null' - name: all_revisions_translated dtype: 'null' - name: MCAI_SFT_response dtype: string - name: MCAI_SFT_harmlessness dtype: string - name: MCAI_SFT_harmlessness_explanation dtype: string - name: MCAI_SFT_DPO_response dtype: string - name: MCAI_SFT_DPO_harmlessness dtype: string - name: MCAI_SFT_DPO_harmlessness_explanation dtype: string - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 37657 num_examples: 5 download_size: 34240 dataset_size: 37657 configs: - config_name: default data_files: - split: train path: data/train-* ---

12kimih/cupid-preview-zero

12kimih

--- dataset_info: - config_name: GPT-4o-mini features: - name: user_id dtype: int64 - name: dialogue_id sequence: int64 - name: question_id dtype: int64 - name: n_hop dtype: int64 - name: question dtype: string - name: personalized_answer dtype: string - name: general_answer dtype: string - name: model_answer dtype: string - name: metadata list: - name: category dtype: string - name: entity dtype: string - name: sentiment dtype: string - name: verb dtype: string splits: - name: test num_bytes: 2365537 num_examples: 2500 download_size: 1376204 dataset_size: 2365537 - config_name: Llama-3.1-8B-Instruct features: - name: user_id dtype: int64 - name: dialogue_id sequence: int64 - name: question_id dtype: int64 - name: n_hop dtype: int64 - name: question dtype: string - name: personalized_answer dtype: string - name: general_answer dtype: string - name: model_answer dtype: string - name: metadata list: - name: category dtype: string - name: entity dtype: string - name: sentiment dtype: string - name: verb dtype: string splits: - name: test num_bytes: 2336000 num_examples: 2500 download_size: 1322279 dataset_size: 2336000 - config_name: Mistral-7B-Instruct-v0.3 features: - name: user_id dtype: int64 - name: dialogue_id sequence: int64 - name: question_id dtype: int64 - name: n_hop dtype: int64 - name: question dtype: string - name: personalized_answer dtype: string - name: general_answer dtype: string - name: model_answer dtype: string - name: metadata list: - name: category dtype: string - name: entity dtype: string - name: sentiment dtype: string - name: verb dtype: string splits: - name: test num_bytes: 1840549 num_examples: 2500 download_size: 1065613 dataset_size: 1840549 - config_name: Phi-3.5-mini-instruct features: - name: user_id dtype: int64 - name: dialogue_id sequence: int64 - name: question_id dtype: int64 - name: n_hop dtype: int64 - name: question dtype: string - name: personalized_answer dtype: string - name: general_answer dtype: string - name: model_answer dtype: string - name: metadata list: - name: category dtype: string - name: entity dtype: string - name: sentiment dtype: string - name: verb dtype: string splits: - name: test num_bytes: 2494011 num_examples: 2500 download_size: 1434436 dataset_size: 2494011 - config_name: Qwen2.5-7B-Instruct features: - name: user_id dtype: int64 - name: dialogue_id sequence: int64 - name: question_id dtype: int64 - name: n_hop dtype: int64 - name: question dtype: string - name: personalized_answer dtype: string - name: general_answer dtype: string - name: model_answer dtype: string - name: metadata list: - name: category dtype: string - name: entity dtype: string - name: sentiment dtype: string - name: verb dtype: string splits: - name: test num_bytes: 1812651 num_examples: 2500 download_size: 1055050 dataset_size: 1812651 configs: - config_name: GPT-4o-mini data_files: - split: test path: GPT-4o-mini/test-* - config_name: Llama-3.1-8B-Instruct data_files: - split: test path: Llama-3.1-8B-Instruct/test-* - config_name: Mistral-7B-Instruct-v0.3 data_files: - split: test path: Mistral-7B-Instruct-v0.3/test-* - config_name: Phi-3.5-mini-instruct data_files: - split: test path: Phi-3.5-mini-instruct/test-* - config_name: Qwen2.5-7B-Instruct data_files: - split: test path: Qwen2.5-7B-Instruct/test-* ---

12kimih/cupid-preview-few

12kimih

--- dataset_info: - config_name: GPT-4o-mini features: - name: user_id dtype: int64 - name: dialogue_id sequence: int64 - name: question_id dtype: int64 - name: n_hop dtype: int64 - name: question dtype: string - name: personalized_answer dtype: string - name: general_answer dtype: string - name: model_answer dtype: string - name: metadata list: - name: category dtype: string - name: entity dtype: string - name: sentiment dtype: string - name: verb dtype: string splits: - name: test num_bytes: 2396173 num_examples: 2500 download_size: 1370321 dataset_size: 2396173 - config_name: Llama-3.1-8B-Instruct features: - name: user_id dtype: int64 - name: dialogue_id sequence: int64 - name: question_id dtype: int64 - name: n_hop dtype: int64 - name: question dtype: string - name: personalized_answer dtype: string - name: general_answer dtype: string - name: model_answer dtype: string - name: metadata list: - name: category dtype: string - name: entity dtype: string - name: sentiment dtype: string - name: verb dtype: string splits: - name: test num_bytes: 2562067 num_examples: 2500 download_size: 1420181 dataset_size: 2562067 - config_name: Mistral-7B-Instruct-v0.3 features: - name: user_id dtype: int64 - name: dialogue_id sequence: int64 - name: question_id dtype: int64 - name: n_hop dtype: int64 - name: question dtype: string - name: personalized_answer dtype: string - name: general_answer dtype: string - name: model_answer dtype: string - name: metadata list: - name: category dtype: string - name: entity dtype: string - name: sentiment dtype: string - name: verb dtype: string splits: - name: test num_bytes: 2030802 num_examples: 2500 download_size: 1180561 dataset_size: 2030802 - config_name: Qwen2.5-7B-Instruct features: - name: user_id dtype: int64 - name: dialogue_id sequence: int64 - name: question_id dtype: int64 - name: n_hop dtype: int64 - name: question dtype: string - name: personalized_answer dtype: string - name: general_answer dtype: string - name: model_answer dtype: string - name: metadata list: - name: category dtype: string - name: entity dtype: string - name: sentiment dtype: string - name: verb dtype: string splits: - name: test num_bytes: 2012422 num_examples: 2500 download_size: 1166424 dataset_size: 2012422 configs: - config_name: GPT-4o-mini data_files: - split: test path: GPT-4o-mini/test-* - config_name: Llama-3.1-8B-Instruct data_files: - split: test path: Llama-3.1-8B-Instruct/test-* - config_name: Mistral-7B-Instruct-v0.3 data_files: - split: test path: Mistral-7B-Instruct-v0.3/test-* - config_name: Qwen2.5-7B-Instruct data_files: - split: test path: Qwen2.5-7B-Instruct/test-* ---

amuvarma/6-layer-crossmodal-750k-llama-tts-ablate-content_0

amuvarma

--- dataset_info: features: - name: transcript dtype: string - name: facodec_0 sequence: int64 - name: facodec_1 sequence: int64 - name: facodec_2 sequence: int64 - name: facodec_3 sequence: int64 - name: facodec_4 sequence: int64 - name: facodec_5 sequence: int64 - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels sequence: int64 splits: - name: train num_bytes: 120187793366 num_examples: 748000 download_size: 17855787111 dataset_size: 120187793366 configs: - config_name: default data_files: - split: train path: data/train-* ---

RichardTg/meta-learn

RichardTg

--- license: mit ---

maniro-ai/2024-09-29-container-slope-lift-berry

maniro-ai

--- dataset_info: features: - name: observation.state sequence: float32 length: 8 - name: action sequence: float32 length: 8 - name: episode_index dtype: int64 - name: frame_index dtype: int64 - name: timestamp dtype: float32 - name: observation.images.cameras.raw.wrist_1 dtype: video_frame - name: observation.images.cameras.raw.wrist_2 dtype: video_frame - name: observation.images.cameras.raw.scene_table dtype: video_frame - name: index dtype: int64 splits: - name: train num_bytes: 5318040 num_examples: 17045 download_size: 1568973 dataset_size: 5318040 configs: - config_name: default data_files: - split: train path: data/train-* ---

netranga/state_of_ai_standford_colpali

netranga

--- dataset_info: features: - name: image dtype: image - name: labels dtype: string - name: queries dtype: string splits: - name: train num_bytes: 35315615.0 num_examples: 502 download_size: 34210458 dataset_size: 35315615.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

spicelion1802/riadd_dataset

spicelion1802

--- dataset_info: features: - name: image dtype: image - name: disease_annotations struct: - name: DR dtype: string - name: ARMD dtype: string - name: MH dtype: string - name: DN dtype: string - name: MYA dtype: string - name: BRVO dtype: string - name: TSLN dtype: string - name: ERM dtype: string - name: LS dtype: string - name: MS dtype: string - name: CSR dtype: string - name: ODC dtype: string - name: CRVO dtype: string - name: TV dtype: string - name: AH dtype: string - name: ODP dtype: string - name: ODE dtype: string - name: ST dtype: string - name: AION dtype: string - name: PT dtype: string - name: RT dtype: string - name: RS dtype: string - name: CRS dtype: string - name: EDN dtype: string - name: RPEC dtype: string - name: MHL dtype: string - name: RP dtype: string - name: CWS dtype: string - name: CB dtype: string - name: ODPM dtype: string - name: PRH dtype: string - name: MNF dtype: string - name: HR dtype: string - name: CRAO dtype: string - name: TD dtype: string - name: CME dtype: string - name: PTCR dtype: string - name: CF dtype: string - name: VH dtype: string - name: MCA dtype: string - name: VS dtype: string - name: BRAO dtype: string - name: PLQ dtype: string - name: HPED dtype: string - name: CL dtype: string splits: - name: train num_bytes: 2550547547.56 num_examples: 1920 download_size: 2676221815 dataset_size: 2550547547.56 configs: - config_name: default data_files: - split: train path: data/train-* ---

jlbaker361/ahri14_2_ddpo

jlbaker361

--- dataset_info: features: - name: index dtype: int64 - name: image dtype: image splits: - name: train num_bytes: 6290502.0 num_examples: 15 download_size: 6292270 dataset_size: 6290502.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

ycfNTU/masum_nozeroshot_loop_mistral

ycfNTU

--- dataset_info: features: - name: document dtype: string - name: aspect dtype: string - name: summary dtype: string - name: top_sentences_words1 dtype: string - name: summary1 dtype: string splits: - name: train num_bytes: 26133276 num_examples: 2000 download_size: 14534130 dataset_size: 26133276 configs: - config_name: default data_files: - split: train path: data/train-* ---

1-800-SHARED-TASKS/Sujet-Vision-QA

1-800-SHARED-TASKS

--- license: apache-2.0 task_categories: - question-answering language: - en tags: - finance - question answer - dataset - qa - vision - visual qa - financial documents - VLM - Llava - Florence - PaliGemma pretty_name: SujetAI's Financial QA Vision Dataset size_categories: - 100K<n<1M --- ## Dataset Description 📊🔍 The Sujet-Finance-QA-Vision-100k is a comprehensive dataset containing over 100,000 question-answer pairs derived from more than 9,800 financial document images. This dataset is designed to support research and development in the field of financial document analysis and visual question answering. ### Key Features: - 🖼️ 9,801 unique financial document images - ❓ 107,050 question-answer pairs - 🇬🇧 English language - 📄 Diverse financial document types ## Dataset Summary - **Training Set**: 9,212 images, 100,629 QA pairs - **Validation Set**: 589 images, 6,421 QA pairs - **Total**: 9,801 images, 107,050 QA pairs ## Get Started Here's a quick example of how to load and explore the dataset: ```python from datasets import load_dataset import json import matplotlib.pyplot as plt # Load the dataset data = load_dataset("sujet-ai/Sujet-Finance-QA-Vision-100k") # Access train and validation splits train_data = data['train'] val_data = data['test'] # Display info about a sample entry sample = val_data[0] print(f"Document ID: {sample['doc_id']}") print(f"Content preview: {sample['content']}") # Display the image plt.figure(figsize=(10, 10)) plt.imshow(sample['image']) plt.axis('off') plt.title(f"Image for Document {sample['doc_id']}") plt.show() # Print QA pairs for the sample qa_pairs = json.loads(sample['qa_pairs']) print("\nQuestion-Answer Pairs:") for qa in qa_pairs: print(f"Q: {qa['question']}") print(f"A: {qa['answer']}") print() ``` ## Dataset Creation This dataset is an evolution of our previous [Sujet-Finance-Vision-10k](https://huggingface.co/datasets/sujet-ai/Sujet-Finance-Vision-10k) dataset. The original dataset contained detailed annotations generated by GPT-4 for each image. However, we encountered challenges when fine-tuning small Vision-Language Models (VLMs) due to the extensive context window size required by these annotations. To address this issue, we used a different approach to break down our data into smaller pieces, easily digestible by a smaller model during the finetuning process: 1. We used the [meta-llama/Meta-Llama-3-70B](https://huggingface.co/meta-llama/Meta-Llama-3-70B) model to generate diverse question-answer pairs based on the original detailed annotations. 2. The model was prompted to create a variety of questions covering different aspects of each financial document, including factual, analytical, comparative, and hypothetical questions. 3. This process allowed us to maintain the depth of information while creating more concise and targeted QA pairs. Here's a simplified version of the prompt used to generate the QA pairs: ``` As an expert in financial document analysis, create diverse, high-quality question-answer pairs based on the given financial document content. Steps: 1. Analyze the document content. 2. Identify key themes, facts, and implications. 3. Generate varied questions covering: - Factual details - Analytical interpretations - Industry comparisons - Hypothetical scenarios 4. Provide concise, informative answers. 5. Ensure diversity and non-repetition. 6. Aim for at least 10 QA pairs, more if content allows. [Document Content Here] Output in JSON format: [ {"question": "What is the total revenue reported?", "answer": "The total revenue reported is $10 million for fiscal year 2023."}, {"question": "How does the profit margin compare to industry average?", "answer": "The 15% profit margin is 2 percentage points above the 13% industry average."}, ... (additional Q&A pairs) ] ``` ## Data Fields - `doc_id`: Unique identifier for the document - `content`: A rich annotation of the information covered in the document : Used to create the QA pairs. - `image`: The financial document image - `qa_pairs`: JSON string containing question-answer pairs ## Limitations and Bias While we've taken care to ensure the quality of the dataset, it's important to note: - The question-answer pairs were generated based on GPT-4 annotations and then refined using Llama 3 70B. While this process produces high-quality results, there may be instances where the answers do not perfectly correspond to the information in the image. - Through manual inspection, we've found that such discrepancies are rare and don't significantly impact the training/validation process. However, users should be aware of the limitations of this unsupervised and automated dataset generation. - The dataset focuses on English-language financial documents, which may limit its applicability to other languages or financial systems. ## Ethical Considerations Users of this dataset should be aware that: - The financial information contained in the images and QA pairs should not be used for making real-world financial decisions without proper verification. - The dataset may reflect biases present in the original financial documents or introduced during the annotation process. ## License This dataset is licensed under Apache 2.0. ## Disclaimer Sujet AI provides the Sujet-Finance-QA-Vision-100k dataset as-is, without any warranties, expressed or implied. We are not responsible for any consequences resulting from the use of this dataset. Users should exercise their own judgment when using the dataset for research, development, or any other purposes. The dataset may contain errors, inaccuracies, or biases, and should not be solely relied upon for critical decision-making in financial or other domains. Users are encouraged to validate and verify the information as needed for their specific use cases. By using this dataset, you agree to hold Sujet AI harmless from any and all claims, damages, or liabilities arising from its use. ## Citation and Contact If you use the Sujet-Finance-QA-Vision-100k dataset in your research, please cite it as: ``` @dataset{Sujet-Finance-QA-Vision-100k, author = {Sujet AI, Allaa Boutaleb, Hamed Rahimi}, title = {Sujet-Finance-QA-Vision-100k: A Large-Scale Dataset for Financial Document VQA}, year = {2024}, url = {https://huggingface.co/datasets/sujet-ai/Sujet-Finance-QA-Vision-100k} } ``` For questions, feedback, or collaborations, please reach out to us on [LinkedIn](https://www.linkedin.com/company/sujet-ai/) or visit our website [https://sujet.ai](https://sujet.ai).

KISTI-AIDATA/PaperMetaExtractionData

KISTI-AIDATA

--- {CC BY-NC} --- # 논문 메타데이터 추출 데이터(Extraction data from paper metadata) ## Outline - The data for extracting metadata from PDF domestic papers. - The data contains information in layout box extracted from each PDF paper with labels corresponding to metadata field types. - The information in each layout box are unique code, text, coordinates(x0, y0, x1, y1) of box, width of box, height of box and font size. - The file named as “train.txt” was constructed through the fully automatic inspection process. It contains a total of 5,241,746 labeled layout boxes for 295,306 papers in 503 journals. It was used as train set. - The file named as “valid.txt” was developed through the manual inspection process by several annotators. It contains a total of 155,629 labeled layout boxes for 9,895 papers in 503 journals. - The file named as “test.txt” was built through the manual inspection process. It contains a total of 159,925 labeled layout boxes for 10,119 papers in 503 journals. It was used as test set. ## Data format(TXT) - In the files, each layout box is separated by a newline. And each paper is separated by two newlines - The data structure of each layout box is as follows : "Unique code"(\t)"Metadata label"(\t)"Text"(\t)"x0 value "(\s)"y0 value"(\s)"x1value"(\s)"y1value"(\s)"width value" (\s)"height value"(\s)"font size" |No.|Metadata Fields|Label| |--|--|--| |1|Title(in Korean)|title_ko| |2|Title(in English)|title_en| |3|Author Name(in Korean)|author_name_ko| |4|Author Name(in English)|author_name_en| |5|Author Affiliation(in Korean)|ko_org| |6|Author Affiliation(in English)|en_org| |7|Abstract(in Korean)|abstract_ko| |8|Abstract(in English)|abstract_en| |9|Keywords(in Korean)|kwds_ko| |10|Keywords(in English)|kwds_en| |11|DOI|doi| |12|Journal name|journal| |13|Out of Boundary|O| ## Data statistics |Data|File name|#Journal|#Paper|#Layout Box| |--|--|--|--|--| |Train set|train.txt|503|295,306|5,241,746 | |Valid set|valid.txt|503|9,895|155,629| |Test set|test.txt|503|10,119|159,925| ## Data download http://doi.org/10.23057/48

1-800-SHARED-TASKS/uber_text-Vision-QA

1-800-SHARED-TASKS

--- dataset_info: features: - name: id dtype: string - name: questions sequence: string - name: answers sequence: string - name: image dtype: image splits: - name: train num_bytes: 1947112649.966 num_examples: 7181 - name: val num_bytes: 772401925.749 num_examples: 2799 download_size: 2705031857 dataset_size: 2719514575.715 --- # Dataset Card for "uber_text_qa" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

KISTI-AIDATA/ReferenceMetaExtractionData

KISTI-AIDATA

--- license: cc-by-nc-3.0 --- # 참고문헌 메타 추출 데이터(Extraction data from reference metadata) ## Outline - The corpus for extracting metadata from multilingual journal references. - The corpus contains the tokens of reference string with IOB labels corresponding to metadata field types. - The file named as “automatic_inspection_data(train_set).txt” was constructed through the fully automatic inspection process. It contains a total of 3,680,620 labeled references, and was used as training set for training our BERT-based parsing model in our study. - The file named as “manual_insepction_data_(validation_set).txt” was developed through the manual inspection process by several annotators. It contains a total of 63,878 labeled references, and was used as validation set. - The file named as “manual_inspection_data_(test_set).txt” was built through the manual inspection process. It contains a total of 71,489 labeled references, and was used as test set. In the files, each reference is separated by a newline character. In each first line of references, a unique identifier and language type are listed. ## Data format(TXT) - CoNLL 2002 Format, https://paperswithcode.com/dataset/conll-2002  ## Data statistics - Number of labeled references: 3,815,987 ## Data download http://doi.org/10.23057/47 ## License CC BY-NC <br>(Copyright Holder : Korea Institute of Science and Technology Information)

KISTI-AIDATA/ImageRecognitionData

KISTI-AIDATA

--- license: cc-by-nc-nd-4.0 --- # 표/그림 객체 인식 데이터셋 본 데이터셋은 논문 및 연구보고서 등 학술문헌의 표와 그림을 자동으로 추출하기 위한 데이터셋이다. ## 데이터 포맷(JPG, TXT) |유형|설명| |--|--| |JPG|표/그림이 존재하는 연구보고서의 페이지를 이미지 파일로 변환| |TXT|각 페이지에 존재하는 표, 그림, 캡션의 레이블 및 좌표 정보를 포함| \<표, 그림, 캡션 레이블 및 좌표 정보 예\>  ## 데이터 통계 - 페이지(파일) 수: 9,124개 - 데이터셋 개수: 표: 7,096 그림: 107,30 표캡션: 6,799 그림캡션: 10,615 - 레이블 개수: 4 (0: 표, 1: 그림, 2: 표캡션, 3: 그림캡션) ## 데이터 구축방법 2021~2022년에 등록된 국가R&D보고서를 대상으로 이미지 추출 모델을 이용하여 1차로 표와 그림을 추출하고, 이후 어노테이터가 검증하는 방식으로 구축했다. ## 데이터 다운로드 http://doi.org/10.23057/71 ## 라이선스 비영리 이용, 출처 표기, 재배포 금지 <br>※ 제공하는 데이터는 연구 수행 주체의 비공개 요청에 의해 일부 삭제가 될 수 있으며, 연구용으로만 사용해야 하며 재배포를 절대 금지함.

KISTI-AIDATA/DocClassificationData

KISTI-AIDATA

--- license: cc-by-nc-nd-4.0 --- # 논문, 보고서, 특허 과학기술표준분류 데이터셋 본 데이터셋은 논문, 보고서, 특허의 제목과 요약문을 과학기술표준분류(2023년 버전)의 중분류와 소분류로 분류한 데이터셋이다. ## 데이터 포맷(TXT) |유형|설명| |--|--| |research_id |NTIS 과제번호| |code|2023년도 과학기술표준분류코드| |similarity|해당 코드에 대한 ChatGPT의 설명문 임베딩과 제목+요약문 임베딩간에 코사인유사도| |type|논문, 보고서, 특허 유형| |title_abstract|각 유형의 제목과 요약문을 취합한 입력문장| ## 데이터 통계 - 중분류 데이터셋 : 961,851건 - 소분류 데이터셋 : 314,234건 - 레이블 개수 : 중분류 185개, 소분류 1,254개 ## 예제 research_id code similarity type title_abstract 1415167736 EB0108 0.8298083304216014 patent 전해정련을 이용한 고순도 네오디뮴 회수방법 본 발명은 불화리튬 (lif) 및 불화칼슘 (caf2)을 함유하는 용융염을 이용한 전해정련을 통하여, 네오디뮴-디스프로슘 합금으로부터 고순도 네오디뮴의 회수 방법을 제공한다. 본 발명에 따르면, 희토류 자석으로부터 추출된 네오디뮴-디스프로슘 합금에서 네오디뮴(nd)을 높은 추출 효율 및 단순하고 경제적인 추출 공정으로 회수할 수 있고, 건식 공정이어서 환경 문제에 대한 부담이 적은 효과가 있다. 1395046214 LB0305 0.7849073675453806 paper 익힌 숙잠의 알콜성 질환 예방 효과 우리나라는 국민 1인당 연간 음주량이 세계 190여개 국가 중 15위권 안에 들 정도로 술을 많이 마시는 국가로, 과도한 음주로 인한 지방간, 간경화, 위염, 숙취 등 빈번한 알콜성 질환의 발생으로 개인적, 사회적 비용이 과도하게 지불되고 있는 상황이다. 익힌 숙잠 생산기술은 세계 최초로 개발된 기술로서 지금까지는 섭취가 불가능했던 5령 3일 이후부터 숙잠까지의 누에, 즉 숙잠을 섭취할 수 있도록 분말로 만드는 기술이다. 이 기술로 제작된 익힌 숙잠 분말을 사용하여 알콜성 지방간, 간경화, 위염 및 숙취 등 알콜성 질환에 대한 예방효과를 시험하였다. 그 결과, 익힌 숙잠의 지속적인 섭취는 알콜 투여 후, 혈중 알콜 농도 및 그 대사산물인 아테트알데히드를 현저하게 감소시켰을 뿐만 아니라, 알콜에 의해서 유도된 지방간, 간섬유증 및 위염을 현저하게 예방하는 효과를 나타냈다. 따라서 익힌 숙잠을 지속적으로 섭취한다면 국민건강증진과 보건의료비용의 감소 및 양잠산업발전 등 1석3조의 효과를 기대할 수 있을 것이다. 1711078644 EI0606 0.8081579607040635 paper 구조광 기술을 이용한 레이저 스펙클 기반의 변형률 측정 센서 접촉식 기반 변형률 측정 센서는 접촉 방식의 고질적인 문제로 부착 위치에 따라 변형률 측정값의 오차를 동반하며, 센서 탈부착 시 파손의 위험 또한 가져온다. 이를 극복하기 위하여, 본 연구는 시편의 변형에 매우 민감한 레이저 스펙클 영상(laser speckle imaging)을 이용한 비접촉식 센서를 구현하였다. 기존의 보고된 스펙클 기반의 센서들은 주변광(ambient light)에 취약하여 현장 적용에 어려움이 따른다. 본 연구에서는 주변광 환경에서도 고대조 및 고민감도 측정이 가능하게 하고자 구조광(structured illumination) 기술을 적용하였다. 또한, 취득한 레이저 스펙클 영상에 대하여 2차원 상관관계 분석을 통해 정량적인 변형률 값을 산출하였다. 알루미늄 시편의 인장 실험을 실시하여 변형률 게이지(strain gauge)와 비교 분석하였으며, 0.99의 높은 상관관계를 확인하였다. 본 센서는 정밀한 동시에 주변광에도 강건한 특성은 실제 철로 유지관리와 같은 현장에 응용될 수 있음을 시사한다. 1415155091 ED0210 0.8294236332199664 patent 상압소결 실리콘 카바이드 웨이퍼 캐리어 및 결합구조와 그 결합방법 본 발명은 상압소결 실리콘 카바이드 웨이퍼 캐리어 및 결합구조와 그 결합방법에 관한 것으로, 더욱 자세하게는 다수의 지지바(30)와 상기 지지바(30)의 양측에 각각 결합되는 상, 하부플레이트(10, 20)로 구성되되, 상기 지지바(30)와 상, 하부플레이트(10, 20)를 결합 시, 1200˚c 온도에서도 사용이 가능하고, 내부식성 및 고온 강도가 강하며, 반도체 공정 사용 수명이 rb sic반응소결 실리콘 카바이드에 비해 더 길고, cvd sic coating 시 흡착력 우수와 사용 중 파손 시 수리 가능한 결합구조 및 그 방법을 제공함으로써, 경제적 효율성과 편리성을 동시에 부여할 수 있는 유용한 발명인 것이다. 1395048567 LB0305 0.8027775242722348 paper 오디생산용 뽕나무 시기별 누에사육가능성 분석 전라북도 부안군 비닐하우스와 노지에서 재배되고 있는 오디 생산용 뽕나무(과상 2호)를 대상으로 누에사육용 뽕나무 청일뽕을 대조구로 하여 각각 뽕잎을 활용하여 시기별로 누에사육가능성을 분석하고자 하였다. 누에사육시기는 수확전과 수확기, 수확후로 구분하여 각각 5월 1일과, 5월 20일, 6월 10일에 소잠을 하고 5령 3일까지 사육을 실시하면서 각 시기별 누에 발육특성 및 뽕잎생산량을 비교하였다. 발육특성은 령기별 누에 발육기간 및 5령 3일 누에 무게, 감잠비율 등을 조사하였다. 시기별 누에 발육기간은 5령 3일까지 20일~22일 정도가 소요되었고, 수확전과 수확후에 비해 수확기에서 약간 빠른 경향이나, 큰 차이는 없었다. 각 뽕잎별 5령 3일 무게로 볼 때 수확전에는 청일뽕과 노지 뽕잎에 비하여 하우스뽕잎에서 발육이 부진하였고, 수확기에는 하우스, 노지 뽕잎 모두 청일뽕과 비슷하였지만, 수확후에는 노지 뽕잎에서 발육이 가장 좋았다. 감잠비율은 청일뽕에 비하여 과상 2호에서 높은 경향이고, 하우스 뽕잎에서 감잠비율이 가장 높았다. 또한, 소잠시기가 늦을수록 감잠비율이 많아지는 경향이었다. 시기별 과상 2호 뽕잎량은 수확전에는 청일뽕에 비하여 하우스에서 뽕잎량이 가장 많았고, 노지는 생육이 느려 상대적으로 부족하였으나, 청일뽕에 비하여 주당 뽕잎무게는 많은 경향이었다. 수확기와 수확후에는 노지와 하우스 뽕잎량은 비슷하였고, 청일뽕이 가장 적었다. 따라서, 수확기에도 누에사육이 가능하나, 수확작업 때문에 작업능률이 떨어질 것으로 판단되고, 수확전과 수확후에는 하우스, 노지 모두 누에 사육이 가능할 것으로 판단되며, 다만, 노지 뽕잎은 수확전에 뽕잎량이 부족할 것으로 보여 많은 량을 사육하지는 못할 것으로 판단된다. 1711060009 LC0301 0.8283563397995648 patent blt 저해 활성을 갖는 화합물을 유효성분으로 포함하는 아토피 예방 또는 치료용 약학적 조성물 본 발명은 blt2 (leukotriene b4 receptor 2) 억제 활성을 나타내는 화합물, 이의 이성질체 또는 이의 약학적 허용가능한 염을 유효성분으로 포함하는, 아토피(atopic dermatitis)의 예방 또는 치료용 약학적 조성물에 관한 것이다. 본 발명자들은 btl2 억제 활성을 나타내는 화합물의 우수한 주화성 억제 효과 및 아토피 치료 효과 등을 실험적으로 확인하였는바, 본 발명의 화합물은 아토피를 치료하기 위한 약학적 조성물로 유용하게 사용될 수 있을 것으로 기대된다. 1711048155 NC0308 0.8174342544699759 patent 퀴놀린 4-온 유도체 또는 이의 약학적으로 허용 가능한 염을 유효성분으로 포함하는 폐렴의 예방 또는 치료용 약학적 조성물 본 발명은 퀴놀린 4-온 유도체, 이의 약학적으로 허용 가능한 염, 또는 이를 유효성분으로 포함하는 폐렴의 예방 또는 치료용 약학적 조성물에 관한 것이다. 본 발명에 따른 퀴놀린 4-온 유도체는 우수한 항균활성을 가질 뿐만 아니라, 종래 일반적으로 사용되고 있는 항균제와는 달리 약물 내성을 갖고 있는 폐렴균에 대해서도 항균 활성이 뛰어나므로 이들 폐렴균에 의해서 발병되는 폐렴의 예방 또는 치료용 약학적 조성물로써 유용하게 사용될 수 있다. 1345274028 EC0103 0.6762329957051496 paper gelatin-based extracellular matrix cryogels for cartilage tissue engineering in this study, gelatin-based cryogels were fabricated by mixing methacrylated gelatin (gelma) with methacrylated hyaluronic acid (meha) or methacrylated chondroitin sulfate (mecs) for cartilage tissue engineering. in vitro revealed that mecs incorporated gelatin-based cryogel (g-mecs) showed significant cartilaginous tissue stimulation. furthermore, the cell-laden gelatin-based ecm cryogels were implanted into mouse subcutaneous tissue for 6 weeks and displayed uniform distribution of cells with normal phenotype maintenance. finally, when these cryogels were implanted into osteochondral defect of new zealand white rabbit, full integration with host tissue and increased cellularity were observed with g-mecs cryogel. (c) 2016 the korean society of industrial and engineering chemistry. published by elsevier b.v. all rights reserved. 1345277451 LC0110 0.7889292570676942 patent 질병 예측 시스템 본 발명의 실시 예에 따른 질병 예측 시스템은 사용자의 질병 예측에 요구되는 유전적, 환경적, 생활습관적 개인정보를 질병 예측 서버로 제공하는 사용자 기기, 상기 사용자 기기로부터 제공받은 개인정보를 통계적 방법과 기계학습법을 이용한 질병 예측 모델에 적용하여 사용자의 질병에 대한 발병 위험을 수치 데이터로 산출하는 질병 예측 서버 및 해당 질병과 관련된 임상 및 유전상담 정보를 제공하는 공공 db를 포함하는 것을 특징으로 한다. 1711053191 EH0104 0.8029917995724812 patent 복합 금속 입자 제조장치 및 제조방법 본 발명은 복합 금속 입자 제조장치 및 제조방법에 관한 것으로, 본 발명의 일 측면에 따르면, 화염 영역을 형성하기 위한 화염 반응기; 복합 금속 입자를 생성하기 위하여, 금속 입자 및 전구체 용액을 각각 화염 영역 측으로 공급하기 위한 하나 이상의 공급부; 및 화염 영역 측으로 초음파를 분사하도록 마련된 초음파 발생기를 포함하는 복합 금속 입자 제조장치가 제공된다. 1415168124 EF0601 0.8105266813447929 patent 에너지 스마트팜 센싱 데이터 오류 식별방법 본 발명은 센서 네트워크 환경에서의 오류 데이터 식별방법에 관한 것으로, 구체적으로는 센서들을 통해 측정된 전력정보들을 수집하는 센서노드 및 상기 센서노드에서 수집한 데이터를 저장하는 센서로거를 포함하는 센서 네트워크 환경에서 각 센서, 상기 센서노드 또는 상기 센서로거에서 발생할 수 있는 데이터의 오류를 식별하는 것으로, 특히, 에너지 스마트팜에서 사용가능한 센서 네트워크 환경에서의 오류 데이터 식별방법에 관한 것이다. 1345278418 EA0210 0.7022551980243033 paper optimal number of components in a load-sharing system for maximizing reliability a k-out-of-n:g load sharing system is a cluster of n components designed to withstand a certain amount of load in field operation, working only if no fewer than k components work. previous research on a load sharing system has focused on predicting the time-independent reliability from the stress-strength model or estimating the unknown parameters of the time-dependent reliability for a given load sharing rule. differently, in this paper, we consider the problem of determining the optimal n to maximize the reliability of both n-out-of-n:g and (n-1)-out-of-n:g load sharing systems. since the load of each component decreases in n, the proportional hazard model is employed to relate the component failure rate with the load, assuming that the components, which have exponential distributions for given loads, are independent of each other. we then derive a sufficient condition under which a smaller number of components each withstanding a high load is preferred to a larger number of components each withstanding a small load. a numerical example is given for the rocket propulsion system to illustrate the result. 1545016652 LB1801 0.7184173006918623 paper chloroplast dna-derived markers for the authentication of oriental medicinal rubus species and mistaken identity of bokbunja in the local markets of korea the traditional oriental medicine bokbunja, prepared from immature berries of rubus coreanus is used as an anti-oxidant,diuretic, and cure for impotence. the bokbunja wine made from fermented fruits of bokbunja has been used as a functionalfood as well. however, the usage of bokbunja has been problematic over the years due to the abundance of mistakenlyidentified berries such as rubus chingii, rubus crataegifolius, and rubus occidentalis. thus, here we developed a methodfor the molecular differentiation of rubus species as well as the authentication bokbunja from other rubus species. wescreened several sequences from the chloroplast dna of these species and found that the rpl16 region was polymorphicfor r. coreanus and r. occidentalis, while the trng–trns intergenic spacer region was polymorphic for r. chingii and r.crataegifolius. species-specific primers were designed and a multiplex pcr was performed by combining the markers atthe rpl16 and trng–trns regions. amplicons of 686 bp for r. coreanus and 478 bp for r. occidentalis were produced by theprimers 5′ rcor or 5′ rocci, respectively, with 3′ rpl16; whereas, amplicons of 389 bp for rubus crataegifolius and 180 bpfor r. chingii were produced by 5′ rcra or 5′ trng–trns, respectively, and 3′ rcra/rchi. the deduced molecular markers wereutilized to authenticate the bokbunja products and demonstrated that the majority of bokbunja samples from the marketswere adulterant berries. hence, our results indicate that the produced molecular markers can serve as an effective tool toauthenticate bokbunja. 1711071232 LC0603 0.8006337804347129 paper cost comparison of androgen deprivation therapy and radical prostatectomy for prostate cancer purposes: 본 연구는 전립선암 환자의 의료비 지출을 평가하기 위해 남성호르몬 박탈 치료와 근치적 전립선적출술의 비용을 비교하였다. methods: 본 연구는 스마트 전립선암 데이터베이스(smart prostate cancer database)의 전립선암 환자 357명의 데이터와 청구데이터베이스에서 의료비 관련 데이터를 도출하였다. 근치적 전립선적출술과 남성호르몬 박탈 치료간 비교를 위해 독립표본 t검정을 실시하였다. 또한 남성호르몬 박탈 치료와 근치적 전립선적출술에 영향을 미치는 요인을 검증하기 위해 다중회귀 분석을 실시하였다. findings: 치료 후 1년까지 남성호르몬 박탈치료가 근치적 전립선적출술 보다 비용이 낮은 것으로 나타났으며, 치료 후 4년까지 낮게 유지되었다. 그러나 4년이 지나면 남성호르몬 박탈 치료의 누적의료비가 근치적 전립선적출술보다 더 유의미하게 높게 나타났다. 환자의 병기가 높거나 나이가 많은 경우 근치적 전립선적출술보다 남성호르몬 박탈 치료를 할 확률이 더 높았다. practical implications: 본 연구는 조기 암 발견이 환자 뿐 아니라 국민건강보험공단의 의료비를 줄일 수 있다는 것을 보여 준다. 또한 의료비를 정확히 평가하기 위해서는 오랜 기간의 정보를 평가해야 하며, 이를 기반으로 평가 및 예측이 필요함을 증명하였다. 1711047293 EC0103 0.6946216096187761 paper effects of vibrations in marine environments on performance of molten-carbonate fuel cells owing to the strengthening of environmental regulations, highly efficient and environmentally sustainable power supply systems have attracted significant attention as auxiliary power units (apus) for marine applications. among several candidates, molten carbonate fuel cells (mcfcs) is of particularly interest because it provides high efficiency with essentially no greenhouse gas emissions of nox and sox. in this study, the effects of vibrations caused by sea-waves and swells on the operation of mcfcs on marine ships are investigated. an mcfc single cell with a unit area of 100 cm2 was tested in a vibration environment at an operating temperature of 620 oc. at a low sealing pressure (0.1 mpa), the performance of the cell decreased owing to increased mass-transfer resistance. electrochemical impedance spectroscopy revealed that using oxygen and co2 as the cathode reactants mitigates the degradation by the vibration induced mass-transfer resistance. in addition, the mcfc single cell is operated under various vibration conditions, including the resonance frequency (13 and 29 hz). it was found that the vibration environment does not affect the performance of mcfcs under normal operating conditions. 1415146859 EC0304 0.7908056708780745 paper concentration-mediated multicolor fluorescence polymer carbon dots abstractpolymer dots (pds) showing concentrationmediated multicolor fluorescence were first prepared from sulfuric acidtreated dehydration of pluronic f127 in a single step. pluronicbased pds (ppds) showed high dispersion stability in solvent media and exhibited a fluorescence emission that was widely tunable from red to blue by adjusting both the excitation wavelengths and the ppd concentration in an aqueous solution. this unique fluorescence behavior of ppds might be a result of crosstalk in the fluorophores of the poly(propylene glycol)rich core inside the ppd through either energy transfer or charge transfer. reconstruction of the surface energy traps of the ppds mediated through aggregation may lead to a new generation of carbonbased nanomaterials possessing a fluorescence emission and tunable by adjusting the concentration. these structures may be useful in the design of multifunctional carbon nanomaterials with tunable emission properties according to a variety of internal or external stimuli. copyright 2015 john wiley sons, ltd.  ## 데이터 구축방법  ## 데이터 다운로드 http://doi.org/10.23057/70 ## 라이선스 비영리 이용, 출처 표기, 재배포 금지

bio-nlp-umass/NoteAid-README

bio-nlp-umass

--- license: cc-by-nc-4.0 --- ## Datasets The Datasets presented here have jargon terms, lay definitions, general definitions, and EHRs. - readme_exp - The general definitions are produced from UMLS open-source data. - readme_exp_good - The general definitions are good for training. - readme_exp_bad - The general definitions are not good enough for training. - readme_syn - We used LLMs to generate General definitions - readme_syn_good - The general definitions are good for training. - readme_syn_bad - The general definitions are not good for training. # Columns - ann_text column is the jargon term - split_print(readme_exp, readme_exp_good, readme_exp_bad) and gen_def(readme_syn, readme_syn_good, readme_syn_bad) columns are the general definitions - gpt_generated is the GPT3.5 generated lay definitions which are slight modifications of the original lay definitions used. - gpt_text_to_annotate is the GPT4o-mini generated EHRs which are slight modifications of the original EHRs used. ## Citation ``` @article{yao2023readme, title={README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLP}, author={Yao, Zonghai and Kantu, Nandyala Siddharth and Wei, Guanghao and Tran, Hieu and Duan, Zhangqi and Kwon, Sunjae and Yang, Zhichao and Yu, Hong and others}, journal={arXiv preprint arXiv:2312.15561}, year={2023} } ```

Sephfox/ReflectionofaLilly

Sephfox

--- license: mit ---

Riley33/kvqa_multiple_choice

Riley33

--- dataset_info: features: - name: question_id dtype: int64 - name: image dtype: image - name: text dtype: string - name: choice sequence: string - name: choice_score dtype: string - name: category dtype: string - name: answers dtype: string splits: - name: train num_bytes: 18106037337.129 num_examples: 9697 download_size: 6176491962 dataset_size: 18106037337.129 configs: - config_name: default data_files: - split: train path: data/train-* ---

Anrom97/WMS-dataset

Anrom97

--- license: unknown ---

open-llm-leaderboard/nbeerbower__gemma2-gutenberg-27B-details

open-llm-leaderboard

--- pretty_name: Evaluation run of nbeerbower/gemma2-gutenberg-27B dataset_summary: "Dataset automatically created during the evaluation run of model\ \ [nbeerbower/gemma2-gutenberg-27B](https://huggingface.co/nbeerbower/gemma2-gutenberg-27B)\n\ The dataset is composed of 38 configuration(s), each one corresponding 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.\n\nTo load the details from a run, you can for instance do the following:\n\ ```python\nfrom datasets import load_dataset\ndata = load_dataset(\n\t\"open-llm-leaderboard/nbeerbower__gemma2-gutenberg-27B-details\"\ ,\n\tname=\"nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_boolean_expressions\"\ ,\n\tsplit=\"latest\"\n)\n```\n\n## Latest results\n\nThese are the [latest results\ \ from run 2024-09-30T00-44-40.185741](https://huggingface.co/datasets/open-llm-leaderboard/nbeerbower__gemma2-gutenberg-27B-details/blob/main/nbeerbower__gemma2-gutenberg-27B/results_2024-09-30T00-44-40.185741.json)\ \ (note that there 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 \"leaderboard\": {\n\ \ \"inst_level_strict_acc,none\": 0.34172661870503596,\n \"\ inst_level_strict_acc_stderr,none\": \"N/A\",\n \"inst_level_loose_acc,none\"\ : 0.35611510791366907,\n \"inst_level_loose_acc_stderr,none\": \"N/A\"\ ,\n \"acc,none\": 0.19822140957446807,\n \"acc_stderr,none\"\ : 0.0036345583399346364,\n \"prompt_level_strict_acc,none\": 0.2476894639556377,\n\ \ \"prompt_level_strict_acc_stderr,none\": 0.0185761392851853,\n \ \ \"exact_match,none\": 0.0,\n \"exact_match_stderr,none\": 0.0,\n\ \ \"prompt_level_loose_acc,none\": 0.2643253234750462,\n \"\ prompt_level_loose_acc_stderr,none\": 0.018976469193346637,\n \"acc_norm,none\"\ : 0.3613957711765469,\n \"acc_norm_stderr,none\": 0.005167160431579617,\n\ \ \"alias\": \"leaderboard\"\n },\n \"leaderboard_bbh\"\ : {\n \"acc_norm,none\": 0.3784065266446797,\n \"acc_norm_stderr,none\"\ : 0.005968335531782059,\n \"alias\": \" - leaderboard_bbh\"\n \ \ },\n \"leaderboard_bbh_boolean_expressions\": {\n \"acc_norm,none\"\ : 0.78,\n \"acc_norm_stderr,none\": 0.02625179282460579,\n \ \ \"alias\": \" - leaderboard_bbh_boolean_expressions\"\n },\n \"\ leaderboard_bbh_causal_judgement\": {\n \"acc_norm,none\": 0.5080213903743316,\n\ \ \"acc_norm_stderr,none\": 0.03665706061581772,\n \"alias\"\ : \" - leaderboard_bbh_causal_judgement\"\n },\n \"leaderboard_bbh_date_understanding\"\ : {\n \"acc_norm,none\": 0.288,\n \"acc_norm_stderr,none\"\ : 0.028697004587398253,\n \"alias\": \" - leaderboard_bbh_date_understanding\"\ \n },\n \"leaderboard_bbh_disambiguation_qa\": {\n \"acc_norm,none\"\ : 0.36,\n \"acc_norm_stderr,none\": 0.03041876402517494,\n \ \ \"alias\": \" - leaderboard_bbh_disambiguation_qa\"\n },\n \"\ leaderboard_bbh_formal_fallacies\": {\n \"acc_norm,none\": 0.508,\n \ \ \"acc_norm_stderr,none\": 0.03168215643141386,\n \"alias\"\ : \" - leaderboard_bbh_formal_fallacies\"\n },\n \"leaderboard_bbh_geometric_shapes\"\ : {\n \"acc_norm,none\": 0.14,\n \"acc_norm_stderr,none\"\ : 0.021989409645240245,\n \"alias\": \" - leaderboard_bbh_geometric_shapes\"\ \n },\n \"leaderboard_bbh_hyperbaton\": {\n \"acc_norm,none\"\ : 0.58,\n \"acc_norm_stderr,none\": 0.03127799950463661,\n \ \ \"alias\": \" - leaderboard_bbh_hyperbaton\"\n },\n \"leaderboard_bbh_logical_deduction_five_objects\"\ : {\n \"acc_norm,none\": 0.236,\n \"acc_norm_stderr,none\"\ : 0.026909337594953852,\n \"alias\": \" - leaderboard_bbh_logical_deduction_five_objects\"\ \n },\n \"leaderboard_bbh_logical_deduction_seven_objects\": {\n \ \ \"acc_norm,none\": 0.2,\n \"acc_norm_stderr,none\": 0.02534897002097912,\n\ \ \"alias\": \" - leaderboard_bbh_logical_deduction_seven_objects\"\n\ \ },\n \"leaderboard_bbh_logical_deduction_three_objects\": {\n \ \ \"acc_norm,none\": 0.432,\n \"acc_norm_stderr,none\": 0.03139181076542942,\n\ \ \"alias\": \" - leaderboard_bbh_logical_deduction_three_objects\"\n\ \ },\n \"leaderboard_bbh_movie_recommendation\": {\n \"\ acc_norm,none\": 0.424,\n \"acc_norm_stderr,none\": 0.03131803437491622,\n\ \ \"alias\": \" - leaderboard_bbh_movie_recommendation\"\n },\n\ \ \"leaderboard_bbh_navigate\": {\n \"acc_norm,none\": 0.532,\n\ \ \"acc_norm_stderr,none\": 0.031621252575725574,\n \"alias\"\ : \" - leaderboard_bbh_navigate\"\n },\n \"leaderboard_bbh_object_counting\"\ : {\n \"acc_norm,none\": 0.228,\n \"acc_norm_stderr,none\"\ : 0.026587432487268498,\n \"alias\": \" - leaderboard_bbh_object_counting\"\ \n },\n \"leaderboard_bbh_penguins_in_a_table\": {\n \"\ acc_norm,none\": 0.3150684931506849,\n \"acc_norm_stderr,none\": 0.03857820876541411,\n\ \ \"alias\": \" - leaderboard_bbh_penguins_in_a_table\"\n },\n\ \ \"leaderboard_bbh_reasoning_about_colored_objects\": {\n \"\ acc_norm,none\": 0.204,\n \"acc_norm_stderr,none\": 0.025537121574548162,\n\ \ \"alias\": \" - leaderboard_bbh_reasoning_about_colored_objects\"\n\ \ },\n \"leaderboard_bbh_ruin_names\": {\n \"acc_norm,none\"\ : 0.54,\n \"acc_norm_stderr,none\": 0.031584653891499004,\n \ \ \"alias\": \" - leaderboard_bbh_ruin_names\"\n },\n \"leaderboard_bbh_salient_translation_error_detection\"\ : {\n \"acc_norm,none\": 0.272,\n \"acc_norm_stderr,none\"\ : 0.028200088296309975,\n \"alias\": \" - leaderboard_bbh_salient_translation_error_detection\"\ \n },\n \"leaderboard_bbh_snarks\": {\n \"acc_norm,none\"\ : 0.4606741573033708,\n \"acc_norm_stderr,none\": 0.03746587736387869,\n\ \ \"alias\": \" - leaderboard_bbh_snarks\"\n },\n \"leaderboard_bbh_sports_understanding\"\ : {\n \"acc_norm,none\": 0.664,\n \"acc_norm_stderr,none\"\ : 0.029933259094191533,\n \"alias\": \" - leaderboard_bbh_sports_understanding\"\ \n },\n \"leaderboard_bbh_temporal_sequences\": {\n \"\ acc_norm,none\": 0.26,\n \"acc_norm_stderr,none\": 0.027797315752644335,\n\ \ \"alias\": \" - leaderboard_bbh_temporal_sequences\"\n },\n\ \ \"leaderboard_bbh_tracking_shuffled_objects_five_objects\": {\n \ \ \"acc_norm,none\": 0.18,\n \"acc_norm_stderr,none\": 0.02434689065029351,\n\ \ \"alias\": \" - leaderboard_bbh_tracking_shuffled_objects_five_objects\"\ \n },\n \"leaderboard_bbh_tracking_shuffled_objects_seven_objects\"\ : {\n \"acc_norm,none\": 0.1,\n \"acc_norm_stderr,none\":\ \ 0.01901172751573434,\n \"alias\": \" - leaderboard_bbh_tracking_shuffled_objects_seven_objects\"\ \n },\n \"leaderboard_bbh_tracking_shuffled_objects_three_objects\"\ : {\n \"acc_norm,none\": 0.368,\n \"acc_norm_stderr,none\"\ : 0.03056207062099311,\n \"alias\": \" - leaderboard_bbh_tracking_shuffled_objects_three_objects\"\ \n },\n \"leaderboard_bbh_web_of_lies\": {\n \"acc_norm,none\"\ : 0.532,\n \"acc_norm_stderr,none\": 0.031621252575725574,\n \ \ \"alias\": \" - leaderboard_bbh_web_of_lies\"\n },\n \"leaderboard_gpqa\"\ : {\n \"acc_norm,none\": 0.2726510067114094,\n \"acc_norm_stderr,none\"\ : 0.012909943366565096,\n \"alias\": \" - leaderboard_gpqa\"\n \ \ },\n \"leaderboard_gpqa_diamond\": {\n \"acc_norm,none\": 0.2474747474747475,\n\ \ \"acc_norm_stderr,none\": 0.030746300742124484,\n \"alias\"\ : \" - leaderboard_gpqa_diamond\"\n },\n \"leaderboard_gpqa_extended\"\ : {\n \"acc_norm,none\": 0.28205128205128205,\n \"acc_norm_stderr,none\"\ : 0.019275803929950375,\n \"alias\": \" - leaderboard_gpqa_extended\"\ \n },\n \"leaderboard_gpqa_main\": {\n \"acc_norm,none\"\ : 0.27232142857142855,\n \"acc_norm_stderr,none\": 0.02105508212932411,\n\ \ \"alias\": \" - leaderboard_gpqa_main\"\n },\n \"leaderboard_ifeval\"\ : {\n \"prompt_level_strict_acc,none\": 0.2476894639556377,\n \ \ \"prompt_level_strict_acc_stderr,none\": 0.0185761392851853,\n \ \ \"inst_level_strict_acc,none\": 0.34172661870503596,\n \"inst_level_strict_acc_stderr,none\"\ : \"N/A\",\n \"prompt_level_loose_acc,none\": 0.2643253234750462,\n \ \ \"prompt_level_loose_acc_stderr,none\": 0.018976469193346637,\n \ \ \"inst_level_loose_acc,none\": 0.35611510791366907,\n \"inst_level_loose_acc_stderr,none\"\ : \"N/A\",\n \"alias\": \" - leaderboard_ifeval\"\n },\n \ \ \"leaderboard_math_hard\": {\n \"exact_match,none\": 0.0,\n \ \ \"exact_match_stderr,none\": 0.0,\n \"alias\": \" - leaderboard_math_hard\"\ \n },\n \"leaderboard_math_algebra_hard\": {\n \"exact_match,none\"\ : 0.0,\n \"exact_match_stderr,none\": 0.0,\n \"alias\": \"\ \ - leaderboard_math_algebra_hard\"\n },\n \"leaderboard_math_counting_and_prob_hard\"\ : {\n \"exact_match,none\": 0.0,\n \"exact_match_stderr,none\"\ : 0.0,\n \"alias\": \" - leaderboard_math_counting_and_prob_hard\"\n\ \ },\n \"leaderboard_math_geometry_hard\": {\n \"exact_match,none\"\ : 0.0,\n \"exact_match_stderr,none\": 0.0,\n \"alias\": \"\ \ - leaderboard_math_geometry_hard\"\n },\n \"leaderboard_math_intermediate_algebra_hard\"\ : {\n \"exact_match,none\": 0.0,\n \"exact_match_stderr,none\"\ : 0.0,\n \"alias\": \" - leaderboard_math_intermediate_algebra_hard\"\ \n },\n \"leaderboard_math_num_theory_hard\": {\n \"exact_match,none\"\ : 0.0,\n \"exact_match_stderr,none\": 0.0,\n \"alias\": \"\ \ - leaderboard_math_num_theory_hard\"\n },\n \"leaderboard_math_prealgebra_hard\"\ : {\n \"exact_match,none\": 0.0,\n \"exact_match_stderr,none\"\ : 0.0,\n \"alias\": \" - leaderboard_math_prealgebra_hard\"\n \ \ },\n \"leaderboard_math_precalculus_hard\": {\n \"exact_match,none\"\ : 0.0,\n \"exact_match_stderr,none\": 0.0,\n \"alias\": \"\ \ - leaderboard_math_precalculus_hard\"\n },\n \"leaderboard_mmlu_pro\"\ : {\n \"acc,none\": 0.19822140957446807,\n \"acc_stderr,none\"\ : 0.0036345583399346364,\n \"alias\": \" - leaderboard_mmlu_pro\"\n \ \ },\n \"leaderboard_musr\": {\n \"acc_norm,none\": 0.3716931216931217,\n\ \ \"acc_norm_stderr,none\": 0.017128776450158697,\n \"alias\"\ : \" - leaderboard_musr\"\n },\n \"leaderboard_musr_murder_mysteries\"\ : {\n \"acc_norm,none\": 0.516,\n \"acc_norm_stderr,none\"\ : 0.03166998503010743,\n \"alias\": \" - leaderboard_musr_murder_mysteries\"\ \n },\n \"leaderboard_musr_object_placements\": {\n \"\ acc_norm,none\": 0.2421875,\n \"acc_norm_stderr,none\": 0.026827898476066977,\n\ \ \"alias\": \" - leaderboard_musr_object_placements\"\n },\n\ \ \"leaderboard_musr_team_allocation\": {\n \"acc_norm,none\"\ : 0.36,\n \"acc_norm_stderr,none\": 0.03041876402517494,\n \ \ \"alias\": \" - leaderboard_musr_team_allocation\"\n }\n },\n \"\ leaderboard\": {\n \"inst_level_strict_acc,none\": 0.34172661870503596,\n\ \ \"inst_level_strict_acc_stderr,none\": \"N/A\",\n \"inst_level_loose_acc,none\"\ : 0.35611510791366907,\n \"inst_level_loose_acc_stderr,none\": \"N/A\",\n\ \ \"acc,none\": 0.19822140957446807,\n \"acc_stderr,none\": 0.0036345583399346364,\n\ \ \"prompt_level_strict_acc,none\": 0.2476894639556377,\n \"prompt_level_strict_acc_stderr,none\"\ : 0.0185761392851853,\n \"exact_match,none\": 0.0,\n \"exact_match_stderr,none\"\ : 0.0,\n \"prompt_level_loose_acc,none\": 0.2643253234750462,\n \"\ prompt_level_loose_acc_stderr,none\": 0.018976469193346637,\n \"acc_norm,none\"\ : 0.3613957711765469,\n \"acc_norm_stderr,none\": 0.005167160431579617,\n\ \ \"alias\": \"leaderboard\"\n },\n \"leaderboard_bbh\": {\n \ \ \"acc_norm,none\": 0.3784065266446797,\n \"acc_norm_stderr,none\": 0.005968335531782059,\n\ \ \"alias\": \" - leaderboard_bbh\"\n },\n \"leaderboard_bbh_boolean_expressions\"\ : {\n \"acc_norm,none\": 0.78,\n \"acc_norm_stderr,none\": 0.02625179282460579,\n\ \ \"alias\": \" - leaderboard_bbh_boolean_expressions\"\n },\n \"\ leaderboard_bbh_causal_judgement\": {\n \"acc_norm,none\": 0.5080213903743316,\n\ \ \"acc_norm_stderr,none\": 0.03665706061581772,\n \"alias\": \" \ \ - leaderboard_bbh_causal_judgement\"\n },\n \"leaderboard_bbh_date_understanding\"\ : {\n \"acc_norm,none\": 0.288,\n \"acc_norm_stderr,none\": 0.028697004587398253,\n\ \ \"alias\": \" - leaderboard_bbh_date_understanding\"\n },\n \"leaderboard_bbh_disambiguation_qa\"\ : {\n \"acc_norm,none\": 0.36,\n \"acc_norm_stderr,none\": 0.03041876402517494,\n\ \ \"alias\": \" - leaderboard_bbh_disambiguation_qa\"\n },\n \"leaderboard_bbh_formal_fallacies\"\ : {\n \"acc_norm,none\": 0.508,\n \"acc_norm_stderr,none\": 0.03168215643141386,\n\ \ \"alias\": \" - leaderboard_bbh_formal_fallacies\"\n },\n \"leaderboard_bbh_geometric_shapes\"\ : {\n \"acc_norm,none\": 0.14,\n \"acc_norm_stderr,none\": 0.021989409645240245,\n\ \ \"alias\": \" - leaderboard_bbh_geometric_shapes\"\n },\n \"leaderboard_bbh_hyperbaton\"\ : {\n \"acc_norm,none\": 0.58,\n \"acc_norm_stderr,none\": 0.03127799950463661,\n\ \ \"alias\": \" - leaderboard_bbh_hyperbaton\"\n },\n \"leaderboard_bbh_logical_deduction_five_objects\"\ : {\n \"acc_norm,none\": 0.236,\n \"acc_norm_stderr,none\": 0.026909337594953852,\n\ \ \"alias\": \" - leaderboard_bbh_logical_deduction_five_objects\"\n \ \ },\n \"leaderboard_bbh_logical_deduction_seven_objects\": {\n \"acc_norm,none\"\ : 0.2,\n \"acc_norm_stderr,none\": 0.02534897002097912,\n \"alias\"\ : \" - leaderboard_bbh_logical_deduction_seven_objects\"\n },\n \"leaderboard_bbh_logical_deduction_three_objects\"\ : {\n \"acc_norm,none\": 0.432,\n \"acc_norm_stderr,none\": 0.03139181076542942,\n\ \ \"alias\": \" - leaderboard_bbh_logical_deduction_three_objects\"\n \ \ },\n \"leaderboard_bbh_movie_recommendation\": {\n \"acc_norm,none\"\ : 0.424,\n \"acc_norm_stderr,none\": 0.03131803437491622,\n \"alias\"\ : \" - leaderboard_bbh_movie_recommendation\"\n },\n \"leaderboard_bbh_navigate\"\ : {\n \"acc_norm,none\": 0.532,\n \"acc_norm_stderr,none\": 0.031621252575725574,\n\ \ \"alias\": \" - leaderboard_bbh_navigate\"\n },\n \"leaderboard_bbh_object_counting\"\ : {\n \"acc_norm,none\": 0.228,\n \"acc_norm_stderr,none\": 0.026587432487268498,\n\ \ \"alias\": \" - leaderboard_bbh_object_counting\"\n },\n \"leaderboard_bbh_penguins_in_a_table\"\ : {\n \"acc_norm,none\": 0.3150684931506849,\n \"acc_norm_stderr,none\"\ : 0.03857820876541411,\n \"alias\": \" - leaderboard_bbh_penguins_in_a_table\"\ \n },\n \"leaderboard_bbh_reasoning_about_colored_objects\": {\n \"\ acc_norm,none\": 0.204,\n \"acc_norm_stderr,none\": 0.025537121574548162,\n\ \ \"alias\": \" - leaderboard_bbh_reasoning_about_colored_objects\"\n \ \ },\n \"leaderboard_bbh_ruin_names\": {\n \"acc_norm,none\": 0.54,\n\ \ \"acc_norm_stderr,none\": 0.031584653891499004,\n \"alias\": \"\ \ - leaderboard_bbh_ruin_names\"\n },\n \"leaderboard_bbh_salient_translation_error_detection\"\ : {\n \"acc_norm,none\": 0.272,\n \"acc_norm_stderr,none\": 0.028200088296309975,\n\ \ \"alias\": \" - leaderboard_bbh_salient_translation_error_detection\"\n\ \ },\n \"leaderboard_bbh_snarks\": {\n \"acc_norm,none\": 0.4606741573033708,\n\ \ \"acc_norm_stderr,none\": 0.03746587736387869,\n \"alias\": \" \ \ - leaderboard_bbh_snarks\"\n },\n \"leaderboard_bbh_sports_understanding\"\ : {\n \"acc_norm,none\": 0.664,\n \"acc_norm_stderr,none\": 0.029933259094191533,\n\ \ \"alias\": \" - leaderboard_bbh_sports_understanding\"\n },\n \"\ leaderboard_bbh_temporal_sequences\": {\n \"acc_norm,none\": 0.26,\n \ \ \"acc_norm_stderr,none\": 0.027797315752644335,\n \"alias\": \" - leaderboard_bbh_temporal_sequences\"\ \n },\n \"leaderboard_bbh_tracking_shuffled_objects_five_objects\": {\n \ \ \"acc_norm,none\": 0.18,\n \"acc_norm_stderr,none\": 0.02434689065029351,\n\ \ \"alias\": \" - leaderboard_bbh_tracking_shuffled_objects_five_objects\"\ \n },\n \"leaderboard_bbh_tracking_shuffled_objects_seven_objects\": {\n \ \ \"acc_norm,none\": 0.1,\n \"acc_norm_stderr,none\": 0.01901172751573434,\n\ \ \"alias\": \" - leaderboard_bbh_tracking_shuffled_objects_seven_objects\"\ \n },\n \"leaderboard_bbh_tracking_shuffled_objects_three_objects\": {\n \ \ \"acc_norm,none\": 0.368,\n \"acc_norm_stderr,none\": 0.03056207062099311,\n\ \ \"alias\": \" - leaderboard_bbh_tracking_shuffled_objects_three_objects\"\ \n },\n \"leaderboard_bbh_web_of_lies\": {\n \"acc_norm,none\": 0.532,\n\ \ \"acc_norm_stderr,none\": 0.031621252575725574,\n \"alias\": \"\ \ - leaderboard_bbh_web_of_lies\"\n },\n \"leaderboard_gpqa\": {\n \ \ \"acc_norm,none\": 0.2726510067114094,\n \"acc_norm_stderr,none\": 0.012909943366565096,\n\ \ \"alias\": \" - leaderboard_gpqa\"\n },\n \"leaderboard_gpqa_diamond\"\ : {\n \"acc_norm,none\": 0.2474747474747475,\n \"acc_norm_stderr,none\"\ : 0.030746300742124484,\n \"alias\": \" - leaderboard_gpqa_diamond\"\n \ \ },\n \"leaderboard_gpqa_extended\": {\n \"acc_norm,none\": 0.28205128205128205,\n\ \ \"acc_norm_stderr,none\": 0.019275803929950375,\n \"alias\": \"\ \ - leaderboard_gpqa_extended\"\n },\n \"leaderboard_gpqa_main\": {\n \ \ \"acc_norm,none\": 0.27232142857142855,\n \"acc_norm_stderr,none\"\ : 0.02105508212932411,\n \"alias\": \" - leaderboard_gpqa_main\"\n },\n\ \ \"leaderboard_ifeval\": {\n \"prompt_level_strict_acc,none\": 0.2476894639556377,\n\ \ \"prompt_level_strict_acc_stderr,none\": 0.0185761392851853,\n \"\ inst_level_strict_acc,none\": 0.34172661870503596,\n \"inst_level_strict_acc_stderr,none\"\ : \"N/A\",\n \"prompt_level_loose_acc,none\": 0.2643253234750462,\n \ \ \"prompt_level_loose_acc_stderr,none\": 0.018976469193346637,\n \"inst_level_loose_acc,none\"\ : 0.35611510791366907,\n \"inst_level_loose_acc_stderr,none\": \"N/A\",\n\ \ \"alias\": \" - leaderboard_ifeval\"\n },\n \"leaderboard_math_hard\"\ : {\n \"exact_match,none\": 0.0,\n \"exact_match_stderr,none\": 0.0,\n\ \ \"alias\": \" - leaderboard_math_hard\"\n },\n \"leaderboard_math_algebra_hard\"\ : {\n \"exact_match,none\": 0.0,\n \"exact_match_stderr,none\": 0.0,\n\ \ \"alias\": \" - leaderboard_math_algebra_hard\"\n },\n \"leaderboard_math_counting_and_prob_hard\"\ : {\n \"exact_match,none\": 0.0,\n \"exact_match_stderr,none\": 0.0,\n\ \ \"alias\": \" - leaderboard_math_counting_and_prob_hard\"\n },\n \ \ \"leaderboard_math_geometry_hard\": {\n \"exact_match,none\": 0.0,\n \ \ \"exact_match_stderr,none\": 0.0,\n \"alias\": \" - leaderboard_math_geometry_hard\"\ \n },\n \"leaderboard_math_intermediate_algebra_hard\": {\n \"exact_match,none\"\ : 0.0,\n \"exact_match_stderr,none\": 0.0,\n \"alias\": \" - leaderboard_math_intermediate_algebra_hard\"\ \n },\n \"leaderboard_math_num_theory_hard\": {\n \"exact_match,none\"\ : 0.0,\n \"exact_match_stderr,none\": 0.0,\n \"alias\": \" - leaderboard_math_num_theory_hard\"\ \n },\n \"leaderboard_math_prealgebra_hard\": {\n \"exact_match,none\"\ : 0.0,\n \"exact_match_stderr,none\": 0.0,\n \"alias\": \" - leaderboard_math_prealgebra_hard\"\ \n },\n \"leaderboard_math_precalculus_hard\": {\n \"exact_match,none\"\ : 0.0,\n \"exact_match_stderr,none\": 0.0,\n \"alias\": \" - leaderboard_math_precalculus_hard\"\ \n },\n \"leaderboard_mmlu_pro\": {\n \"acc,none\": 0.19822140957446807,\n\ \ \"acc_stderr,none\": 0.0036345583399346364,\n \"alias\": \" - leaderboard_mmlu_pro\"\ \n },\n \"leaderboard_musr\": {\n \"acc_norm,none\": 0.3716931216931217,\n\ \ \"acc_norm_stderr,none\": 0.017128776450158697,\n \"alias\": \"\ \ - leaderboard_musr\"\n },\n \"leaderboard_musr_murder_mysteries\": {\n \ \ \"acc_norm,none\": 0.516,\n \"acc_norm_stderr,none\": 0.03166998503010743,\n\ \ \"alias\": \" - leaderboard_musr_murder_mysteries\"\n },\n \"leaderboard_musr_object_placements\"\ : {\n \"acc_norm,none\": 0.2421875,\n \"acc_norm_stderr,none\": 0.026827898476066977,\n\ \ \"alias\": \" - leaderboard_musr_object_placements\"\n },\n \"leaderboard_musr_team_allocation\"\ : {\n \"acc_norm,none\": 0.36,\n \"acc_norm_stderr,none\": 0.03041876402517494,\n\ \ \"alias\": \" - leaderboard_musr_team_allocation\"\n }\n}\n```" repo_url: https://huggingface.co/nbeerbower/gemma2-gutenberg-27B leaderboard_url: '' point_of_contact: '' configs: - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_boolean_expressions data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_boolean_expressions_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_boolean_expressions_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_causal_judgement data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_causal_judgement_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_causal_judgement_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_date_understanding data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_date_understanding_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_date_understanding_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_disambiguation_qa data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_disambiguation_qa_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_disambiguation_qa_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_formal_fallacies data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_formal_fallacies_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_formal_fallacies_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_geometric_shapes data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_geometric_shapes_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_geometric_shapes_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_hyperbaton data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_hyperbaton_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_hyperbaton_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_logical_deduction_five_objects data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_logical_deduction_five_objects_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_logical_deduction_five_objects_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_logical_deduction_seven_objects data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_logical_deduction_seven_objects_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_logical_deduction_seven_objects_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_logical_deduction_three_objects data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_logical_deduction_three_objects_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_logical_deduction_three_objects_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_movie_recommendation data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_movie_recommendation_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_movie_recommendation_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_navigate data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_navigate_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_navigate_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_object_counting data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_object_counting_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_object_counting_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_penguins_in_a_table data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_penguins_in_a_table_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_penguins_in_a_table_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_reasoning_about_colored_objects data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_reasoning_about_colored_objects_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_reasoning_about_colored_objects_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_ruin_names data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_ruin_names_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_ruin_names_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_salient_translation_error_detection data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_salient_translation_error_detection_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_salient_translation_error_detection_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_snarks data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_snarks_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_snarks_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_sports_understanding data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_sports_understanding_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_sports_understanding_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_temporal_sequences data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_temporal_sequences_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_temporal_sequences_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_tracking_shuffled_objects_five_objects data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_tracking_shuffled_objects_five_objects_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_tracking_shuffled_objects_five_objects_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_tracking_shuffled_objects_seven_objects data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_tracking_shuffled_objects_seven_objects_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_tracking_shuffled_objects_seven_objects_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_tracking_shuffled_objects_three_objects data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_tracking_shuffled_objects_three_objects_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_tracking_shuffled_objects_three_objects_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_web_of_lies data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_bbh_web_of_lies_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_bbh_web_of_lies_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_gpqa_diamond data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_gpqa_diamond_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_gpqa_diamond_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_gpqa_extended data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_gpqa_extended_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_gpqa_extended_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_gpqa_main data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_gpqa_main_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_gpqa_main_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_ifeval data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_ifeval_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_ifeval_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_math_algebra_hard data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_math_algebra_hard_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_math_algebra_hard_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_math_counting_and_prob_hard data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_math_counting_and_prob_hard_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_math_counting_and_prob_hard_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_math_geometry_hard data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_math_geometry_hard_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_math_geometry_hard_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_math_intermediate_algebra_hard data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_math_intermediate_algebra_hard_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_math_intermediate_algebra_hard_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_math_num_theory_hard data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_math_num_theory_hard_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_math_num_theory_hard_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_math_prealgebra_hard data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_math_prealgebra_hard_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_math_prealgebra_hard_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_math_precalculus_hard data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_math_precalculus_hard_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_math_precalculus_hard_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_mmlu_pro data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_mmlu_pro_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_mmlu_pro_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_musr_murder_mysteries data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_musr_murder_mysteries_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_musr_murder_mysteries_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_musr_object_placements data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_musr_object_placements_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_musr_object_placements_2024-09-30T00-44-40.185741.jsonl' - config_name: nbeerbower__gemma2-gutenberg-27B__leaderboard_musr_team_allocation data_files: - split: 2024_09_30T00_44_40.185741 path: - '**/samples_leaderboard_musr_team_allocation_2024-09-30T00-44-40.185741.jsonl' - split: latest path: - '**/samples_leaderboard_musr_team_allocation_2024-09-30T00-44-40.185741.jsonl' --- # Dataset Card for Evaluation run of nbeerbower/gemma2-gutenberg-27B <!-- Provide a quick summary of the dataset. --> Dataset automatically created during the evaluation run of model [nbeerbower/gemma2-gutenberg-27B](https://huggingface.co/nbeerbower/gemma2-gutenberg-27B) The dataset is composed of 38 configuration(s), each one corresponding 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. 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/nbeerbower__gemma2-gutenberg-27B-details", name="nbeerbower__gemma2-gutenberg-27B__leaderboard_bbh_boolean_expressions", split="latest" ) ``` ## Latest results These are the [latest results from run 2024-09-30T00-44-40.185741](https://huggingface.co/datasets/open-llm-leaderboard/nbeerbower__gemma2-gutenberg-27B-details/blob/main/nbeerbower__gemma2-gutenberg-27B/results_2024-09-30T00-44-40.185741.json) (note that there 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": { "leaderboard": { "inst_level_strict_acc,none": 0.34172661870503596, "inst_level_strict_acc_stderr,none": "N/A", "inst_level_loose_acc,none": 0.35611510791366907, "inst_level_loose_acc_stderr,none": "N/A", "acc,none": 0.19822140957446807, "acc_stderr,none": 0.0036345583399346364, "prompt_level_strict_acc,none": 0.2476894639556377, "prompt_level_strict_acc_stderr,none": 0.0185761392851853, "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "prompt_level_loose_acc,none": 0.2643253234750462, "prompt_level_loose_acc_stderr,none": 0.018976469193346637, "acc_norm,none": 0.3613957711765469, "acc_norm_stderr,none": 0.005167160431579617, "alias": "leaderboard" }, "leaderboard_bbh": { "acc_norm,none": 0.3784065266446797, "acc_norm_stderr,none": 0.005968335531782059, "alias": " - leaderboard_bbh" }, "leaderboard_bbh_boolean_expressions": { "acc_norm,none": 0.78, "acc_norm_stderr,none": 0.02625179282460579, "alias": " - leaderboard_bbh_boolean_expressions" }, "leaderboard_bbh_causal_judgement": { "acc_norm,none": 0.5080213903743316, "acc_norm_stderr,none": 0.03665706061581772, "alias": " - leaderboard_bbh_causal_judgement" }, "leaderboard_bbh_date_understanding": { "acc_norm,none": 0.288, "acc_norm_stderr,none": 0.028697004587398253, "alias": " - leaderboard_bbh_date_understanding" }, "leaderboard_bbh_disambiguation_qa": { "acc_norm,none": 0.36, "acc_norm_stderr,none": 0.03041876402517494, "alias": " - leaderboard_bbh_disambiguation_qa" }, "leaderboard_bbh_formal_fallacies": { "acc_norm,none": 0.508, "acc_norm_stderr,none": 0.03168215643141386, "alias": " - leaderboard_bbh_formal_fallacies" }, "leaderboard_bbh_geometric_shapes": { "acc_norm,none": 0.14, "acc_norm_stderr,none": 0.021989409645240245, "alias": " - leaderboard_bbh_geometric_shapes" }, "leaderboard_bbh_hyperbaton": { "acc_norm,none": 0.58, "acc_norm_stderr,none": 0.03127799950463661, "alias": " - leaderboard_bbh_hyperbaton" }, "leaderboard_bbh_logical_deduction_five_objects": { "acc_norm,none": 0.236, "acc_norm_stderr,none": 0.026909337594953852, "alias": " - leaderboard_bbh_logical_deduction_five_objects" }, "leaderboard_bbh_logical_deduction_seven_objects": { "acc_norm,none": 0.2, "acc_norm_stderr,none": 0.02534897002097912, "alias": " - leaderboard_bbh_logical_deduction_seven_objects" }, "leaderboard_bbh_logical_deduction_three_objects": { "acc_norm,none": 0.432, "acc_norm_stderr,none": 0.03139181076542942, "alias": " - leaderboard_bbh_logical_deduction_three_objects" }, "leaderboard_bbh_movie_recommendation": { "acc_norm,none": 0.424, "acc_norm_stderr,none": 0.03131803437491622, "alias": " - leaderboard_bbh_movie_recommendation" }, "leaderboard_bbh_navigate": { "acc_norm,none": 0.532, "acc_norm_stderr,none": 0.031621252575725574, "alias": " - leaderboard_bbh_navigate" }, "leaderboard_bbh_object_counting": { "acc_norm,none": 0.228, "acc_norm_stderr,none": 0.026587432487268498, "alias": " - leaderboard_bbh_object_counting" }, "leaderboard_bbh_penguins_in_a_table": { "acc_norm,none": 0.3150684931506849, "acc_norm_stderr,none": 0.03857820876541411, "alias": " - leaderboard_bbh_penguins_in_a_table" }, "leaderboard_bbh_reasoning_about_colored_objects": { "acc_norm,none": 0.204, "acc_norm_stderr,none": 0.025537121574548162, "alias": " - leaderboard_bbh_reasoning_about_colored_objects" }, "leaderboard_bbh_ruin_names": { "acc_norm,none": 0.54, "acc_norm_stderr,none": 0.031584653891499004, "alias": " - leaderboard_bbh_ruin_names" }, "leaderboard_bbh_salient_translation_error_detection": { "acc_norm,none": 0.272, "acc_norm_stderr,none": 0.028200088296309975, "alias": " - leaderboard_bbh_salient_translation_error_detection" }, "leaderboard_bbh_snarks": { "acc_norm,none": 0.4606741573033708, "acc_norm_stderr,none": 0.03746587736387869, "alias": " - leaderboard_bbh_snarks" }, "leaderboard_bbh_sports_understanding": { "acc_norm,none": 0.664, "acc_norm_stderr,none": 0.029933259094191533, "alias": " - leaderboard_bbh_sports_understanding" }, "leaderboard_bbh_temporal_sequences": { "acc_norm,none": 0.26, "acc_norm_stderr,none": 0.027797315752644335, "alias": " - leaderboard_bbh_temporal_sequences" }, "leaderboard_bbh_tracking_shuffled_objects_five_objects": { "acc_norm,none": 0.18, "acc_norm_stderr,none": 0.02434689065029351, "alias": " - leaderboard_bbh_tracking_shuffled_objects_five_objects" }, "leaderboard_bbh_tracking_shuffled_objects_seven_objects": { "acc_norm,none": 0.1, "acc_norm_stderr,none": 0.01901172751573434, "alias": " - leaderboard_bbh_tracking_shuffled_objects_seven_objects" }, "leaderboard_bbh_tracking_shuffled_objects_three_objects": { "acc_norm,none": 0.368, "acc_norm_stderr,none": 0.03056207062099311, "alias": " - leaderboard_bbh_tracking_shuffled_objects_three_objects" }, "leaderboard_bbh_web_of_lies": { "acc_norm,none": 0.532, "acc_norm_stderr,none": 0.031621252575725574, "alias": " - leaderboard_bbh_web_of_lies" }, "leaderboard_gpqa": { "acc_norm,none": 0.2726510067114094, "acc_norm_stderr,none": 0.012909943366565096, "alias": " - leaderboard_gpqa" }, "leaderboard_gpqa_diamond": { "acc_norm,none": 0.2474747474747475, "acc_norm_stderr,none": 0.030746300742124484, "alias": " - leaderboard_gpqa_diamond" }, "leaderboard_gpqa_extended": { "acc_norm,none": 0.28205128205128205, "acc_norm_stderr,none": 0.019275803929950375, "alias": " - leaderboard_gpqa_extended" }, "leaderboard_gpqa_main": { "acc_norm,none": 0.27232142857142855, "acc_norm_stderr,none": 0.02105508212932411, "alias": " - leaderboard_gpqa_main" }, "leaderboard_ifeval": { "prompt_level_strict_acc,none": 0.2476894639556377, "prompt_level_strict_acc_stderr,none": 0.0185761392851853, "inst_level_strict_acc,none": 0.34172661870503596, "inst_level_strict_acc_stderr,none": "N/A", "prompt_level_loose_acc,none": 0.2643253234750462, "prompt_level_loose_acc_stderr,none": 0.018976469193346637, "inst_level_loose_acc,none": 0.35611510791366907, "inst_level_loose_acc_stderr,none": "N/A", "alias": " - leaderboard_ifeval" }, "leaderboard_math_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_hard" }, "leaderboard_math_algebra_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_algebra_hard" }, "leaderboard_math_counting_and_prob_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_counting_and_prob_hard" }, "leaderboard_math_geometry_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_geometry_hard" }, "leaderboard_math_intermediate_algebra_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_intermediate_algebra_hard" }, "leaderboard_math_num_theory_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_num_theory_hard" }, "leaderboard_math_prealgebra_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_prealgebra_hard" }, "leaderboard_math_precalculus_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_precalculus_hard" }, "leaderboard_mmlu_pro": { "acc,none": 0.19822140957446807, "acc_stderr,none": 0.0036345583399346364, "alias": " - leaderboard_mmlu_pro" }, "leaderboard_musr": { "acc_norm,none": 0.3716931216931217, "acc_norm_stderr,none": 0.017128776450158697, "alias": " - leaderboard_musr" }, "leaderboard_musr_murder_mysteries": { "acc_norm,none": 0.516, "acc_norm_stderr,none": 0.03166998503010743, "alias": " - leaderboard_musr_murder_mysteries" }, "leaderboard_musr_object_placements": { "acc_norm,none": 0.2421875, "acc_norm_stderr,none": 0.026827898476066977, "alias": " - leaderboard_musr_object_placements" }, "leaderboard_musr_team_allocation": { "acc_norm,none": 0.36, "acc_norm_stderr,none": 0.03041876402517494, "alias": " - leaderboard_musr_team_allocation" } }, "leaderboard": { "inst_level_strict_acc,none": 0.34172661870503596, "inst_level_strict_acc_stderr,none": "N/A", "inst_level_loose_acc,none": 0.35611510791366907, "inst_level_loose_acc_stderr,none": "N/A", "acc,none": 0.19822140957446807, "acc_stderr,none": 0.0036345583399346364, "prompt_level_strict_acc,none": 0.2476894639556377, "prompt_level_strict_acc_stderr,none": 0.0185761392851853, "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "prompt_level_loose_acc,none": 0.2643253234750462, "prompt_level_loose_acc_stderr,none": 0.018976469193346637, "acc_norm,none": 0.3613957711765469, "acc_norm_stderr,none": 0.005167160431579617, "alias": "leaderboard" }, "leaderboard_bbh": { "acc_norm,none": 0.3784065266446797, "acc_norm_stderr,none": 0.005968335531782059, "alias": " - leaderboard_bbh" }, "leaderboard_bbh_boolean_expressions": { "acc_norm,none": 0.78, "acc_norm_stderr,none": 0.02625179282460579, "alias": " - leaderboard_bbh_boolean_expressions" }, "leaderboard_bbh_causal_judgement": { "acc_norm,none": 0.5080213903743316, "acc_norm_stderr,none": 0.03665706061581772, "alias": " - leaderboard_bbh_causal_judgement" }, "leaderboard_bbh_date_understanding": { "acc_norm,none": 0.288, "acc_norm_stderr,none": 0.028697004587398253, "alias": " - leaderboard_bbh_date_understanding" }, "leaderboard_bbh_disambiguation_qa": { "acc_norm,none": 0.36, "acc_norm_stderr,none": 0.03041876402517494, "alias": " - leaderboard_bbh_disambiguation_qa" }, "leaderboard_bbh_formal_fallacies": { "acc_norm,none": 0.508, "acc_norm_stderr,none": 0.03168215643141386, "alias": " - leaderboard_bbh_formal_fallacies" }, "leaderboard_bbh_geometric_shapes": { "acc_norm,none": 0.14, "acc_norm_stderr,none": 0.021989409645240245, "alias": " - leaderboard_bbh_geometric_shapes" }, "leaderboard_bbh_hyperbaton": { "acc_norm,none": 0.58, "acc_norm_stderr,none": 0.03127799950463661, "alias": " - leaderboard_bbh_hyperbaton" }, "leaderboard_bbh_logical_deduction_five_objects": { "acc_norm,none": 0.236, "acc_norm_stderr,none": 0.026909337594953852, "alias": " - leaderboard_bbh_logical_deduction_five_objects" }, "leaderboard_bbh_logical_deduction_seven_objects": { "acc_norm,none": 0.2, "acc_norm_stderr,none": 0.02534897002097912, "alias": " - leaderboard_bbh_logical_deduction_seven_objects" }, "leaderboard_bbh_logical_deduction_three_objects": { "acc_norm,none": 0.432, "acc_norm_stderr,none": 0.03139181076542942, "alias": " - leaderboard_bbh_logical_deduction_three_objects" }, "leaderboard_bbh_movie_recommendation": { "acc_norm,none": 0.424, "acc_norm_stderr,none": 0.03131803437491622, "alias": " - leaderboard_bbh_movie_recommendation" }, "leaderboard_bbh_navigate": { "acc_norm,none": 0.532, "acc_norm_stderr,none": 0.031621252575725574, "alias": " - leaderboard_bbh_navigate" }, "leaderboard_bbh_object_counting": { "acc_norm,none": 0.228, "acc_norm_stderr,none": 0.026587432487268498, "alias": " - leaderboard_bbh_object_counting" }, "leaderboard_bbh_penguins_in_a_table": { "acc_norm,none": 0.3150684931506849, "acc_norm_stderr,none": 0.03857820876541411, "alias": " - leaderboard_bbh_penguins_in_a_table" }, "leaderboard_bbh_reasoning_about_colored_objects": { "acc_norm,none": 0.204, "acc_norm_stderr,none": 0.025537121574548162, "alias": " - leaderboard_bbh_reasoning_about_colored_objects" }, "leaderboard_bbh_ruin_names": { "acc_norm,none": 0.54, "acc_norm_stderr,none": 0.031584653891499004, "alias": " - leaderboard_bbh_ruin_names" }, "leaderboard_bbh_salient_translation_error_detection": { "acc_norm,none": 0.272, "acc_norm_stderr,none": 0.028200088296309975, "alias": " - leaderboard_bbh_salient_translation_error_detection" }, "leaderboard_bbh_snarks": { "acc_norm,none": 0.4606741573033708, "acc_norm_stderr,none": 0.03746587736387869, "alias": " - leaderboard_bbh_snarks" }, "leaderboard_bbh_sports_understanding": { "acc_norm,none": 0.664, "acc_norm_stderr,none": 0.029933259094191533, "alias": " - leaderboard_bbh_sports_understanding" }, "leaderboard_bbh_temporal_sequences": { "acc_norm,none": 0.26, "acc_norm_stderr,none": 0.027797315752644335, "alias": " - leaderboard_bbh_temporal_sequences" }, "leaderboard_bbh_tracking_shuffled_objects_five_objects": { "acc_norm,none": 0.18, "acc_norm_stderr,none": 0.02434689065029351, "alias": " - leaderboard_bbh_tracking_shuffled_objects_five_objects" }, "leaderboard_bbh_tracking_shuffled_objects_seven_objects": { "acc_norm,none": 0.1, "acc_norm_stderr,none": 0.01901172751573434, "alias": " - leaderboard_bbh_tracking_shuffled_objects_seven_objects" }, "leaderboard_bbh_tracking_shuffled_objects_three_objects": { "acc_norm,none": 0.368, "acc_norm_stderr,none": 0.03056207062099311, "alias": " - leaderboard_bbh_tracking_shuffled_objects_three_objects" }, "leaderboard_bbh_web_of_lies": { "acc_norm,none": 0.532, "acc_norm_stderr,none": 0.031621252575725574, "alias": " - leaderboard_bbh_web_of_lies" }, "leaderboard_gpqa": { "acc_norm,none": 0.2726510067114094, "acc_norm_stderr,none": 0.012909943366565096, "alias": " - leaderboard_gpqa" }, "leaderboard_gpqa_diamond": { "acc_norm,none": 0.2474747474747475, "acc_norm_stderr,none": 0.030746300742124484, "alias": " - leaderboard_gpqa_diamond" }, "leaderboard_gpqa_extended": { "acc_norm,none": 0.28205128205128205, "acc_norm_stderr,none": 0.019275803929950375, "alias": " - leaderboard_gpqa_extended" }, "leaderboard_gpqa_main": { "acc_norm,none": 0.27232142857142855, "acc_norm_stderr,none": 0.02105508212932411, "alias": " - leaderboard_gpqa_main" }, "leaderboard_ifeval": { "prompt_level_strict_acc,none": 0.2476894639556377, "prompt_level_strict_acc_stderr,none": 0.0185761392851853, "inst_level_strict_acc,none": 0.34172661870503596, "inst_level_strict_acc_stderr,none": "N/A", "prompt_level_loose_acc,none": 0.2643253234750462, "prompt_level_loose_acc_stderr,none": 0.018976469193346637, "inst_level_loose_acc,none": 0.35611510791366907, "inst_level_loose_acc_stderr,none": "N/A", "alias": " - leaderboard_ifeval" }, "leaderboard_math_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_hard" }, "leaderboard_math_algebra_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_algebra_hard" }, "leaderboard_math_counting_and_prob_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_counting_and_prob_hard" }, "leaderboard_math_geometry_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_geometry_hard" }, "leaderboard_math_intermediate_algebra_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_intermediate_algebra_hard" }, "leaderboard_math_num_theory_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_num_theory_hard" }, "leaderboard_math_prealgebra_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_prealgebra_hard" }, "leaderboard_math_precalculus_hard": { "exact_match,none": 0.0, "exact_match_stderr,none": 0.0, "alias": " - leaderboard_math_precalculus_hard" }, "leaderboard_mmlu_pro": { "acc,none": 0.19822140957446807, "acc_stderr,none": 0.0036345583399346364, "alias": " - leaderboard_mmlu_pro" }, "leaderboard_musr": { "acc_norm,none": 0.3716931216931217, "acc_norm_stderr,none": 0.017128776450158697, "alias": " - leaderboard_musr" }, "leaderboard_musr_murder_mysteries": { "acc_norm,none": 0.516, "acc_norm_stderr,none": 0.03166998503010743, "alias": " - leaderboard_musr_murder_mysteries" }, "leaderboard_musr_object_placements": { "acc_norm,none": 0.2421875, "acc_norm_stderr,none": 0.026827898476066977, "alias": " - leaderboard_musr_object_placements" }, "leaderboard_musr_team_allocation": { "acc_norm,none": 0.36, "acc_norm_stderr,none": 0.03041876402517494, "alias": " - leaderboard_musr_team_allocation" } } ``` ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - 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If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. 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maniro-ai/test

maniro-ai

--- dataset_info: features: - name: observation.state sequence: float32 length: 8 - name: action sequence: float32 length: 8 - name: episode_index dtype: int64 - name: frame_index dtype: int64 - name: timestamp dtype: float32 - name: observation.images.cameras.raw.wrist_1 dtype: video_frame - name: observation.images.cameras.raw.wrist_2 dtype: video_frame - name: observation.images.cameras.raw.scene_table dtype: video_frame - name: index dtype: int64 splits: - name: train num_bytes: 5318040 num_examples: 17045 download_size: 1558455 dataset_size: 5318040 configs: - config_name: default data_files: - split: train path: data/train-* ---

saeed11b95/Transaction-Data

saeed11b95

--- dataset_info: config_name: all features: - name: client_id dtype: int32 - name: bank_id dtype: int32 - name: account_id dtype: int32 - name: txn_id dtype: int32 - name: txn_date dtype: string - name: description dtype: string - name: amount dtype: float32 - name: category dtype: string - name: day_of_week dtype: int32 - name: day_of_month dtype: int32 - name: month dtype: int32 - name: amount_mean dtype: float32 - name: amount_std dtype: float32 - name: IS_INTERESTED_INVESTMENT dtype: bool - name: IS_INTERESTED_BUILD_CREDIT dtype: bool - name: IS_INTERESTED_INCREASE_INCOME dtype: bool - name: IS_INTERESTED_PAY_OFF_DEBT dtype: bool - name: IS_INTERESTED_MANAGE_SPENDING dtype: bool - name: IS_INTERESTED_GROW_SAVINGS dtype: bool splits: - name: train num_bytes: 28118167 num_examples: 222816 download_size: 7223715 dataset_size: 28118167 configs: - config_name: all data_files: - split: train path: all/train-* ---

SCX163/voxdialogue

SCX163

--- license: apache-2.0 ---

1231czx/gemma2_9b_it_prm_math_base_N30

1231czx

--- dataset_info: features: - name: idx dtype: int64 - name: gt dtype: string - name: my_solu sequence: string splits: - name: train num_bytes: 333703719 num_examples: 232500 download_size: 148834398 dataset_size: 333703719 configs: - config_name: default data_files: - split: train path: data/train-* ---

ZixuanKe/business_unsup

ZixuanKe

--- dataset_info: features: - name: text dtype: string - name: topic dtype: string - name: title dtype: string - name: llama3_input_ids sequence: int64 - name: llama3_attention_mask sequence: int64 - name: llama3_special_tokens_mask sequence: int64 - name: subset dtype: int64 splits: - name: train num_bytes: 5406149641 num_examples: 24444 download_size: 776153265 dataset_size: 5406149641 configs: - config_name: default data_files: - split: train path: data/train-* ---

1231czx/gemma2_9b_it_prm_gsm8k_base

1231czx

--- dataset_info: features: - name: idx dtype: int64 - name: gt dtype: string - name: my_solu sequence: string splits: - name: train num_bytes: 168777780 num_examples: 186825 download_size: 68571467 dataset_size: 168777780 configs: - config_name: default data_files: - split: train path: data/train-* ---

rrojin/025

rrojin

--- dataset_info: - config_name: 영한 features: - name: sn dtype: string - name: data_set dtype: string - name: domain dtype: string - name: subdomain dtype: string - name: en_original dtype: string - name: en dtype: string - name: mt dtype: string - name: ko dtype: string - name: source_language dtype: string - name: target_language dtype: string - name: word_count_ko dtype: float64 - name: word_count_en dtype: float64 - name: word_ratio dtype: float64 - name: file_name dtype: string - name: source dtype: string - name: license dtype: string - name: style dtype: string - name: included_unknown_words dtype: bool - name: ner struct: - name: tags list: - name: position dtype: string - name: tag dtype: string - name: value dtype: string - name: text dtype: string splits: - name: train num_bytes: 388563073 num_examples: 810207 - name: validation num_bytes: 129536980 num_examples: 270069 - name: test num_bytes: 128158121 num_examples: 270069 download_size: 233204318 dataset_size: 646258174 - config_name: 한영 features: - name: sn dtype: string - name: data_set dtype: string - name: domain dtype: string - name: subdomain dtype: string - name: ko_original dtype: string - name: en dtype: string - name: mt dtype: string - name: ko dtype: string - name: source_language dtype: string - name: target_language dtype: string - name: word_count_ko dtype: int64 - name: word_count_en dtype: int64 - name: word_ratio dtype: float64 - name: file_name dtype: string - name: source dtype: string - name: license dtype: string - name: style dtype: string - name: included_unknown_words dtype: bool - name: ner struct: - name: tags list: - name: position dtype: string - name: tag dtype: string - name: value dtype: string - name: text dtype: string splits: - name: train num_bytes: 364665575 num_examples: 810000 - name: validation num_bytes: 121669296 num_examples: 270000 - name: test num_bytes: 121530762 num_examples: 270000 download_size: 264744792 dataset_size: 607865633 configs: - config_name: 영한 data_files: - split: train path: 영한/train-* - split: validation path: 영한/validation-* - split: test path: 영한/test-* - config_name: 한영 data_files: - split: train path: 한영/train-* - split: validation path: 한영/validation-* - split: test path: 한영/test-* ---

varietysum/livecodebench

varietysum

--- dataset_info: features: - name: question_title dtype: string - name: question_content dtype: string - name: platform dtype: string - name: question_id dtype: string - name: contest_id dtype: string - name: contest_date dtype: string - name: starter_code dtype: string - name: difficulty dtype: string - name: public_test_cases dtype: string - name: private_test_cases dtype: string - name: metadata dtype: string splits: - name: train num_bytes: 2589168257 num_examples: 612 download_size: 2513271341 dataset_size: 2589168257 configs: - config_name: default data_files: - split: train path: data/train-* ---

klcsp/closedqa-eval

klcsp

--- dataset_info: features: - name: instructions dtype: string - name: target_responses dtype: string - name: candidate_responses dtype: string - name: model_id dtype: string - name: model_sha dtype: string - name: eval_prompts dtype: string - name: similarity_scores dtype: float64 - name: precision_scores dtype: float64 - name: evaluators dtype: string - name: dates dtype: string splits: - name: gemma7b_k num_bytes: 327778 num_examples: 60 download_size: 84260 dataset_size: 327778 configs: - config_name: default data_files: - split: gemma7b_k path: data/gemma7b_k-* ---

astroyat/so_test

astroyat

--- task_categories: - robotics tags: - LeRobot - tutorial --- This dataset was created using [🤗 LeRobot](https://github.com/huggingface/lerobot).

ZixuanKe/accounting_unsup

ZixuanKe

--- dataset_info: features: - name: text dtype: string - name: topic dtype: string - name: title dtype: string - name: llama3_input_ids sequence: int64 - name: llama3_attention_mask sequence: int64 - name: llama3_special_tokens_mask sequence: int64 - name: subset dtype: int64 splits: - name: train num_bytes: 3154624654 num_examples: 14215 download_size: 388877429 dataset_size: 3154624654 configs: - config_name: default data_files: - split: train path: data/train-* ---

klcsp/coding-eval

klcsp

--- dataset_info: features: - name: instructions dtype: string - name: target_responses dtype: string - name: candidate_responses dtype: string - name: model_id dtype: string - name: model_sha dtype: string - name: eval_prompts dtype: string - name: similarity_scores dtype: float64 - name: precision_scores dtype: float64 - name: evaluators dtype: string - name: dates dtype: string splits: - name: gemma7b_k num_bytes: 348228 num_examples: 64 download_size: 123960 dataset_size: 348228 configs: - config_name: default data_files: - split: gemma7b_k path: data/gemma7b_k-* ---

klcsp/classification-eval

klcsp

--- dataset_info: features: - name: instructions dtype: string - name: target_responses dtype: string - name: candidate_responses dtype: string - name: model_id dtype: string - name: model_sha dtype: string - name: eval_prompts dtype: string - name: similarity_scores dtype: float64 - name: precision_scores dtype: float64 - name: evaluators dtype: string - name: dates dtype: string splits: - name: gemma7b_k num_bytes: 237748 num_examples: 64 download_size: 56374 dataset_size: 237748 configs: - config_name: default data_files: - split: gemma7b_k path: data/gemma7b_k-* ---

jinzzang23/Busan_Meter_info

jinzzang23

--- dataset_info: features: - name: 연번 dtype: int64 - name: 다량관리년도 dtype: int64 - name: 고객번호 dtype: string - name: 사업소코드 dtype: int64 - name: 사업소명 dtype: string - name: 구코드 dtype: int64 - name: 구명 dtype: string - name: 동코드 dtype: int64 - name: 동명 dtype: string - name: 상수도업종 dtype: string - name: 가구수 dtype: float64 - name: 구경(mm) dtype: int64 - name: 사용월수 dtype: int64 - name: 사용량 dtype: int64 - name: 평균사용량 dtype: int64 - name: 총사용금액 dtype: int64 - name: 월평균사용금액 dtype: int64 - name: 구분 dtype: string - name: response_msg dtype: string splits: - name: train num_bytes: 1857646 num_examples: 3951 download_size: 414885 dataset_size: 1857646 configs: - config_name: default data_files: - split: train path: data/train-* ---

josedonoso/ecg-khan-rotated-2

josedonoso

--- dataset_info: features: - name: image dtype: image - name: conclusion dtype: string splits: - name: train num_bytes: 188143183.0 num_examples: 738 - name: test num_bytes: 47463028.0 num_examples: 187 download_size: 227024508 dataset_size: 235606211.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

ycfNTU/masum_oneshot_loop

ycfNTU

--- dataset_info: features: - name: document dtype: string - name: aspect dtype: string - name: summary dtype: string - name: top_sentences_words1 dtype: string - name: summary1 dtype: string - name: random_index dtype: int64 splits: - name: train num_bytes: 24961023 num_examples: 2000 download_size: 13831915 dataset_size: 24961023 configs: - config_name: default data_files: - split: train path: data/train-* ---