[NLP] [question/bug?] `train_loss` falling, whereas `val_loss`, `punct_f1`, `capit_f1` all increasing
@PeganovAnton Training on multiple GPUs I'm noticing that `train_loss` is decreasing, and `f1` scores are increasing, but so is `val_loss`. Is `val_loss` the right metric to be monitored? Would mean `f1` score be better suited?

What does `logits_ndim` in https://github.com/NVIDIA/NeMo/blob/fea3775c00adfacfe0a414dea15544abc96db8dc/nemo/collections/nlp/models/token_classification/punctuation_capitalization_model.py#L126
stand for? Is this initialisation still correct if one changes the number of classes, i.e. includes support for additional punctuation marks? What if the numbers of classes for punctuation and capitalisation differ?  

<img width="348" alt="image" src="https://user-images.githubusercontent.com/4784070/180222056-3f2d6dbc-6123-43a1-a4d1-c49b1651f979.png">
<img width="348" alt="image" src="https://user-images.githubusercontent.com/4784070/180222242-6fde5196-fc70-454e-86c7-fbe3c800f5a0.png">
<img width="348" alt="image" src="https://user-images.githubusercontent.com/4784070/180222345-ee0f65a2-7153-4d8e-b652-2b549e937be0.png">
<img width="348" alt="image" src="https://user-images.githubusercontent.com/4784070/180222409-27f760c0-4d4e-41ef-a58f-0a905d73862f.png">

**Environment details**

`pytorch:22.06-py3` + `nemo:1.10.0` + PR #4553 patch
