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README.md

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+---
+language:
+- ja
+license: cc-by-4.0
+size_categories:
+- 1K<n<10K
+task_categories:
+- visual-question-answering
+dataset_info:
+  features:
+  - name: image_id
+    dtype: int64
+  - name: url
+    dtype: string
+  - name: width
+    dtype: int64
+  - name: height
+    dtype: int64
+  - name: coco_id
+    dtype: float64
+  - name: flickr_id
+    dtype: float64
+  - name: qas
+    list:
+    - name: a_objects
+      sequence: 'null'
+    - name: answer
+      dtype: string
+    - name: q_objects
+      sequence: 'null'
+    - name: qa_id
+      dtype: int64
+    - name: question
+      dtype: string
+  - name: image
+    dtype: image
+  splits:
+  - name: test
+    num_bytes: 73348776.0
+    num_examples: 500
+  download_size: 355977607
+  dataset_size: 357916367.0
+configs:
+- config_name: default
+  data_files:
+  - split: test
+    path: data/test-*
+---
+
+# JA-VG-VQA-500
+
+
+## Dataset Description 
+
+**JA-VG-VQA-500** is a 500-sample subset of [Japanese Visual Genome VQA dataset](https://github.com/yahoojapan/ja-vg-vqa).
+This dataset was used in the evaluation of [EvoVLM-JP-v1-7B](https://huggingface.co/SakanaAI/EvoVLM-JP-v1-7B). 
+Please refer to our [report](https://arxiv.org/abs/2403.13187) and [blog](https://sakana.ai/evolutionary-model-merge/) for more details. 
+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). 
+
+- [Visual Genome](https://homes.cs.washington.edu/~ranjay/visualgenome/index.html)
+- [Japanese Visual Genome VQA dataset](https://github.com/yahoojapan/ja-vg-vqa)
+
+## Usage
+
+Use the code below to get started with the dataset.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("SakanaAI/JA-VG-VQA-500", split="test")
+```
+
+See [our GitHub repository](https://github.com/SakanaAI/evolutionary-model-merge) to evaluate Japanese VLMs. 
+
+## Acknowledgement
+
+We would like to thank the developers of the source datasets for their contributions and for making their work available.
+
+## Citation
+
+```bibtex
+@article{Krishna2016VisualGC,
+  title   = {Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations},
+  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},
+  journal = {International Journal of Computer Vision},
+  year.   = {2017},
+  volume. = {123},
+  pages.  = {32-73},
+  URL     = {https://doi.org/10.1007/s11263-016-0981-7},
+  doi     = {10.1007/s11263-016-0981-7}
+}
+```
+
+```bibtex
+@InProceedings{C18-1163,
+  author    = "Shimizu, Nobuyuki and Rong, Na and Miyazaki, Takashi",
+  title     = "Visual Question Answering Dataset for Bilingual Image Understanding: A Study of Cross-Lingual Transfer Using Attention Maps",
+  booktitle = "Proceedings of the 27th International Conference on Computational Linguistics",
+  year      = "2018",
+  publisher = "Association for Computational Linguistics",
+  pages     = "1918--1928",
+  location  = "Santa Fe, New Mexico, USA",
+  url       = "http://aclweb.org/anthology/C18-1163"
+}
+```

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