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Getting Started with Google BERT

You're reading from   Getting Started with Google BERT Build and train state-of-the-art natural language processing models using BERT

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Product type Paperback
Published in Jan 2021
Publisher Packt
ISBN-13 9781838821593
Length 352 pages
Edition 1st Edition
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Author (1):
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Sudharsan Ravichandiran Sudharsan Ravichandiran
Author Profile Icon Sudharsan Ravichandiran
Sudharsan Ravichandiran
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Table of Contents (15) Chapters Close

Preface 1. Section 1 - Starting Off with BERT
2. A Primer on Transformers FREE CHAPTER 3. Understanding the BERT Model 4. Getting Hands-On with BERT 5. Section 2 - Exploring BERT Variants
6. BERT Variants I - ALBERT, RoBERTa, ELECTRA, and SpanBERT 7. BERT Variants II - Based on Knowledge Distillation 8. Section 3 - Applications of BERT
9. Exploring BERTSUM for Text Summarization 10. Applying BERT to Other Languages 11. Exploring Sentence and Domain-Specific BERT 12. Working with VideoBERT, BART, and More 13. Assessments 14. Other Books You May Enjoy

Understanding the decoder of a transformer

Suppose we want to translate the English sentence (source sentence) I am good to the French sentence (target sentence) Je vais bien. To perform this translation, we feed the source sentence I am good to the encoder. The encoder learns the representation of the source sentence. In the previous section, we learned how exactly the encoder learns the representation of the source sentence. Now, we take this encoder's representation and feed it to the decoder. The decoder takes the encoder representation as input and generates the target sentence Je vais bien, as shown in the following figure:

Figure 1.35 – Encoder and decoder of the transformer

In the encoder section, we learned that, instead of having one encoder, we can have a stack of encoders. Similar to the encoder, we can also have a stack of decoders. For simplicity, let's set . As shown in the following figure, the output of one decoder is sent as the input to the decoder...

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Getting Started with Google BERT
Published in: Jan 2021
Publisher: Packt
ISBN-13: 9781838821593
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