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I have read the paper and it seems that you are treating this as a regression task not a classification task.
I know that the final labels are binary and the ground truth summary is a continuous set between 0 and 1.
My question is since you are using a sigmoid output and f-score metric shouldn't that be called a classification model and not regression
and if so how is using MSE loss suitable in this case
I tried to replace MSE with BCE but i got slightly worse results.
The text was updated successfully, but these errors were encountered:
I have read the paper and it seems that you are treating this as a regression task not a classification task.
I know that the final labels are binary and the ground truth summary is a continuous set between 0 and 1.
My question is since you are using a sigmoid output and f-score metric shouldn't that be called a classification model and not regression
and if so how is using MSE loss suitable in this case
The text was updated successfully, but these errors were encountered: