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Chap 3: Fault about TransformerForSequenceClassification #144

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S3nnyK opened this issue Aug 9, 2024 · 0 comments
Open
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Chap 3: Fault about TransformerForSequenceClassification #144

S3nnyK opened this issue Aug 9, 2024 · 0 comments

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@S3nnyK
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S3nnyK commented Aug 9, 2024

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The question or comment is about chapter:

  • Introduction
  • Text Classification
  • Transformer Anatomy
  • Multilingual Named Entity Recognition
  • Text Generation
  • Summarization
  • Question Answering
  • Making Transformers Efficient in Production
  • Dealing with Few to No Labels
  • Training Transformers from Scratch
  • Future Directions

Question or comment

In TransformerForSequenceClassification, x = self.encoder(x)[:, 0, :] means [CLS] token is included in the inputs. However, in the beginning of this chapter, inputs is defined as tokenizer(text, return_tensors="pt", add_special_tokens=False), without special_tokens. Hence, the 0-th is "time", not "[CLS]".
@S3nnyK S3nnyK changed the title Fault about TransformerForSequenceClassification Chap 3: Fault about TransformerForSequenceClassification Aug 9, 2024
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