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run.sh
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run.sh
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# CIFAR10
python train.py --arch resnet32 /
--dataset cifar10 --data_path './dataset/data_img' /
--gpu 3 /
--loss_type 'FeaBal' --batch_size 64 --learning_rate 0.1 --lambda_ 60
# CIFAR100
python train.py --arch resnet32 /
--dataset cifar100 --data_path './dataset/data_img' /
--gpu 3 /
--loss_type 'FeaBal' --batch_size 64 --learning_rate 0.1 --lambda_ 60
# ImageNet
python train.py --arch resnet50 /
--dataset imagenet --data_path './dataset/data_txt' --img_path '/home/datasets/imagenet/ILSVRC2012_dataset' /
--gpu 3 /
--loss_type 'FeaBal' --batch_size 512 --learning_rate 0.2 --lambda_ 150
# iNaturalist
python train.py --arch resnet50 /
--dataset inat --data_path './dataset/data_txt' --img_path '/home/datasets/iNaturelist2018' /
--gpu 3 /
--loss_type 'FeaBal' --batch_size 512 --learning_rate 0.2 --lambda_ 150
# Places
python train.py --arch resnet152_p /
--dataset place365 --data_path './dataset/data_txt' --img_path '/home/datasets/Places365' /
--gpu 3 /
--loss_type 'FeaBal' --batch_size 512 --learning_rate 0.2 --lambda_ 150