I have split the database available into 70% training, 15% validation, and 15% test, using holdout validation. I have trained the model and got the following results: training accuracy 100%, validation accuracy 97.83%, test accuracy 96.74%
In another trial for training the model, I got the following results: Training accuracy 100%, validation accuracy 97.61%, test accuracy 98.91%
The same data split is used in each run. Which model should I choose, the first case in which the the test accuracy is lower than the validation? or the second case in which the test is higher than the validation?