Trained the first ShiftGuard baseline CNN on all 50,000 CIFAR-10 training images using my AMD GPU. Over 5 epochs, training accuracy increased from 53.47% to 80.57%, while the loss dropped from 1.3057 to 0.5520. I used the optimizer Adam with a learning rate of 0.001 and normalized the CIFAR-10 images before training. The trained weights are now saved, so the next step is evaluating the model on the unseen test set and measuring its prediction confidence.