How to calculate loss and accuracy?

Loss is used to calculate the gradient in back-propagation. We should keep the actual value produced by the model and use it to calculate the loss.

On the other hand, accuracy is used by human to judge on how good the model performs on certain dataset. In this case, we need to round the actual value to the expected range, e.g. expected value either [0, 1].