Another additional layer adds more capacity to the model, which might help.
Are you using F.softmax of an nn.Softmax module as the last non-linearity?
If so, this might be wrong for a multi-class classification use case, since e.g. nn.CrossEntropyLoss expects raw logits while nn.NLLLoss expects log probabilities created with F.log_softmax.