什么是微调？

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参考文献

Attention Is All You Need, Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin, 2017 Advances in Neural Information Processing Systems (NIPS 2017) DOI: 10.48550/arXiv.1706.03762 - 介绍了Transformer架构，这是现代大型语言模型（包括经过微调的模型）的基础。
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, 2019 Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) DOI: 10.48550/arXiv.1810.04805 - 详细介绍了深度双向Transformer的预训练和微调范式，为大型语言模型的适应性应用设定了重要方法。
Natural Language Processing with Transformers, Lewis Tunstall, Leandro von Werra, Thomas Wolf, 2022 (O'Reilly Media) - 一本关于使用和微调Transformer模型以完成各种自然语言处理任务的实用指南，提供了具体示例和最佳实践。
Transfer Learning in Natural Language Processing: A Survey, Sebastian Ruder, Iain Stewart, Jeremy Howard, 2019 Proceedings of the Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) DOI: 10.18653/v1/D19-1587 - 全面概述了自然语言处理中的迁移学习技术，包括本文讨论的预训练和微调方法。