`intent_slot_classification_model` tutorial wont converge
I'm trying to run the `intent_slot_classification_model` and I'm not getting anywhere near the accuracy that the workbook implies I should. I'm running the tutorial from `Joint_Intent_and_Slot_Classification.ipynb`

The workbook contains the following markedown

```
After training for 5 epochs, which should take no more than few minutes, you can expect training precision for this data set to be around these numbers (the accuracy will gradually continue to improve for this dataset up to about 50 epochs of training): 

Intents:

    micro avg                                               85.04      85.04      85.04       1076
    macro avg                                               81.13      80.81      79.36       1076
    weighted avg                                            84.10      85.04      83.54       1076
    
Slots:

    -------------------
    micro avg                                               89.10      89.10      89.10       7199
    macro avg                                               21.86      18.56      18.18       7199
    weighted avg                                            84.42      89.10      86.01       7199
```

But I'm not able to reproduce this, the training / eval loss is stuck around 4.12 and the precision/recall/f1 is really low (less than 2%) - I don't actually get any improvement after the first epoch.

I've tried on bare-metal and aws sagemaker with the exact same results.

**Expected behavior**

Expect much better precision/recall when running tutorial workbook

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

 - Environment location: AWS Sagemaker (Pytorch 2.0.0 Python 3.10 GPU Optimised)
 - Method of NeMo install: [pip install or from source]. Ran the install command from the workbook

```
BRANCH = 'stable'
!python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[nlp]
```

 - If method of install is [Docker], provide `docker pull` & `docker run` commands used

**Environment details**

AWS Sagemaker (Pytorch 2.0.0 Python 3.10 GPU Optimised)

(same results running on bare metal with torch 2.0.1 with 3090 RTX GPU)

Note I don't have Apex installed, I suspect perhaps I'm using a newer version of lightning that the one that was used when the notebook was created but not really sure?