Comments (3)
We use the F1 version of ROUGE, which penalizes the length. For the dataset, it's a common practice to set a minimum length and a maximum length to control the output. For example, in the code https://github.com/sebastianGehrmann/OpenNMT-py/blob/copy_constraint/opts.py#L416 , there are -min_length
and -max_length
flags used for this purpose.
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Yes, they are equivalent implementations for better flexibility. Thanks for the comments.
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Ha right !
You are completely right !
In other code, this "truncation" is mostly done while predicting.
It seemed odd to me to truncate after predicting.
But indeed it's completely equivalent...
Thank you for the clarification and sorry for the bother..
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