Yes, about the overfitting. I have tried this and my model went from being nicely balanced to horribly overfitted. I don’t know what to make of the information though, as its only ever validating agianst one image in this scenario. See this post: Dog Breed Identification challenge
Whereas I had achieved around 0.200 loss prior to this, after it I had 0.230 loss - but again I am not sure how to understand it 
When I submitted this “enhanced” model to kaggle it had a 0.2275 loss, so it looks like it did something like the predicted accuracy, which was not very good to say the least! Perhpas @jeremy could let us know if there is a best approach to doing this, as I struggled to piece together an approach from reading numerous posts, and likely stuffed something up!