README.md

metadata

dataset_info:
  features:
    - name: id
      dtype: string
    - name: type
      dtype: string
    - name: source_type
      dtype: string
    - name: source
      dtype: string
    - name: question
      dtype: string
    - name: option1
      dtype: string
    - name: option2
      dtype: string
    - name: option3
      dtype: string
    - name: option4
      dtype: string
    - name: image_1
      dtype: image
    - name: image_2
      dtype: image
    - name: image_3
      dtype: image
    - name: image_4
      dtype: image
    - name: image_5
      dtype: image
    - name: answer
      dtype: string
    - name: analysis
      dtype: string
    - name: distribution
      dtype: string
    - name: difficulty_level
      dtype: string
    - name: subcategory
      dtype: string
    - name: category
      dtype: string
    - name: subfield
      dtype: string
    - name: img_type
      dtype: string
    - name: image_1_filename
      dtype: string
    - name: image_2_filename
      dtype: string
    - name: image_3_filename
      dtype: string
    - name: image_4_filename
      dtype: string
    - name: image_5_filename
      dtype: string
  splits:
    - name: dev
      num_bytes: 13180933
      num_examples: 112
    - name: val
      num_bytes: 95817884
      num_examples: 900
    - name: test
      num_bytes: 3146080167
      num_examples: 11000
  download_size: 1297435382
  dataset_size: 3255078984
configs:
  - config_name: default
    data_files:
      - split: dev
        path: data/dev-*
      - split: val
        path: data/val-*
      - split: test
        path: data/test-*

Large-scale Multi-modality Models Evaluation Suite

Accelerating the development of large-scale multi-modality models (LMMs) with lmms-eval

🏠 Homepage | 📚 Documentation | 🤗 Huggingface Datasets

This Dataset

This is a formatted version of CMMMU. It is used in our lmms-eval pipeline to allow for one-click evaluations of large multi-modality models.

@article{zhang2024cmmmu,
        title={CMMMU: A Chinese Massive Multi-discipline Multimodal Understanding Benchmark},
        author={Ge, Zhang and Xinrun, Du and Bei, Chen and Yiming, Liang and Tongxu, Luo and Tianyu, Zheng and Kang, Zhu and Yuyang, Cheng and Chunpu, Xu and Shuyue, Guo and Haoran, Zhang and Xingwei, Qu and Junjie, Wang and Ruibin, Yuan and Yizhi, Li and Zekun, Wang and Yudong, Liu and Yu-Hsuan, Tsai and Fengji, Zhang and Chenghua, Lin and Wenhao, Huang and Wenhu, Chen and Jie, Fu},
        journal={arXiv preprint arXiv:2401.20847},
        year={2024},
      }