text: Title: [BUG] For an nrms model, run_fast_eval does not return the correct prediction scores
  Body: ### Description
  
  I believe that for the nrms model, the output of `run_fast_eval` is incorrect. (See code [here](https://github.com/microsoft/recommenders/blob/98d661edc6a9965c7f42b76dc5317af3ae74d5e0/recommenders/models/newsrec/models/base_model.py#L399).)
  
  ### In which platform does it happen?
  
  Jupyter Lab running in Ubuntu 20.04.4 LTS (Focal Fossa). Using Python version 3.8.10 with tensorflow version 2.8.0.
  
  ### How do we replicate the issue?
  
  Run the following code and verify that the outputs are different (I believe they should be the same):
  
  ```
  group_impr_indexes, group_labels, group_preds = model.run_slow_eval(valid_news_file, valid_behaviors_file)
  group_impr_indexes, group_labels, group_preds = model.run_fast_eval(valid_news_file, valid_behaviors_file)
  ```
  
  Also, notice that the group_preds output of `run_slow_eval` is in the range [0,1] (as expected) while the output group_preds of `run_fast_eval` is not.
  
  
  ### Expected behavior (i.e. solution)
  
  As stated in the [NRMS paper](https://wuch15.github.io/paper/EMNLP2019-NRMS.pdf) (equation 11), the output should be click probabilities (in the range [0,1]). I think this can be fixed by adding a sigmoid function after the computation of the dot product on [line 416](https://github.com/microsoft/recommenders/blob/98d661edc6a9965c7f42b76dc5317af3ae74d5e0/recommenders/models/newsrec/models/base_model.py#L416).
  
  ### Other Comments
  