hello , In your paper ,we can see
BERT embedding uses the pre-trained BERT to generate word vectors of sequence. In order to facilitate the training and fine-tuning of BERT model, we transform the given context and target to “[CLS] + context + [SEP]” and “[CLS] + target + [SEP]” respectively.
can you tell me ,how you fine-tuning BERT model? use BERT ML model?
hello , In your paper ,we can see
BERT embedding uses the pre-trained BERT to generate word vectors of sequence. In order to facilitate the training and fine-tuning of BERT model, we transform the given context and target to “[CLS] + context + [SEP]” and “[CLS] + target + [SEP]” respectively.
can you tell me ,how you fine-tuning BERT model? use BERT ML model?