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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
The text was updated successfully, but these errors were encountered:
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
The text was updated successfully, but these errors were encountered: