Hi ,
I want to train a sentiment analysis multi-label classifier and in addition to training the final output layers, I’d like to train the hidden BERT layers as well.
I want to understand how much improvement can I get in my metric(F1 score) by feeding it my domain-specific data.
All the documents /references I have seen thus far only point to training the final output layer that generates classification. Is there a way to train various hidden layers of BERT using (let’s say) BERT Base?
Thanks in advance,
Devesh
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