I just finished my Lesson 1 Part 1 2019, and was playing with this dataset from kaggle :
It contains 2357 images of 8 different categories, and I think is a very similar problem to the cats breed vs dogs breed problem in Lesson 1.
I split 20% of the train dataset for a validation dataset, and implemented resnet34.
Using model fine tuning, I selected the suitable learning rate slice, and after 40 epochs, I reached an accuracy of 78%.
Is this the best that can be achieved, or can this be improved (and how)?