Improving Language Understanding by Generative Pre-Training閱讀筆記
文章目錄 概述 Framwork 1. 無監督預訓練 2.有監督的fine-tuning 實驗 實驗設置 無監督預訓練 模型規格 Fine-tuning細節 實驗結果 概述 要說最近NLP最顯著的成果, 自然是幾乎無人不知, 無人不曉的Bert. 但其實在Bert出現幾個月之前, OpenAI在《Improving Language Understanding by Generative Pre-
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- 3. 【論文筆記】Improving Language Understanding by Generative Pre-Training
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- 5. 深度學習 -- > NLP -- >Improving Language Understanding by Generative Pre-Training
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相關文章
- 1. 文獻閱讀筆記—Improving Language Understanding by Generative Pre-Training
- 2. GPT模型：Improving Language Understanding by Generative Pre-Training
- 3. 【論文筆記】Improving Language Understanding by Generative Pre-Training
- 4. 文獻閱讀筆記：XLNet: Generalized Autoregressive Pretraining for Language Understanding
- 5. 深度學習 -- > NLP -- >Improving Language Understanding by Generative Pre-Training
- 6. 【論文閱讀筆記】Cross-lingual Language Model Pretraining
- 7. 【閱讀筆記】Generative Adversarial Nets
- 8. 論文閱讀筆記：BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
- 9. Multi-Task Deep Neural Networks for Natural Language Understanding閱讀筆記
- 10. 論文閱讀筆記：《ERNIE 2.0: A Continual Pre-training Framework for Language Understanding》