You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I see the Self-supervised pretrained learning (SSP).
There are many models in SSP.
CE(Uniform) + SSP
CE(Balanced) + SSP
Where can I setting the CB in train.py code?
In my opinion, per_cls_weights seems to set a uniform or balance.
Does the CB setting mean 'Reweight' in args.train_rule?
Hi, thanks for your interest. "CE(Balanced)" means CE with class-balanced sampling, which corresponds to "Resample" as for args.train_rule. You can also choose "Reweight", which means re-weighting the loss for each class according to # of samples, by changing args.train_rule.
I see the Self-supervised pretrained learning (SSP).
There are many models in SSP.
Where can I setting the CB in train.py code?
In my opinion, per_cls_weights seems to set a uniform or balance.
Does the CB setting mean 'Reweight' in args.train_rule?
The text was updated successfully, but these errors were encountered: