数据与计算发展前沿2025，Vol.7Issue(1)：163-174,12.DOI:10.11871/jfdc.issn.2096-742X.2025.01.012
Llama2-70b模型的微调技术及其在材料领域的应用研究
A Study of the Fine-Tuning Technique of the Llama2-70b Model and Its Application in the Field of Materials
摘要
Abstract
[Objective]To lower the barriers of using large language models and promote their applica-tions in different fields,this paper systematically introduces the fine-tuning process of the Lla-ma2-70b model and its application procedure in the field of materials science.[Methods]This study utilized the DeepSpeed framework and an instruction data set of inorganic material syn-thesis pathways,and employed the LoRA fine-tuning technique to fine-tune the open-source Llama2-70b model.The model's hyperparameters were optimized,and the tuning effects were evaluated based on the loss value dur-ing model training and the model's stability.A suitable combination of hyperparameters was finally determined.[Results]Through the training and optimization of the model,a large language model for material synthesis that performs excellently in terms of stability and performance was obtained.[Conclusions]This research provides valuable experience and methods for the application of large language models in academic fields.The trained ma-terial language model offers meaningful reference and support for material synthesis design.关键词
Llama2-70b模型/LoRA/大模型微调/材料合成Key words
Llama2-70b Model/LoRA/Large Language model/material synthesis引用本文复制引用
唐雷,周纯葆,王宗国,陈子逸,梁锶翰,李凯,万萌,张博尧,刘淼,孟胜,王彦棡..Llama2-70b模型的微调技术及其在材料领域的应用研究[J].数据与计算发展前沿,2025,7(1):163-174,12.基金项目
中国科学院网信专项"能源材料端到端设计的信息化智能平台"(CAS-WX2023SF-0101) （CAS-WX2023SF-0101）
中国科学院前沿科学重点研究计划"Ⅲ-Ⅴ族半导体材料的'基因图谱'研究"(ZDBS-LY-7025) （ZDBS-LY-7025）
中国科学院青年创新促进会(2021167) （2021167）
