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TRAINING.md

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CIFAR-10

AlexNet

python cifar.py -a alexnet --epochs 164 --schedule 81 122 --gamma 0.1 --checkpoint checkpoints/cifar10/alexnet

VGG19 (BN)

python cifar.py -a vgg19_bn --epochs 164 --schedule 81 122 --gamma 0.1 --checkpoint checkpoints/cifar10/vgg19_bn

ResNet-110

python cifar.py -a resnet --depth 110 --epochs 164 --schedule 81 122 --gamma 0.1 --wd 1e-4 --checkpoint checkpoints/cifar10/resnet-110

ResNet-1202

python cifar.py -a resnet --depth 1202 --epochs 164 --schedule 81 122 --gamma 0.1 --wd 1e-4 --checkpoint checkpoints/cifar10/resnet-1202

PreResNet-110

python cifar.py -a preresnet --depth 110 --epochs 164 --schedule 81 122 --gamma 0.1 --wd 1e-4 --checkpoint checkpoints/cifar10/preresnet-110

ResNeXt-29, 8x64d

python cifar.py -a resnext --depth 29 --cardinality 8 --widen-factor 4 --schedule 150 225 --wd 5e-4 --gamma 0.1 --checkpoint checkpoints/cifar10/resnext-8x64d

ResNeXt-29, 16x64d

python cifar.py -a resnext --depth 29 --cardinality 16 --widen-factor 4 --schedule 150 225 --wd 5e-4 --gamma 0.1 --checkpoint checkpoints/cifar10/resnext-16x64d

WRN-28-10-drop

python cifar.py -a wrn --depth 28 --depth 28 --widen-factor 10 --drop 0.3 --epochs 200 --schedule 60 120 160 --wd 5e-4 --gamma 0.2 --checkpoint checkpoints/cifar10/WRN-28-10-drop

DenseNet-BC (L=100, k=12)

Note:

  • DenseNet use weight decay value 1e-4. Larger weight decay (5e-4) if harmful for the accuracy (95.46 vs. 94.05)
  • Official batch size is 64. But there is no big difference using batchsize 64 or 128 (95.46 vs 95.11).
python cifar.py -a densenet --depth 100 --growthRate 12 --train-batch 64 --epochs 300 --schedule 150 225 --wd 1e-4 --gamma 0.1 --checkpoint checkpoints/cifar10/densenet-bc-100-12

DenseNet-BC (L=190, k=40)

python cifar.py -a densenet --depth 190 --growthRate 40 --train-batch 64 --epochs 300 --schedule 150 225 --wd 1e-4 --gamma 0.1 --checkpoint checkpoints/cifar10/densenet-bc-L190-k40

CIFAR-100

AlexNet

python cifar.py -a alexnet --dataset cifar100 --checkpoint checkpoints/cifar100/alexnet --epochs 164 --schedule 81 122 --gamma 0.1

VGG19 (BN)

python cifar.py -a vgg19_bn --dataset cifar100 --checkpoint checkpoints/cifar100/vgg19_bn --epochs 164 --schedule 81 122 --gamma 0.1

ResNet-110

python cifar.py -a resnet --dataset cifar100 --depth 110 --epochs 164 --schedule 81 122 --gamma 0.1 --wd 1e-4 --checkpoint checkpoints/cifar100/resnet-110

ResNet-1202

python cifar.py -a resnet --dataset cifar100 --depth 1202 --epochs 164 --schedule 81 122 --gamma 0.1 --wd 1e-4 --checkpoint checkpoints/cifar100/resnet-1202

PreResNet-110

python cifar.py -a preresnet --dataset cifar100 --depth 110 --epochs 164 --schedule 81 122 --gamma 0.1 --wd 1e-4 --checkpoint checkpoints/cifar100/preresnet-110

ResNeXt-29, 8x64d

python cifar.py -a resnext --dataset cifar100 --depth 29 --cardinality 8 --widen-factor 4 --checkpoint checkpoints/cifar100/resnext-8x64d --schedule 150 225 --wd 5e-4 --gamma 0.1

ResNeXt-29, 16x64d

python cifar.py -a resnext --dataset cifar100 --depth 29 --cardinality 16 --widen-factor 4 --checkpoint checkpoints/cifar100/resnext-16x64d --schedule 150 225 --wd 5e-4 --gamma 0.1

WRN-28-10-drop

python cifar.py -a wrn --dataset cifar100 --depth 28 --depth 28 --widen-factor 10 --drop 0.3 --epochs 200 --schedule 60 120 160 --wd 5e-4 --gamma 0.2 --checkpoint checkpoints/cifar100/WRN-28-10-drop

DenseNet-BC (L=100, k=12)

python cifar.py -a densenet --dataset cifar100 --depth 100 --growthRate 12 --train-batch 64 --epochs 300 --schedule 150 225 --wd 1e-4 --gamma 0.1 --checkpoint checkpoints/cifar100/densenet-bc-100-12

DenseNet-BC (L=190, k=40)

python cifar.py -a densenet --dataset cifar100 --depth 190 --growthRate 40 --train-batch 64 --epochs 300 --schedule 150 225 --wd 1e-4 --gamma 0.1 --checkpoint checkpoints/cifar100/densenet-bc-L190-k40

ImageNet

ResNet-18

python imagenet.py -a resnet18 --data ~/dataset/ILSVRC2012/ --epochs 90 --schedule 31 61 --gamma 0.1 -c checkpoints/imagenet/resnet18

ResNeXt-50 (32x4d)

(Originally trained on 8xGPUs)

python imagenet.py -a resnext50 --base-width 4 --cardinality 32 --data ~/dataset/ILSVRC2012/ --epochs 90 --schedule 31 61 --gamma 0.1 -c checkpoints/imagenet/resnext50-32x4d