Trying to understand the right approach for a multi-class classification problem

I am working with a music genre classifier problem where the dependent variable has 11 classes and the data is imbalanced(Added picture).

The problem I am facing is, as far as I know, the best way to deal with these types of problems is to oversample or undersample. But, the issue is this is not a binary classification problem ,rather multi-class classification problem.

The second approach that I found out was adjusting weights(either by using the argument class\_weight = 'balanced' …

classification classifier data datascience deal music types