It’s a 4 class classification.
The number of samples for the classes in train set look something like: [15%, 40%,  30%, 15%]
Validation set is similar.
Orange curve is train accuracy and blue curve is validation accuracy
MLP without weighted Loss


MLP with weighted Loss


Ok, the diagonal numbers in the matrix have increased using weighted loss – which is a good sign. 
Any inputs on how I can improve train and validation accuracy? Unfortunately, I don’t have the privilege of getting more train data. I’m training a MLP: [70 6000 4] without weighted loss, just to see if I’m able to overfit on train data.
Do let me know your thoughts. Thank you!