I am trying to train a resnet-18 downloaded from torchvision model downloaded using the following command
model=torchvision.models.resnet18(pretrained=False, num_classes=100)
I am only able to reach an accuracy of 58%. I am using data-augmentations and hyperparameters followed by a lot of projects 25 at github which locally specify the structure of the network instead of using the one from torchvision. I understand that the difference can arise from a lot of reasons.
What I am looking for is to know if there’s a project/set of hyperparameters which I can follow to perform well on the torchvision models. I have observed a similar trend for vgg16_bn as well.