This is not really an issue as the code is doing what it should, but I think it would be good to warn users that if they are truncating samples (which, to my knowledge, is the default setting of HuggingFace and PyTorch) to fit the maximum model length (e.g. 512 tokens), then they will have blanks in their reconstructed files, which will lower their results.
This is not really an issue as the code is doing what it should, but I think it would be good to warn users that if they are truncating samples (which, to my knowledge, is the default setting of HuggingFace and PyTorch) to fit the maximum model length (e.g. 512 tokens), then they will have blanks in their reconstructed files, which will lower their results.
Just dropping the idea !