Using validation accuracy vs validation loss to determine best model


I notice that in the tutorials for fine tuning torchvision models. The code uses the best validation accuracy to determine the best model. Although other materials I about fine tuning models tend to use the lowest validation loss to decide which is the best model. Is there a reason that validation accuracy is being used here. Thanks for any help in advice.


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