Your validation set is huge. I suspect that what's taking time is the computation of the first validation accuracy metric. If finalization takes 15 minutes then it means processing 30000 images takes at least 15 minutes, which means 7000 images is going to take at least 3.5 minutes, and most likely more. Validation sets should be the smallest you can get away with for statistically significant metrics. Use a larger test set on the final network to check the quality of the output, rather than relying on validation during training.
Why not run the MATLAB profiler during training and tell us what the report says? It could be other things, like loading and preprocessing data.
The 15 minutes at the end is the finalization - your network has batch normalization layers and the TrainedMean and TrainedVariance population statistics are being computed from your complete dataset.
