Train LM with a large file
I try to train ~5.6G data with ~700M validation 

Using this below command:

 python /workspace/data/NeMo/examples/nlp/language_modeling/bert_pretraining.py 
        --config-name=/workspace/data/NeMo/examples/nlp/language_modeling/conf/bert_pretraining_from_text_config.yaml 
        model.train_ds.data_file="/workspace/data/NeMo/lm/data/public-data/train.txt"  
        model.validation_ds.data_file="/workspace/data/NeMo/lm/data/public-data/val.txt"  
        model.train_ds.batch_size=128 
        model.optim.lr=5e-5 
        trainer.max_epochs=1 
        trainer.gpus=1 
      
Then it show this error

GPU available: True, used: True
TPU available: False, using: 0 TPU cores
Using native 16bit precision.
[NeMo I 2022-08-09 02:50:20 exp_manager:216] Experiments will be logged at /workspace/data/NeMo/public-data-lm/nemo_experiments/PretrainingBERTFromText/2022-08-09_02-50-20
[NeMo I 2022-08-09 02:50:20 exp_manager:563] TensorboardLogger has been set up
  0%|                                                              | 0/1 [00:48<?, ?it/s]
Traceback (most recent call last):
  File "/workspace/data/bew/NeMo/examples/nlp/language_modeling/bert_pretraining.py", line 31, in main
    bert_model = BERTLMModel(cfg.model, trainer=trainer)
  File "/opt/conda/lib/python3.6/site-packages/nemo/collections/nlp/models/language_modeling/bert_lm_model.py", line 63, in __init__
    super().__init__(cfg=cfg, trainer=trainer)
  File "/opt/conda/lib/python3.6/site-packages/nemo/core/classes/modelPT.py", line 127, in __init__
    self.setup_training_data(self._cfg.train_ds)
  File "/opt/conda/lib/python3.6/site-packages/nemo/collections/nlp/models/language_modeling/bert_lm_model.py", line 192, in setup_training_data
    else self._setup_dataloader(train_data_config)
  File "/opt/conda/lib/python3.6/site-packages/nemo/collections/nlp/models/language_modeling/bert_lm_model.py", line 235, in _setup_dataloader
    short_seq_prob=cfg.short_seq_prob,
  File "/opt/conda/lib/python3.6/site-packages/nemo/collections/nlp/data/language_modeling/lm_bert_dataset.py", line 90, in __init__
    sentence_indices[filename] = array.array("I", newline_indices)
OverflowError: unsigned int is greater than maximum

I can train with the small size data, training is fine but the large file I got this error

**Environment details**
- Ubuntu
- Pytorch 1.8.0a0+17f8c32
- Pytorch-lightning 1.2.10
- Python 3.6.10
- DGX-V100 32G
- NeMO 1.0.0rc1
