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.
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