Did anyone get good CIFAR10 results?

Author: IdoZachCreated Sep 30, 2022Updated Aug 11, 2025

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: image I'm also attaching the training results that I get (the divergent one is the validation loss): image 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