Hi there! Thanks for sharing your work! The paper is very impressive!

I ran the cifar_experiment.sh with cifar data, resnet model, and fmix. However, I'm a little confused about two things:
1- Training accuracy is much lower than validation accuracy. Is this an artifact of using the masks and therefore making the learning phase much harder? Am I missing something? I confess that I'm not 100% sure I understand all the moving parts.
2- When it runs, it says running_mixup_acc etc. I had selected fmix so it's confusing to see mixup here. Can you help me understand this?

Thank you in advance!