Distributed training via Horovod does not make learning faster
**Describe the bug**
I run [text classification with bert example](https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/text_classification/text_classification_with_bert.py). Training is done well. I got approximately %90 accuracy after first epoch. Then I tried to run the same example with [horovod](https://github.com/horovod/horovod). My change is written below:



Change [line 116](https://github.com/NVIDIA/NeMo/blob/c03f87d47fc57abc89c0ebf859fccba397dd0f8e/examples/nlp/text_classification/text_classification_with_bert.py#L116):
`trainer = pl.Trainer(plugins=[NLPDDPPlugin()], **cfg.trainer)` to `trainer = pl.Trainer(strategy="horovod", **cfg.trainer)`. 

Change [config file](https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/text_classification/conf/text_classification_config.yaml): 
model.train_ds.file_path = path/to/train
model.validation_ds.file_path = path/to/test
model.train_ds.batch_size = 8
model.validation_ds.batch_size = 8
model.dataset.num_classes = 2
trainer.devices = 1
trainer.max_epochs = 1

Then I run 2 training with this commands:
`horovodrun -np 1 -H localhost:1 --verbose --start-timeout 300 python text_classification_with_bert.py`
and
`horovodrun -np 2 -H localhost:2 --verbose --start-timeout 300 python text_classification_with_bert.py`

For second one, I also changed `trainer.devices` to 2 in config file.

First training took 15:06 min and second training took 22:00 min.

**Expected behavior**
I expect that second training should take less time.

**Environment overview**
horovod: 0.24.3
pytorch-lightning: 1.6.3
pytorch: 1.11.0
nemo-toolkit: 1.8.2