Hello guys!
Currently I am working with this dataset - https://www.kaggle.com/vishu53/indian-coins-dataset
This dataset has relatively less images. I have tried transfer learning using both resnet34 and resnet50 but the error rate I am getting is 0.20. This is causing my model to predict incorrect labels while predicing a single image. I have also tried data augmentation but the error doesn’t decrease at all.
With resnet34-
With resnet50-
I have using following code for Resnet34 -
learn.fit_one_cycle(8, max_lr=slice(1e-3, 1e-2))
For Resnet50 I am getting the following learning rate finder plot:
What is the learning rate I should use with this graph?
Also, I would like to have error rate less than 0.1. Peferably close to 0.05. But With all the variations I have tried of Learning Rate and Epochs, I am getting 0.2 error rate.
What can I do to resolve this issue?