README.md

metadata

dataset_info:
  - config_name: ScienceQA-FULL
    features:
      - name: image
        dtype: image
      - name: question
        dtype: string
      - name: choices
        sequence: string
      - name: answer
        dtype: int8
      - name: hint
        dtype: string
      - name: task
        dtype: string
      - name: grade
        dtype: string
      - name: subject
        dtype: string
      - name: topic
        dtype: string
      - name: category
        dtype: string
      - name: skill
        dtype: string
      - name: lecture
        dtype: string
      - name: solution
        dtype: string
    splits:
      - name: validation
        num_bytes: 140142913.699
        num_examples: 4241
      - name: test
        num_bytes: 138277282.051
        num_examples: 4241
    download_size: 679275875
    dataset_size: 700620101.932
  - config_name: ScienceQA-IMG
    features:
      - name: image
        dtype: image
      - name: question
        dtype: string
      - name: choices
        sequence: string
      - name: answer
        dtype: int8
      - name: hint
        dtype: string
      - name: task
        dtype: string
      - name: grade
        dtype: string
      - name: subject
        dtype: string
      - name: topic
        dtype: string
      - name: category
        dtype: string
      - name: skill
        dtype: string
      - name: lecture
        dtype: string
      - name: solution
        dtype: string
    splits:
      - name: validation
        num_bytes: 137253441
        num_examples: 2097
      - name: test
        num_bytes: 135188432
        num_examples: 2017
    download_size: 663306124
    dataset_size: 685752524
configs:
  - config_name: ScienceQA-FULL
    data_files:
      - split: validation
        path: ScienceQA-FULL/validation-*
      - split: test
        path: ScienceQA-FULL/test-*
  - config_name: ScienceQA-IMG
    data_files:
      - split: validation
        path: ScienceQA-IMG/validation-*
      - split: test
        path: ScienceQA-IMG/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 derek-thomas/ScienceQA. It is used in our lmms-eval pipeline to allow for one-click evaluations of large multi-modality models.

@inproceedings{lu2022learn,
    title={Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering},
    author={Lu, Pan and Mishra, Swaroop and Xia, Tony and Qiu, Liang and Chang, Kai-Wei and Zhu, Song-Chun and Tafjord, Oyvind and Clark, Peter and Ashwin Kalyan},
    booktitle={The 36th Conference on Neural Information Processing Systems (NeurIPS)},
    year={2022}
}