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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: 12-category
dtype: 'null'
- name: comment
dtype: string
splits:
- name: test
num_bytes: 103342891
num_examples: 4324
download_size: 101580105
dataset_size: 103342891
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
# MMBench_Greek
This dataset is a Greek translation of [MMBench](https://huggingface.co/datasets/HuggingFaceM4/MMBench), a multiple-choice benchmark for evaluating multimodal and Vision-Language Models.
The goal of this version is to make MMBench usable as an evaluation benchmark for Greek-capable VLMs.
## Dataset Description
The dataset keeps the same structure and column names as the original MMBench_dev dataset. The text fields have been translated into Greek, while metadata fields are kept unchanged.
Each example contains an image, a question, optional hint text, multiple-choice answer options, the correct answer label, and category/source metadata.
## Columns
* `index`: example index
* `question`: the question
* `hint`: optional hint
* `A`: answer option A
* `B`: answer option B
* `C`: answer option C
* `D`: answer option D
* `answer`: correct answer
* `image`: the image associated with the question
* `source`: source dataset
* `l2-category`: higher-level category
* `comment`: optional comment
## Intended Use
This dataset is intended for evaluating Greek Vision-Language Models on multimodal multiple-choice question answering.
A typical evaluation prompt can ask the model to inspect the image, read the Greek question and answer options, and output only the correct option label.
## Citation
Please cite the original MMBench paper when using this dataset:
```bibtex id="ej32xq"
@article{MMBench,
title={MMBench: Is Your Multi-modal Model an All-around Player?},
author={Liu, Yuan and Duan, Haodong and Zhang, Yuanhan and Li, Bo and Zhang, Songyang and Zhao, Wangbo and Yuan, Yike and Wang, Jiaqi and He, Conghui and Liu, Ziwei and Chen, Kai and Lin, Dahua},
journal={arXiv preprint arXiv:2307.06281},
year={2023}
}
```
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