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I am also interested in knowing how we can do multi-label classification through BERT. Does it depend on the 'out' attribute in the BERTBaseUncased Class? There is a hint in the video for this repo about changing loss functions for multi-label classification. Would like to know more about from @abhishekkrthakur .
how can this model be trained for a multi-label classification problem?
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