Peter_Featherstone:

but I would expect it to be roughly the same as when it is being trained.


I think this is a shaky expectation. If a model does not reduce the value of the objective function on unseen examples after increased training, it is a sign that the model is not effective for the data.
But, it is unclear what “evaluation” means in the context of generative adversarial networks, without seeing the code that you’re working with (or a minimum viable example). GANs (from my knowledge) typically don’t have training/testing/validation passes in the way that a classifier does.
Though, I suppose StyleGAN uses Frechet inception distance to measure similarity of generated examples relative to the dataset.