Over/Under Sampling for Multi-classification
You are applying  xgb and random forest to a multiclassification task and you are doing under sampling to some how try to improve your class

If i understand your histogram, that is the distribution of labels.

When you say accuracy went down for both classes you are refering to a multiclassficitaion problem right?

Answers directly to your questions:


There are same cases when over or undersampling improves your model, but there are not many. Selecting the right loss is more important.
Consider using another can also help you to improve your model.