LLM在工业品物料分类场景的应用  

The application of LLM in industrial material classification

作　　者：朱俊 ZHU Jun(Obei Co.,Ltd.,Shanghai 201900,China)

机构地区：[1]欧冶工业品股份有限公司,上海201900

出　　处：《宝钢技术》2023年第6期29-32,共4页Baosteel Technology

摘　　要：为了解决工业品分类中传统技术所面临的数据不足、泛化性能不佳和准确度不高的问题,提出了一种结合大语言模型与深度学习文本分类的新型工业品物料分类模型。通过利用大语言模型进行数据增强和分类结果的校准,优化了原有的技术框架。经过验证,与原模型相比,新模型在精准率、召回率和准确率方面均实现了显著提升。To address the issues faced by traditional technologies in industrial product classification,such as data insufficiency,poor generalization performance,and low accuracy,we have introduced a new industrial product material classification model that integrates large language model techniques with deep learning text classification.By leveraging the large language model for data augmentation and classification result verification,we have optimized the existing technical stack.After validation,compared to the original model,the new model has achieved significant improvements in precision,recall,and accuracy.

关 键 词：工业品物料分类 文本分类 自然语言处理(NLP) 生成式大语言模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]