I have tried to compare my new backbone network with SOTA models such as DenseNet and ResNet. For fair comparison, all models need to be trained by same training protocols such as total training epoch, data augmentation, etc.
So,
I want to know the training protocol to get the reported accuracies of torch.models such as ResNet and DenseNet.
For example, I wonder whether those models were trained by default settings 1 i.e., 90 epoch, initial learning rate of 0.1, learning rate schedule, same data augmentation( flip and normalization, not color augmentation,etc) that code provides, etc.