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---
language:
- en
- zh
- fr
license: apache-2.0
size_categories:
- 1K<n<10K
task_categories:
- question-answering
- multiple-choice
pretty_name: 'FAMMA: A Benchmark for Financial Domain Multilingual Multimodal Question
Answering'
tags:
- finance
dataset_info:
features:
- name: idx
dtype: int32
- name: question_id
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: options
sequence: string
- name: image_1
dtype:
image:
decode: false
- name: image_2
dtype:
image:
decode: false
- name: image_3
dtype:
image:
decode: false
- name: image_4
dtype:
image:
decode: false
- name: image_5
dtype:
image:
decode: false
- name: image_6
dtype:
image:
decode: false
- name: image_7
dtype:
image:
decode: false
- name: image_type
dtype: string
- name: answers
dtype: string
- name: explanation
dtype: string
- name: topic_difficulty
dtype: string
- name: question_type
dtype: string
- name: subfield
dtype: string
- name: language
dtype: string
- name: main_question_id
dtype: string
- name: sub_question_id
dtype: string
- name: ans_image_1
dtype:
image:
decode: false
- name: ans_image_2
dtype:
image:
decode: false
- name: ans_image_3
dtype:
image:
decode: false
- name: ans_image_4
dtype:
image:
decode: false
- name: ans_image_5
dtype:
image:
decode: false
- name: ans_image_6
dtype:
image:
decode: false
- name: release
dtype: string
splits:
- name: release_v2406
num_bytes: 76263174.75
num_examples: 1378
download_size: 68945186
dataset_size: 76263174.75
configs:
- config_name: default
data_files:
- split: release_v2406
path: data/release_v2406-*
---
## Introduction
FAMMA dataset consists of 1,758 meticulously collected multimodal questions. The questions encompass three heterogeneous image types - tables, charts and text & math screenshots - and span eight subfields in finance, comprehensively covering topics across major asset classes. Additionally, all the questions are categorized by three difficulty levels — easy, medium, and hard - and are available in three languages — English, Chinese, and French. Furthermore, the questions are divided into two types: multiple-choice and open questions.
The leaderboard is regularly updated and can be accessed at https://famma-bench.github.io/famma/.
Note: we are reconstructing the dataset again, which will be finihsed before Feb.
## Dataset Structure
### features
- question_id: a unique identifier for the question across the whole dataset.
- context: relevant background information related to the question.
- question: the specific query being asked.
- options: the specific query being asked.
- image_1- image_7: directories of images referenced in the context or question.
- image_type: type of the image, e.g., chart, table, screenshot.
- answers: a concise and accurate response. **(non-public on the test set for the moment)**
- explanation：a detailed justification for the answer. **(non-public on the test set for the moment)**
- topic_difficulty: a measure of the question's complexity based on the level of reasoning required.
- question_type: categorized as either multiple-choice or open-ended.
- subfield: the specific area of expertise to which the question belongs, categorized into eight subfields.
- language：the language in which the question text is written.
- main_question_id：a unique identifier for the question within its context; questions with the same context share the same ID.
- sub_question_id：a unique identifier for the question within its corresponding main question.
- ans_image_1 - ans_image_4： **(non-public on the test set for the moment)**
### dataset splits
Chinese subset
- splits:
- name: validation
- num_bytes: 530067.0
- num_examples: 19
- name: test
- num_bytes: 10497574.0
- num_examples: 234
English subset
- splits:
- name: validation
- num_bytes: 19326545.0
- num_examples: 88
- name: test
- num_bytes: 235713843.904
- num_examples: 1297
French subset
- splits:
- name: validation
- num_bytes: 1945622.0
- num_examples: 13
- name: test
- num_bytes: 14026200.0
- num_examples: 107
## Citation
If you use FAMMA in your research, please cite our paper as follows:
```latex
@article{xue2024famma,
title={FAMMA: A Benchmark for Financial Domain Multilingual Multimodal Question Answering},
author={Siqiao Xue, Tingting Chen, Fan Zhou, Qingyang Dai, Zhixuan Chu, and Hongyuan Mei},
journal={arXiv preprint arXiv:2410.04526},
year={2024},
url={https://arxiv.org/abs/2410.04526}
}
``` |