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Did anyone get good CIFAR10 results? #100
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nop, have been trying all day. MNIST works fine |
you can try |
How do you show the loss on the tensorboard? Could you share the code maybe? |
does someone have example code for mnist/cifar10? |
I do here, but with a different codebase:
[https://wandb.ai/capecape/train\_sd/reports/How-to-Train-a-Conditional-Diffusion-Model-from-Scratch--VmlldzoyNzIzNTQ1][https_wandb.ai_capecape_train_sd_reports_How-to-Train-a-Conditional-Diffusion-Model-from-Scratch--VmlldzoyNzIzNTQ1]
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does someone have example code for mnist/cifar10?
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What parameter is 'p2_loss_weight_gamma'? and where do we exactly use it? Can anyone highlight it in the |
Can u tell me where is |
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.

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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.
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