Did anyone get good CIFAR10 results?
Hi, thanks for providing this code. I'm trying to reproduce the CIFAR10 results from the original DDPM paper. I use 3x32x32 images, all the CIFAR data (50k frames), 2000 epochs (but I check every 100 epochs how it looks like), and I get some similar results, but not as good as the paper.
This is the result that I get:
I'm also attaching the training results that I get (the divergent one is the validation loss):
My training schedule is similar to the original except that I maximize the batch size on my GPUs. I'm using image size of 32, and U-Net options dim=64, dim_mults=(1,2,4,8).
Was anyone more successful and can share their results and tips? I think that this result is far from perfect. Thanks very much, I hope you could help me find what I'm missing.
Source: lucidrains/denoising-diffusion-pytorch