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https://github.com/yuhao318/mwh


https://github.com/yuhao318/mwh

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# Mixup Without Hesitation
This repo contains demo reimplementations of the CIFAR-100 training code in PyTorch based on the following paper:

Hao Yu, Huanyu Wang, Jianxin Wu. *Mixup Without Hesitation.*

## How to use

```
git clone https://github.com/yuhao318/mwh.git
cd mwh
CUDA_VISIBLE_DEVICES=0 python easy_mwh.py --sess mwh_shufflenetv2_0.5 --alpha 0.5
```

## Results
The following table shows accuracy with $\alpha = 0.5$ and 100 epochs in CIFAR-100:

| Model | PreAct ResNet-18 | DenseNet-161 | Wide ResNet28-10|
| :------ | ---------------: | -----------: |---------------: |
| mixup | 75.27% | 78.71% |78.86%|
| mwh | 77.00% | 79.94% |79.94%|