deep transformation

Train CIFAR10 with PyTorch

I'm playing with PyTorch on the CIFAR10 dataset.

Pros & cons

Pros:

• Built-in data loading and augmentation, very nice!
• Training is fast, maybe even a little bit faster.
• Very memory efficient!

Cons:

• No progress bar, sad :(
• No built-in log.

Accuracy

Model	Acc.
VGG16	92.64%
ResNet18	93.02%
ResNet50	93.62%
ResNet101	93.75%
ResNeXt29(32x4d)	94.73%
ResNeXt29(2x64d)	94.82%
DenseNet121	95.04%
ResNet18(pre-act)	95.11%
DPN92	95.16%

Learning rate adjustment

I manually change the lr during training:

• 0.1 for epoch [0,150)
• 0.01 for epoch [150,250)
• 0.001 for epoch [250,350)

Resume the training with python main.py --resume --lr=0.01

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