Using more data should improve the ability to generalize. I would start by checking e.g. the preprocessing pipeline and make sure that e.g. the normalization is applied in the training and validation use case. A quick test might be to use the training dataset in the validation loop and check it’s performance.


I’m unsure if the model is only overfitting after the first epoch, since epoch0 already shows a worse validation accuracy than the training one.