README.md

metadata

pretty_name: FinBen · FSRL
license: mit
language:
  - en
task_categories:
  - token-classification
size_categories:
  - n<1K
source_datasets:
  - extended
tags:
  - finance
  - benchmark
  - thefinai
  - finben
  - flare
dataset_info:
  features:
    - name: id
      dtype: string
    - name: query
      dtype: string
    - name: answer
      dtype: string
    - name: text
      dtype: string
    - name: label
      sequence: string
    - name: token
      sequence: string
  splits:
    - name: test
      num_bytes: 200466
      num_examples: 97
  download_size: 69893
  dataset_size: 200466
extra_gated_heading: Request access to FinBen · FSRL
extra_gated_description: >-
  This FinBen task is released by The Fin AI for research. Access is granted
  automatically after you complete this short form.
extra_gated_button_content: Agree and access
extra_gated_prompt: >-
  By accessing this dataset you agree to the license of the original source (MIT
  License) and to cite the FinBen paper and the original dataset in any
  resulting publication.
extra_gated_fields:
  Full name: text
  Affiliation: text
  Country: country
  Intended use:
    type: select
    options:
      - Research
      - Education
      - Commercial evaluation
      - Other
  I agree to the terms above and will cite the papers: checkbox

FinBen · FSRL

📄 Paper · 💻 Code · 🏆 Leaderboard · 🌐 The Fin AI

Part of FinBen — FinBen: A Holistic Financial Benchmark for Large Language Models (arXiv:2402.12659).

Task	textual analogy parsing
Original dataset	FSRL (Lamm et al., 2018)
Evaluation metric	F1, EM Accuracy
Source license	MIT License
Language	en

Quick Start

from datasets import load_dataset

ds = load_dataset("TheFinAI/en-fsrl", split="test")
print(ds[0])

Example prompt

In the task of Textual Analogy Parsing (TAP), your job is to identify and label the semantic role of each token in a sentence. The labels can include 'O', 'I-QUANT', 'B-QUANT', 'I-TIME', 'B-TIME', 'I-MANNER', 'B-MANNER', 'I-THEME', 'B-THEME', 'I-VALUE', 'B-VALUE', 'I-WHOLE', 'B-WHOLE', 'I-LOCATION', 'B-LOCATION', 'I-AGENT', 'B-AGENT', 'I-CAUSE', 'B-CAUSE', 'I-SOURCE', 'B-SOURCE', 'I-REF_TIME', 'B-…

Dataset Structure

Split	Rows
test	97

Field	Description
id	Example id
query	Full instruction prompt given to the model
answer	Gold answer / label text
text	Raw input text (without instruction)
label	Gold label(s)
token

License

The original data is released under MIT License (FinBen paper, Table 2).

Citation

Please cite FinBen and the original dataset (FSRL (Lamm et al., 2018)):

@misc{xie2024finbenholisticfinancialbenchmark,
      title={FinBen: A Holistic Financial Benchmark for Large Language Models},
      author={Qianqian Xie and Weiguang Han and Zhengyu Chen and Ruoyu Xiang and Xiao Zhang and Yueru He and Mengxi Xiao and Dong Li and Yongfu Dai and Duanyu Feng and Yijing Xu and Haoqiang Kang and Ziyan Kuang and Chenhan Yuan and Kailai Yang and Zheheng Luo and Tianlin Zhang and Zhiwei Liu and Guojun Xiong and Zhiyang Deng and Yuechen Jiang and Zhiyuan Yao and Haohang Li and Yangyang Yu and Gang Hu and Jiajia Huang and Xiao-Yang Liu and Alejandro Lopez-Lira and Benyou Wang and Yanzhao Lai and Hao Wang and Min Peng and Sophia Ananiadou and Jimin Huang},
      year={2024},
      eprint={2402.12659},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2402.12659},
}