Commits on Aug 28, 2023

1. Many improvements to the resnet flax example, including: …

   1. Reaches 91% accuracy with a resnet18 model on CIFAR10, before
   we were only getting 88%. The main change that made this possible was
   to tweak the size of the convolutional kernel in the first layer, from
   7x7 (default) to 3x3. This is documented in the code, which now allows
   easily to overwrite the default kernel size.
   
   2. Runs in 50 epochs (vs 200 before), and only takes 13 min on free
   colab, vs 1 hour before.
   
   3. Removed many unused variables, and cleaned up the code.
   
   4. I'm now using a warm-up learning rate, which seems to be working
   great across different architectures and datasets.

   

   fabianp committed Aug 28, 2023
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