Quick question:
I’m wondering if there is some reasonable range for per class weights (for dealing with unbalanced class representations)? Or are they somewhere later normalized? I’m specifically talking about weights attribute of nn.CrossEntropyLoss().
If there are many classes (say 7000), the approach to calculate weights per class as total_number_of_samples / number_of_samples_in_class results in big weights (say > 25000 for biggest classes). Isn’t that a problem?