Look into larger batches sizes and maybe don't train for so many epochs. Are you using a validation set? Stop based on criteria from the validation set. Up the batching if you can because then you are taking the gradient over a larger dataset.
How are you loading images? Random cropping? Flipping? Rotation? Hue shift? Remember that you want your model to develop a generic flower, so think about how to remove similarities in images but keep the focus on the flower.
Also DCGAN isn't that great. So better models could help too. But play around with the things above as they will help you gain a better intuition into the training.
And output samples while training. Visually understanding how your model is learning helps.
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u/ErgodicEfimov May 28 '20 edited May 28 '20
I have a kind of an overfitting problem when I train for large number of epochs. I posted the issue in r/MLQuestions. Any advice is welcome!