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Pointer-generator reinforced seq2seq summarization in PyTorch

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This code uses batch-averaged (sample_rouge - baseline rouge), but it don't make sense in math and this item should be sample-wise because what we really want to maximize is this:

Hello, @ymfa I am now training this model. Could you tell me what is the ideal rouge score? Thank you.

I run the code in GPU server,but when run the rouge to value the result ,the error come out: /bin/sh: 1: ./ROUGE-1.5.5.pl: Permission denied ![image](https://user-images.githubusercontent.com/59657317/98352548-229fac80-2059-11eb-9f78-d02a5a8728db.png) Do you know what happen?...

sorry, but how can I get data/.vector_cache/glove.6B.100d.txt?

i am new in pythin & nlp, so i am not sure how to solve this problem. i will appreciate you if you can tell me how to solve that...

Hello, i have a trouble. when i train the model by using the data of google. the trainn loss is decrease, but the valid loss is increase at about 6....

i want to ask about the end_token of the generating summarization. for example. extras needed for film that starts island in the island ; ' for rise again '' film...

The author of pointer-generator propose a method called coverage mechanism. Coverage vector, which is the sum of attention distributions over all previous decoder timesteps, but the coverage vector in this...

Good job. How about rouge scores?