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huggingface / transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
https://huggingface.co/transformers
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Some questions about the abstractive summarization code. #1855

Closed linWujl closed 5 years ago

linWujl commented 5 years ago

❓ Questions & Help

Hi, thanks for sharing the code, i was confused about some code and implements when i reading it. a) In run_summarization_finetuning.py, image should cls_token_id be replaced by sep_token_id? b) In utils_summarization.py image This will make sequence [cls] a b [sep] c d [sep] encoded as 0 0 0 1 1 1 0, should the order be changed? c) In the decoder, the deocder_mask only mask the pad token, i think look_ahead_mask is more accurate for we can't see the future words in advance.

Looking forward to reply. Thanks!

rlouf commented 5 years ago

Hi!

First, please check the run_summarization.py script in the example-summarization branch as it is more up-to-date. To answer your questions:

a) We are following this implementation: https://arxiv.org/pdf/1908.08345.pdf where they add an extra [CLS] token for each new sentence.

b) I would need to triple-check the authors’ code, but I hope it does not matter.

c) Good point. If you look at the way the encoder-decoder is implemented you will see that masks passed to the decoder are automatically turned into causal (“look-ahead”), so the code does have the expected behavior :)

linWujl commented 5 years ago

Thank you so much.