README.md

---
dataset_info:
  features:
  - name: index
    dtype: int64
  - name: question
    dtype: string
  - name: hint
    dtype: string
  - name: A
    dtype: string
  - name: B
    dtype: string
  - name: C
    dtype: string
  - name: D
    dtype: string
  - name: answer
    dtype: string
  - name: category
    dtype: string
  - name: image
    dtype: image
  - name: source
    dtype: string
  - name: l2-category
    dtype: string
  - name: comment
    dtype: string
  - name: split
    dtype: string
  splits:
  - name: dev
    num_bytes: 103845260.875
    num_examples: 4377
  - name: test
    num_bytes: 149612780.25
    num_examples: 6718
  download_size: 240192616
  dataset_size: 253458041.125
configs:
- config_name: default
  data_files:
  - split: dev
    path: data/dev-*
  - split: test
    path: data/test-*
---
# Dataset Card for "MMBench_EN"
<p align="center" width="100%">
<img src="https://i.postimg.cc/g0QRgMVv/WX20240228-113337-2x.png"  width="100%" height="80%">
</p>

# Large-scale Multi-modality Models Evaluation Suite

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

🏠 [Homepage](https://lmms-lab.github.io/) | 📚 [Documentation](docs/README.md) | 🤗 [Huggingface Datasets](https://huggingface.co/lmms-lab)

# This Dataset

This is a formatted version of the English subset of [MMBench](https://arxiv.org/abs/2307.06281). It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models.

```
@article{MMBench,
    author  = {Yuan Liu, Haodong Duan, Yuanhan Zhang, Bo Li, Songyang Zhang, Wangbo Zhao, Yike Yuan, Jiaqi Wang, Conghui He, Ziwei Liu, Kai Chen, Dahua Lin},
    journal = {arXiv:2307.06281},
    title   = {MMBench: Is Your Multi-modal Model an All-around Player?},
    year    = {2023},
}
```