Description
I'm trying to replicate your results for ResNet18 on ImageNet 1k. I'm using the default hyperparameters in your train_resnet.py
and all of the same augmenters (for aug-level=2), but can't achieve the accuracy that you report. The most obvious issue is that if I use your default learning rate of 0.1, the net fails to learn anything, even though I'm using the same batch size (256), momentum (0.9), weight decay (0.0001), etc. I have to set a learning rate to 0.001 for it to start learning well, but even then, the accuracy tops out at about 80% for Top 5 and 55% for Top 1.
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I see in the code that these are the default parameters for ResNet50. Did you change any of them for ResNet18?
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Is the data that you are using standard ImageNet, or did you modify it before training (by normalizing, etc.)?