Clarification: finetune.py max target length
@sshleifer(1) could you clarify what is the rationale behind these assertions?github.comhuggingface/transformers/blob/5e24982e580ab32a779d7271ad8cb46dc5c6475f/examples/seq2seq/finetune.py#L93-L94assert self.target_lens["train"] <= self.target_lens["val"], f"target_lens: {self.target_lens}"assert self.target_lens["train"] <= self.target_lens["test"], f"target_lens: {self.target_lens}"(2) The naming of the variables*_max_target_lengthmake it seem like they specify a bound on the target (output), but it seems like (according totheir description) they’re limits on the input (source). What do you think we rename them to something more descriptive?
2020-11-12T17:44:52Z
danyaljj:their descriptionNaming of the variables is correct, the description is wrong. Feel free to change the description.cc@valhallaif you copy pasted bad descriptions.
2020-11-12T17:46:04Z
The assertions basically suggest that there is no reason you would want to truncate validation target sequences more aggressively than you are truncating train sequences. So if you passed those parameters, you probably made a mistake.