تقرير
DISC-FinLLM: A Chinese Financial Large Language Model based on Multiple Experts Fine-tuning
| العنوان: | DISC-FinLLM: A Chinese Financial Large Language Model based on Multiple Experts Fine-tuning |
|---|---|
| المؤلفون: | Chen, Wei, Wang, Qiushi, Long, Zefei, Zhang, Xianyin, Lu, Zhongtian, Li, Bingxuan, Wang, Siyuan, Xu, Jiarong, Bai, Xiang, Huang, Xuanjing, Wei, Zhongyu |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language |
| الوصف: | We propose Multiple Experts Fine-tuning Framework to build a financial large language model (LLM), DISC-FinLLM. Our methodology improves general LLMs by endowing them with multi-turn question answering abilities, domain text processing capabilities, mathematical computation skills, and retrieval-enhanced generation capabilities. We build a financial instruction-tuning dataset named DISC-FIN-SFT, including instruction samples of four categories (consulting, NLP tasks, computing and retrieval-augmented generation). Evaluations conducted on multiple benchmarks demonstrate that our model performs better than baseline models in various financial scenarios. Further resources can be found at https://github.com/FudanDISC/DISC-FinLLM. Comment: 18 pages, 13 figures, 7 tables |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2310.15205 |
| رقم الأكسشن: | edsarx.2310.15205 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |