Improving Language Understanding by Generative Pre-Training阅读笔记
文章目录 概述 Framwork 1. 无监督预训练 2.有监督的fine-tuning 实验 实验设置 无监督预训练 模型规格 Fine-tuning细节 实验结果 概述 要说最近NLP最显著的成果, 自然是几乎无人不知, 无人不晓的Bert. 但其实在Bert出现几个月之前, OpenAI在《Improving Language Understanding by Generative Pre-
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相关文章
- 1. 文献阅读笔记—Improving Language Understanding by Generative Pre-Training
- 2. GPT模型：Improving Language Understanding by Generative Pre-Training
- 3. 【论文笔记】Improving Language Understanding by Generative Pre-Training
- 4. 文献阅读笔记：XLNet: Generalized Autoregressive Pretraining for Language Understanding
- 5. 深度学习 -- > NLP -- >Improving Language Understanding by Generative Pre-Training
- 6. 【论文阅读笔记】Cross-lingual Language Model Pretraining
- 7. 【阅读笔记】Generative Adversarial Nets
- 8. 论文阅读笔记：BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
- 9. Multi-Task Deep Neural Networks for Natural Language Understanding阅读笔记
- 10. 论文阅读笔记：《ERNIE 2.0: A Continual Pre-training Framework for Language Understanding》