The FinChina SA dataset and code from FinLLM@IJCAI'23 paper:
Chinese Fine-Grained Financial Sentiment Analysis with Large Language Models
https://link.springer.com/article/10.1007/s00521-024-10603-6
First, the data needs to be processed into a conversational form like this:
{
"conversations":[
{
"from":"human",
"value":"question"
},
{
"from":"gpt",
"value":"answer"
}
]
}
The code is in the src folder and you need to modify the configuration in the shell script.
To fine-tune the model:
sh sft.sh
To run inference:
sh run_infer.sh
Our experiments is based on the following repo:
Thanks for their efforts to make the code and model weights public.
If you find this project useful, please cite it using the following format
@article{lan2024chinese,
title={Chinese fine-grained financial sentiment analysis with large language models},
author={Lan, Yinyu and Wu, Yanru and Xu, Wang and Feng, Weiqiang and Zhang, Youhao},
journal={Neural Computing and Applications},
pages={1--10},
year={2024},
publisher={Springer}
}