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README.md

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-# BU_Stoch_pool
+# BU_Stoch_pool
+
+# Train CIFAR10 with PyTorch
+
+I'm playing with [PyTorch](http://pytorch.org/) on the CIFAR10 dataset.
+
+## Prerequisites
+- Python 3.6+
+- PyTorch 1.0+
+
+## Accuracy
+| Model             | Acc.        |
+| ----------------- | ----------- |
+| [VGG16](https://arxiv.org/abs/1409.1556)              | 92.64%      |
+| [ResNet18](https://arxiv.org/abs/1512.03385)          | 93.02%      |
+| [ResNet50](https://arxiv.org/abs/1512.03385)          | 93.62%      |
+| [ResNet101](https://arxiv.org/abs/1512.03385)         | 93.75%      |
+| [RegNetX_200MF](https://arxiv.org/abs/2003.13678)     | 94.24%      |
+| [RegNetY_400MF](https://arxiv.org/abs/2003.13678)     | 94.29%      |
+| [MobileNetV2](https://arxiv.org/abs/1801.04381)       | 94.43%      |
+| [ResNeXt29(32x4d)](https://arxiv.org/abs/1611.05431)  | 94.73%      |
+| [ResNeXt29(2x64d)](https://arxiv.org/abs/1611.05431)  | 94.82%      |
+| [DenseNet121](https://arxiv.org/abs/1608.06993)       | 95.04%      |
+| [PreActResNet18](https://arxiv.org/abs/1603.05027)    | 95.11%      |
+| [DPN92](https://arxiv.org/abs/1707.01629)             | 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`