Fix custom token in train.py #246
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After the LLaMA model finetuning using the existing training code, I realized that the model never outputs the EOS token, which causes the generation never stop until max_new_token is reached. I tried to debug the code and found that `tokenizer.eos_token`, `tokenizer.bos_token`, and `tokenizer.unk_token` are all `'' (empty string).` Since `'' (empty string)` is not equal to `None`, the custom tokens in the training code will not be added. So I would suggest fixing using the current code changes. I have tested that after the training using the modified code, the model can output EOS token correctly.
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After the LLaMA model finetuning using the existing training code, I realized that the model never outputs the EOS token, which causes the generation never stop until max_new_token is reached.
I tried to debug the code and found that
tokenizer.eos_token,tokenizer.bos_token, andtokenizer.unk_tokenare all'' (empty string).Since
'' (empty string)is not equal toNone, the custom tokens in the training code will not be added. So I would suggest fixing using the current code changes.I have tested that after the training using the modified code, the model can output EOS token correctly.