I am using msggan, but I get worse results than in the paper.
I tried celebHQ whole dataset (100k samples), with resolution 64x64 and 128x,128.
For 64x64 I have done ~250 epochs
and for 128x128 ~ 47epochs.
Results are not bad (much better than DCGAN), but they have worse texture quality than in msggan paper, and only 30% samples looks realistic. 70% samples look like monster (weird faces, weird artifacts etc).
I am using 3060ti
batch size 12
Rest of hyperparameters are default like in repo (LR = 0.003, latent_size = 512, loss_function = relativistic-hinge, flip-augment=True)
Any ideas? Can anyone share results?
I am attaching my 64x64 results (every epoch is 100k samples, so 251 epoch is 25mln real samples)
Hello!
I am using msggan, but I get worse results than in the paper.
I tried celebHQ whole dataset (100k samples), with resolution 64x64 and 128x,128. For 64x64 I have done ~250 epochs and for 128x128 ~ 47epochs.
Results are not bad (much better than DCGAN), but they have worse texture quality than in msggan paper, and only 30% samples looks realistic. 70% samples look like monster (weird faces, weird artifacts etc).
I am using 3060ti batch size 12 Rest of hyperparameters are default like in repo (LR = 0.003, latent_size = 512, loss_function = relativistic-hinge, flip-augment=True)
Any ideas? Can anyone share results?
I am attaching my 64x64 results (every epoch is 100k samples, so 251 epoch is 25mln real samples)
and 47 epoch for 256x256