---
title: FinQA
canonical_url: "https://www.modelscope.cn/datasets/OmniData/FinQA"
md_url: "https://www.modelscope.cn/datasets/OmniData/FinQA.md"
repository: OmniData/FinQA
last_updated: 2024-07-02
license: "[MIT]"
storage_size: "94 MB"
domain:
  - publishDate
  - displayName
  - paperUrl
  - publishUrl
  - publisher
  - mediaTypes
  - taskTypes
tasks:
  - 2021
  - FinQA
  - "https://arxiv.org/pdf/2109.00122v3.pdf"
  - "https://github.com/czyssrs/FinQA"
  - "J.P. Morgan"
  - Text
  - "Visual Question Answering"
downloads: 483
stars: 2
---

# FinQA

> FinQA - OmniData 在 ModelScope 开源的数据集。displayName: FinQA license: MIT mediaTypes: Text paperUrl: https://arxiv.org/pdf/2109.00122v3.pdf publishDate: "2021" publishUrl: https://github.com/czyssrs/FinQA publisher: Carnegie Mellon University University of…

OmniData/FinQA 是 ModelScope 魔搭社区上的2021、FinQA、https://arxiv.org/pdf/2109.00122v3.pdf数据集，涉及 publishDate、displayName、paperUrl 领域，存储大小 94 MB，采用 [MIT] 许可。

- **Repository**: OmniData/FinQA
- **License**: [MIT]
- **Tasks**: 2021, FinQA, https://arxiv.org/pdf/2109.00122v3.pdf, https://github.com/czyssrs/FinQA, J.P. Morgan, Text, Visual Question Answering
- **Domain**: publishDate, displayName, paperUrl, publishUrl, publisher, mediaTypes, taskTypes
- **Storage size**: 94 MB
- **Downloads**: 483
- **Stars**: 2
- **Last updated**: 2024-07-02

Source: https://www.modelscope.cn/datasets/OmniData/FinQA

---

displayName: FinQA
license:
- MIT
mediaTypes:
- Text
paperUrl: https://arxiv.org/pdf/2109.00122v3.pdf
publishDate: "2021"
publishUrl: https://github.com/czyssrs/FinQA
publisher:
- Carnegie Mellon University
- University of California
- Pennsylvania State University
- J.P. Morgan
tags:
- Finance QA
taskTypes:
- Visual Question Answering

---
# 数据集介绍
  ## 简介
  FinQA 是一个新的大型数据集，由财务专家编写，在财务报告中包含问答对。该数据集包含 8,281 个财务 QA 对，以及它们的数值推理过程。
  ## 引文
  ```
@article{chen2021finqa,
  title={Finqa: A dataset of numerical reasoning over financial data},
  author={Chen, Zhiyu and Chen, Wenhu and Smiley, Charese and Shah, Sameena and Borova, Iana and Langdon, Dylan and Moussa, Reema and Beane, Matt and Huang, Ting-Hao and Routledge, Bryan and others},
  journal={arXiv preprint arXiv:2109.00122},
  year={2021}
}
```
  
## Download dataset
:modelscope-code[]{type="git"}