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I am running the model on ImageNet data from scratch, using the best config from the paper (small encoder and large decoder), training on a cluster of 56 A100 GPUs for more than a week's time, but the rFID (reconstruction FID on validation) I am getting so far is around 21, which is far from the number reported in the paper.
Could anyone get close to the rFID reported in the paper (around 1.6)?
The text was updated successfully, but these errors were encountered:
Hi,
I am running the model on ImageNet data from scratch, using the best config from the paper (small encoder and large decoder), training on a cluster of 56 A100 GPUs for more than a week's time, but the rFID (reconstruction FID on validation) I am getting so far is around 21, which is far from the number reported in the paper.
Could anyone get close to the rFID reported in the paper (around 1.6)?
The text was updated successfully, but these errors were encountered: