This is a PyTorch implementation of Google's Inception module architecture as described in the paper Rethinking the Inception Architecture for Computer Vision. This model is trained for classification on the CIFAR-10 dataset.
To train the model, run python train.py. The script will automatically download the CIFAR-10 dataset and train the model for 200 epochs. The model will be saved to model.pth after training.
Trained on T4 GPU available on Google Colab. Stored model is stored in mounted google drive and then downloaded to local machine.
To evaluate the model, run python eval.py. The script will automatically download the CIFAR-10 dataset and evaluate the model on the test set. The top-1 and top-5 error will be printed.
