Hi, I just want to check all the experiments details and make sure I didn't miss any part(?
1) Training Phase : use SimCLR (two encoder branches) to train on ImageNet for 1000 epochs to get a init pretrained weights.
2) Fine-Tuned : load the init pretrained weights on the resnet18(50/101/...) with freezed parameters and concate with a linear classifier, and train the classifier with CIFAR10/STL10 training dataset for 100 epochs.
3) Test Phase : freeze all the encoder, classifier parameters, and test on the CIFAR10/STL10 testing dataset.
Is this the way how you get the top1 acc in the README?
Hi, I just want to check all the experiments details and make sure I didn't miss any part(?
1) Training Phase : use SimCLR (two encoder branches) to train on ImageNet for 1000 epochs to get a init pretrained weights. 2) Fine-Tuned : load the init pretrained weights on the resnet18(50/101/...) with freezed parameters and concate with a linear classifier, and train the classifier with CIFAR10/STL10 training dataset for 100 epochs. 3) Test Phase : freeze all the encoder, classifier parameters, and test on the CIFAR10/STL10 testing dataset.
Is this the way how you get the top1 acc in the README?