Strange Neural Network overfitting
I wouldn't say your model is overfitting, for two reasons:

The validation AUC is extremely high, I don't think many models end up with ~0.98 AUC in validation. This essentially means that the model is perfectly learning the task given, with the possibility of some exceptions. These exceptions might be always a thing the same, for each training experiment you've done, and for this reason you see a consistent drop of performance.
Whenever you train a model, it is normal for the validation performance to be slightly lower than the training performance, and that doesn't necessarily mean the model is overfitting, especially when the difference is around 1/1000 of AUC. I think this question might help you understand, for instance. I would say a model overfits if there is a significant drop, which I don't see here.