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ELR+
This is an official PyTorch implementation of ELR+ method proposed in Early-Learning Regularization Prevents Memorization of Noisy Labels.
Usage
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.
References
- S. Liu, J. Niles-Weed, N. Razavian and C. Fernandez-Granda "Early-Learning Regularization Prevents Memorization of Noisy Labels", 2020