The predicted output remains empty during training. Training loss is decreasing but validation loss is constant
**Describe the bug**

I am training stt_en_conformer_ctc_large on my custom datset+librispeech dev and test splits. Currently, half of epoch 0 has completed but the best value of WER is 1 and logs show epty in predicted. I am a beginner and do not understand the ASR process fully so it must be something that I am doing wrong. Can someone help me?. I am tokenizing using SPE with a vocab size of 15000, and am using the default training script from
```
https://github.com/NVIDIA/NeMo/blob/main/examples/asr/asr_ctc/speech_to_text_ctc_bpe.py
```
and the config from 
```
https://github.com/NVIDIA/NeMo/blob/main/examples/asr/conf/conformer/conformer_ctc_bpe.yaml
``` 
with some fields changed according to my need

**Steps/Code to reproduce bug**

Running the above training script with the config file which contains all the relevant path information.

**Expected behavior**

At least something should be predicted in logs

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

 - Environment location: AWS
 - Method of NeMo install: [pip install nemo_toolkit["all"]

**Environment details**

If NVIDIA docker image is used you don't need to specify these.
Otherwise, please provide:
- OS version Ubuntu 20.04
- PyTorch version 11.7
- Python version 3.8

**Additional context**

Add any other context about the problem here.
Tesla T4
