Hi, practicing a lesson I tried to train a cnn_learner and predict if a car was one of (sports, suv, mini van) and I got very odd error_rates variation with input size:
- (20%) with input image size of 128, (I even tried unfreezing and using slice(1e-7, 1e-4) for fit())
- (6%) with input image size of 224 (only fine-tuned) and
- (15%) with input image size of 512 (after unfreeze and fit(5, slice(1e-7,1e-4))
Can anyone explain why that is? I assumed it could have to do with the original training input dimensions of the resnet18 whose parameters were being used but I’ve found posts stating that it did not matter what dimensions it was trained on!