hi,
first of all thanks for your pytorch implementation. i m getting a pretty good results when i put is_coverage=False in config. But while putting it true all the summaries just contain the single word which is repeated (atleast minimum number of decoder times). i am using the same dataset and i trained it for 250000 iteration for is_coverage=True and 200000 for is_coverage=False.
Most of the summaries are abstractive in nature they are just copying complete lines from the story . why as per model there needs to be some kind of abstraction.???
while use coverage as true all decoder outputs the same word means there is only single word repeated in entire summary.
Any kind of help is very helpful......thanks in advance.
hi, first of all thanks for your pytorch implementation. i m getting a pretty good results when i put is_coverage=False in config. But while putting it true all the summaries just contain the single word which is repeated (atleast minimum number of decoder times). i am using the same dataset and i trained it for 250000 iteration for is_coverage=True and 200000 for is_coverage=False.
Most of the summaries are abstractive in nature they are just copying complete lines from the story . why as per model there needs to be some kind of abstraction.???
while use coverage as true all decoder outputs the same word means there is only single word repeated in entire summary. Any kind of help is very helpful......thanks in advance.