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Transformers for Natural Language Processing

You're reading from   Transformers for Natural Language Processing Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more

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Product type Paperback
Published in Jan 2021
Publisher Packt
ISBN-13 9781800565791
Length 384 pages
Edition 1st Edition
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Author (1):
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Denis Rothman Denis Rothman
Author Profile Icon Denis Rothman
Denis Rothman
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Toc

Table of Contents (16) Chapters Close

Preface 1. Getting Started with the Model Architecture of the Transformer 2. Fine-Tuning BERT Models FREE CHAPTER 3. Pretraining a RoBERTa Model from Scratch 4. Downstream NLP Tasks with Transformers 5. Machine Translation with the Transformer 6. Text Generation with OpenAI GPT-2 and GPT-3 Models 7. Applying Transformers to Legal and Financial Documents for AI Text Summarization 8. Matching Tokenizers and Datasets 9. Semantic Role Labeling with BERT-Based Transformers 10. Let Your Data Do the Talking: Story, Questions, and Answers 11. Detecting Customer Emotions to Make Predictions 12. Analyzing Fake News with Transformers 13. Other Books You May Enjoy
14. Index
Appendix: Answers to the Questions

Chapter 4, Downstream NLP Tasks with Transformers

  1. Machine intelligence uses the same data as humans to make predictions. (True/False)

    False. For NLU, humans have access to more information through their senses. Machine intelligence relies on what humans provide for all types of media.

  2. SuperGLUE is more difficult than GLUE for NLP models. (True/False)

    True.

  3. BoolQ expects a binary answer. (True/False)

    True.

  4. WiC stands for Words in Context. (True/False)

    True.

  5. Recognizing Textual Entailment (RTE) detects if one sequence entails another sequence. (True/False)

    True.

  6. A Winograd Schema predicts if a verb is spelled correctly. (True/False)

    False. Winograd schemas mostly apply to pronoun disambiguation.

  7. Transformer models now occupy the top ranks of GLUE and SuperGLUE. (True/False)

    True.

  8. Human Baseline Standards are not defined once and for all. They were made tougher to attain by SuperGLUE. (True...
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