Some transformers-based models may not work
**Describe the bug**
With the update of the requirements to transformers >= 4.0.0 on the main branch, calling a model now passes `return_dict=True` by default rather than a tuple previously: https://github.com/huggingface/transformers/releases/tag/v4.0.0

The fix is simple - any transformers model call should explicitly state `return_dict=False` to maintain old functionality.

**Steps/Code to reproduce bug**
I've only looked at the text2sparql model myself - training and evaluating a model will error. I expect some of the other transformer models to do so as well.

**Expected behavior**
Model trains and evaluates properly.

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

 - Environment location: Local
 - Method of NeMo install: Installing from main branch:
```
pip install Cython
pip install git+https://github.com/NVIDIA/NeMo.git@main#egg=nemo_toolkit[nlp]
./reinstall.sh
```

**Environment details**
- OS version: Ubuntu 20.04.1
- PyTorch version: 1.8.0.dev20201207+cu110 (I'm using a RTX 3090)
- Python version: 3.8.3
