The model reaches a maximum accuracy of 92.26% on CIFAR-10 using One Cycle Policy for Learning Rate.
- Loss Function: Cross Entropy Loss (combination of
nn.LogSoftmax
andnn.NLLLoss
) - Optimizer: SGD
- Momentum: 0.9
- L2 regularization factor: 0.01
- LR Range Test
- Start LR: 1e-6
- End LR: 0.02
- Number of epochs: 10
- Comparison Metric: Accuracy
- One Cycle Policy
- Max LR: 0.02
- Min LR: 0.002
- Increase LR step size: 5 epochs
- Epochs: 24
- Batch Size: 512
The following data augmentation techniques were applied to the dataset during training:
- Padding
- Random Crop
- Flip LR
- CutOut
Install the required packages
$ pip install -r requirements.txt
Upload the files in the root folder and select Python 3 as the runtime type and GPU as the harware accelerator.
- Rakhee (Canvas ID: 25180625)
- Shantanu Acharya (Canvas ID: 25180630)