I'm playing with PyTorch on the CIFAR10 dataset.
- Python 3.6+
- PyTorch 1.0+
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% |
DenseNet121 | 95.04% |
PreActResNet18 | 95.11% |
DPN92 | 95.16% |
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