Metric to use to choose between different models - Hyperparameters tuning
Essentially, the function of your testset is to evaluate the performance of your model on new data. It mimics the situation of your model being put into production. The validation set is used for optimizing your algorithm.
Personally I would recommend tuning your algorithm using your validation set and using the hyperparameters of the training epoch with the lowest validation loss. The accuracy of the model using these hyperparameters on your testset can be used to estimate the performance of your model in the 'real world'.