I just finished the intro chapter in the free book and, in the fastai spirit, I decided to build my first model that recognises whether an image has something fluffy in it (yes, you read that right!). However, I can’t get the model the yield an error rate of less than 20%.
Things I’ve tried:
- Increasing the number of images fed into it (currently 283).
- Tweaking the number of epochs.
- Changing the number of layers in the resnet model architecture I’m using.
Are there any other quick and easy changes I could make?