CIFAR10_WideResNet22
Wide ResNet 22 model trained on the CIFAR10 image dataset.
- Data normalization, data augmentation (4px padding, random 32x32 cropping, random horizontal flipping (p=0.5)).
- Gradient clipping, Batch normalization, weight decay, learning rate scheduling, residual connections. Model trained for 20 epochs on a GPU achieves 93% test accuracy.