This is an official PyTorch implementation of ELR+ method proposed in Early-Learning Regularization Prevents Memorization of Noisy Labels.

Train the network on the Symmmetric Noise CIFAR-10 dataset (noise rate = 0.8):

python train.py -c config_cifar10.json --percent 0.8

Train the network on the Asymmmetric Noise CIFAR-10 dataset (noise rate = 0.4):

python train.py -c config_cifar10_asym.json --percent 0.4

Train the network on the Asymmmetric Noise CIFAR-100 dataset (noise rate = 0.4):

python train.py -c config_cifar100.json --percent 0.4 --asym 1

The config files can be modified to adjust hyperparameters and optimization settings.

• S. Liu, J. Niles-Weed, N. Razavian and C. Fernandez-Granda "Early-Learning Regularization Prevents Memorization of Noisy Labels", 2020