PyTorch Implementation of CutMix

Usage

$ python train.py --depth 20 --use_cutmix --outdir results

Results on CIFAR-10

Model	Test Error (median of 3 runs)	Training Time
WRN-20-4	4.56	1h22m
WRN-20-4, CutMix (alpha=1)	3.62	1h22m

• These models were trained for 300 epochs with batch size 128, initial learning rate 0.2, and cosine annealing.
• Test errors reported above are of the last epoch.
• These experiments were done using Tesla V100.

w/o CutMix

$ python -u train.py --depth 20 --base_channels 64 --base_lr 0.2 --scheduler cosine --seed 7 --outdir results/wo_cutmix/00

w/ CutMix

$ python -u train.py --depth 20 --base_channels 64 --base_lr 0.2 --scheduler cosine --seed 7 --use_cutmix --cutmix_alpha 1.0 --outdir results/w_cutmix/00

References

• Yun, Sangdoo, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo. "CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features." arXiv preprint arXiv:1905.04899 (2019). arXiv:1905.04899