Issue in saving the checkpoint after epoch
**Issue in saving the checkpoint after epoch**
After the epoch runs successfully it tries to save the model checkpoint file in storage and throws exception

**MisconfigurationException: ModelCheckpoint(monitor='val_loss') not found in the returned metrics: ['lr', 'train_loss']**


**Steps/Code to reproduce bug**
Following the IMDB dataset structures put up custom dataset for classification model training and run the training epochs. While it tries to save the checkpoint exception is generated.

**Expected behavior**
Model should be saved to the storage after each epoch or number of epochs and next iteration should be running.

[Screenshot from 2021-08-27 12-57-25](https://user-images.githubusercontent.com/41611198/131109161-0252e098-3d4c-46d1-be31-b62a61d00e90.png)

**Environment overview (please complete the following information)**

 - Environment location: Kubernetes pod
 - Method of NeMo install: NeMo image as base

**Additional context**
NeMo version 1.0.1 and Python version 3.8
Model used is bert base uncased