What should be the labels for subword tokens in BERT for NER task?
Method 2 is the correct one. 

Leave the actual label of the word only in the first sub-token, and the other sub-tokens will have a dummy label (which in this case is 'X'). The important thing is that when calculating the loss (e.g., CELoss) and metrics (e.g., F1), this 'X' labels on the sub-tokens are not taken into account.

This is also the reason why we don't use method 1 is that otherwise, we would be introducing more labels of the type [B-count] and affecting the support number for such a class (which would make a test set no longer comparable with other models that do not increase the number of labels for such class).