基于预训练模型的深度学习算法优化研究

Optimization study of deep learning algorithm based on pre-training model

近年来,预训练模型在深度学习算法中的应用越发广泛,其具体功能愈加完善。文章首先阐述了深度学习的研究进展及其存在的问题,其次由深度学习的应用引入预训练模型的概念、应用方式及其在深度学习算法优化中的作用,最后总结了预训练模型存在的不足及发展前景。随着自然语言处理技术的进一步发展,基于预训练模型的深度学习算法的弊端得到部分消除,未来发展前景值得期待。

In recent years,pre-trained models have been more widely used in deep learning algorithms,and their specific functions have become more perfect.The paper first expounds the research progress of deep learning and its problems existing.Secondly,it introduces the concept,application mode and its role in the optimization of deep learning algorithm,and finally summarizes the shortcomings,solution strategies and development prospects of the pre-training model.With the further development of natural language processing technology,the drawbacks of deep learning algorithms based on pre-training models have been partially eliminated,and the future development prospect is worth looking forward to.