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The FinChina SA dataset and code for FinLLM@IJCAI'23 paper "Chinese Fine-Grained Financial Sentiment Analysis with Large Language Models"

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FinChina SA

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

Code

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.

Fine-tune

To fine-tune the model:

sh sft.sh

Inference

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.

Citation

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}
}

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The FinChina SA dataset and code for FinLLM@IJCAI'23 paper "Chinese Fine-Grained Financial Sentiment Analysis with Large Language Models"

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