weiaicunzai / pytorch-cifar100

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)

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Cannot achieve the comparable accuracy results with the provided

EddieEduardo opened this issue · comments

Hello, thanks for code sharing.

I use Cifar100 to train and test the ShuffleNetV2, but the accuracy I got is just 0.499, all the parameter setting is consistent with the provided in READMe, which are, init lr = 0.1 divide by 5 at 60th, 120th, 160th epochs, train for 200 epochs with batchsize 128 and weight decay 5e-4, Nesterov momentum of 0.9 (I have run 2 times on my end and 0.499 is the best accuracy).

Looking forword to anyone's reply, thanks a lot again!

Plus, my PyTorch version is 1.8.0.

After repeated experiments, this code fails to achieve the described accuracy in the CIFAR100.
You can set a higher input size for training, which can achieve a higher accuracy.

For densenet161, Top 1 err: tensor(0.2350) Top 5 err: tensor(0.0520)