I built a model with 470,000 parameters for image classification. This model was trained on CIFAR-100 for 400 epochs. I used learning rate scheduler, dropout, Random Data Augmentation (MixUp & CutMix) with 50% probability, label smoothing, warmup (10 epochs) in the model.

The test accuracy is 70%, while the training accuracy is 45%.

Does the higher test accuracy compared to training accuracy indicate a problem?

I have trained the model multiple times and consistently achieved the same accuracy.