Skip to content

fumihwh/pytorch-cifar

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

45 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

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%
PreActResNet18 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

About

95.16% on CIFAR10 with PyTorch

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%