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Dear author, your framework is valid on the English dataset, but when I used dual-loss deficiency on my Chinese dataset, gradient collapse occurred. My Chinese label is two characters, is it related to this? Or do I have to adjust somewhere? Thank you very much. Look forward to hearing from you soon
The text was updated successfully, but these errors were encountered:
Hi, we should use a single word to tokenize each label in DualCL. I conjecture that if the two-character Chinese label is encoded by two or more tokens, the DualCL loss will perform abnormally. Consider adding the whole label to the dictionary or alerting the label to a single (Chinese) character.
Dear author, your framework is valid on the English dataset, but when I used dual-loss deficiency on my Chinese dataset, gradient collapse occurred. My Chinese label is two characters, is it related to this? Or do I have to adjust somewhere? Thank you very much. Look forward to hearing from you soon
The text was updated successfully, but these errors were encountered: