Testing on SVHN
kbui1993 opened this issue · comments
Hi, I tried testing the code on SVHN, but the test accuracy isn't as high as the one in the paper. For example, on Densenet-40, I managed to get to around 96.5% with 20 epochs, but I expected it to be higher than 98% according to the paper. I tried normalizing as follows to see if it makes a different, but it didn't:
train_loader = torch.utils.data.DataLoader(
datasets.SVHN('./data.SVHN', split = "train", download = True, transform =transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.4377, 0.4438, 0.4728), (0.1980, 0.2010, 0.1970)),
])),
batch_size=args.batch_size, shuffle=True, **kwargs)
test_loader = torch.utils.data.DataLoader(
datasets.SVHN('./data.SVHN', split = "test", download = True, transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.4377, 0.4438, 0.4728), (0.1980, 0.2010, 0.1970)),
])),
batch_size =args.test_batch_size, shuffle = True, **kwargs)
Did you do anything else to SVHN?
Sorry, we didn't test our code in SVNH.