If it’s converged on validation very flatly, it’s likely converged at a local minimum possibly for reasons I mentioned above… but also you can try adjusting hyper parameters, choosing curated weight intitializations (not pretrained), data augmentation, and the plethora of techniques that fall into the broad category of adversarial training.