title: Would it be possible that test result is better than validation result?
body: <p>I'm training a CNN for a classification task and I split the dataset into three parts: 70% for training, 15% for validation and final 15% for testing. I use the training set to train the network and use the validation set to choose the hyper-parameters. After all the works, I tested my model using the test set, however, it turned out the model performed better on the test set than the validation set(one got 85% accuracy and the other got 80% accuracy).</p>
  
  <p>Would it be possible or I did something wrong? Since I put much effort on improving the model performance on validation set while the test set is invisible during the whole process of model training.</p>