Early stopping conditioned on metric `val_loss` isn't recognised when setting the val_check_interval
Describe the bug
Training stops when setting val_check_interval<1.0 in the Trainer class as it doesn't recognise val_loss. I get the following warning at the end of the 3rd epoch:
Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,train_loss

To Reproduce
Steps to reproduce the behavior:

Run the CoolModel example but change the trainer line to
trainer = Trainer(val_check_interval=0.5,default_save_path="test")
Training will stop at the end of the third epoch and the above warning will show.

Expected behavior
Training shouldn't stop and val_loss should be recognised.
Desktop (please complete the following information):

VM: Google Colab
Version 0.5.3.2

Additional context
This doesn't happen with 0.5.2.1 although it looks like something has changed with model saving mechanism since it only seems to save the best model in 0.5.3.2.
EDIT: Also seems to happen when setting train_percent_check<1.0