Hi, are you using accuracy as your metric? if so, please use f1-score as your metric and check train and valid set scores. As accuracy is not the right one to use for imbalanced data sets. Hope this helps
You can use python imgaug tool on your dataset and easily augment the dataset as you want. Also, you can use the weight parameter on your optimizer and that will affect your loss curve. Please let me know if it resolves your problem.
Hi
Yes. It will. For imgaug, it depends on your augmentation on the image. However, it may not work well on your dataset. For weights, If you don’t pass the weights the loss value, your loss value doesn’t really catch the real loss and won’t learn anything. Have you tried?