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Adaptive Stochastic Weight Averaging

Knowledge Graph Embeddings

The code is based on dice

CIFAR10 experiments

The code is based on https://github.com/kuangliu/pytorch-cifar

Train CIFAR10 with PyTorch

I'm playing with PyTorch on the CIFAR10 dataset.

Prerequisites

  • Python 3.6+
  • PyTorch 1.0+

Training

# Start training with: 
python main.py

# You can manually resume the training with: 
python main.py --resume --lr=0.01

Accuracy

Model Acc.
VGG16 92.64%
ResNet18 93.02%
ResNet50 93.62%
ResNet101 93.75%
RegNetX_200MF 94.24%
RegNetY_400MF 94.29%
MobileNetV2 94.43%
ResNeXt29(32x4d) 94.73%
ResNeXt29(2x64d) 94.82%
SimpleDLA 94.89%
DenseNet121 95.04%
PreActResNet18 95.11%
DPN92 95.16%
DLA 95.47%

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