Datasets:
Tasks:
Visual Question Answering
Formats:
parquet
Languages:
Japanese
Size:
1K - 10K
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README.md
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---
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language:
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- ja
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license: cc-by-4.0
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size_categories:
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- 1K<n<10K
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task_categories:
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- visual-question-answering
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dataset_info:
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features:
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- name: image_id
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dtype: int64
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- name: url
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dtype: string
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- name: width
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dtype: int64
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- name: height
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dtype: int64
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- name: coco_id
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dtype: float64
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- name: flickr_id
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dtype: float64
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- name: qas
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list:
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- name: a_objects
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sequence: 'null'
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- name: answer
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dtype: string
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- name: q_objects
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sequence: 'null'
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- name: qa_id
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dtype: int64
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- name: question
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dtype: string
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- name: image
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dtype: image
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splits:
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- name: test
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num_bytes: 73348776.0
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num_examples: 500
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download_size: 355977607
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dataset_size: 357916367.0
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configs:
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- config_name: default
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data_files:
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- split: test
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path: data/test-*
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---
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# JA-VG-VQA-500
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## Dataset Description
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**JA-VG-VQA-500** is a 500-sample subset of [Japanese Visual Genome VQA dataset](https://github.com/yahoojapan/ja-vg-vqa).
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This dataset was used in the evaluation of [EvoVLM-JP-v1-7B](https://huggingface.co/SakanaAI/EvoVLM-JP-v1-7B).
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Please refer to our [report](https://arxiv.org/abs/2403.13187) and [blog](https://sakana.ai/evolutionary-model-merge/) for more details.
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We are grateful to the developers for making the dataset available under [Creative Commons Attribution 4.0 License](https://creativecommons.org/licenses/by/4.0/legalcode).
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- [Visual Genome](https://homes.cs.washington.edu/~ranjay/visualgenome/index.html)
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- [Japanese Visual Genome VQA dataset](https://github.com/yahoojapan/ja-vg-vqa)
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## Usage
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Use the code below to get started with the dataset.
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```python
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from datasets import load_dataset
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dataset = load_dataset("SakanaAI/JA-VG-VQA-500", split="test")
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```
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See [our GitHub repository](https://github.com/SakanaAI/evolutionary-model-merge) to evaluate Japanese VLMs.
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## Acknowledgement
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We would like to thank the developers of the source datasets for their contributions and for making their work available.
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## Citation
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```bibtex
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@article{Krishna2016VisualGC,
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title = {Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations},
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author. = {Ranjay Krishna and Yuke Zhu and Oliver Groth and Justin Johnson and Kenji Hata and Joshua Kravitz and Stephanie Chen and Yannis Kalantidis and Li-Jia Li and David A. Shamma and Michael S. Bernstein and Li Fei-Fei},
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journal = {International Journal of Computer Vision},
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year. = {2017},
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volume. = {123},
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pages. = {32-73},
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URL = {https://doi.org/10.1007/s11263-016-0981-7},
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doi = {10.1007/s11263-016-0981-7}
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}
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```
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```bibtex
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@InProceedings{C18-1163,
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author = "Shimizu, Nobuyuki and Rong, Na and Miyazaki, Takashi",
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title = "Visual Question Answering Dataset for Bilingual Image Understanding: A Study of Cross-Lingual Transfer Using Attention Maps",
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booktitle = "Proceedings of the 27th International Conference on Computational Linguistics",
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year = "2018",
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publisher = "Association for Computational Linguistics",
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pages = "1918--1928",
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location = "Santa Fe, New Mexico, USA",
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url = "http://aclweb.org/anthology/C18-1163"
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}
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```
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data/test-00000-of-00001.parquet → default/test/0000.parquet
RENAMED
File without changes
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