Load the state dict on CPU to prevent unnecessary GPU memory surge
Author: HarshTrivedi
Pull request: yes

# What does this PR do?

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When loading the best checkpoint after training is finished, the code loads the weights in a `state_dict` on a GPU _before_ applying them on the model. This means that the weights use 2X GPU memory actually required, 1X for the model object, and 1X for the state_dict. This PR fixes it by using `map_location="cpu"` for loading the weights in `state_dict`.

Without this fix, one can get OOM even after the full training is done as I did. I've encountered [this issue](https://github.com/allenai/allennlp/pull/5518) before on Allennlp as well. That was also fixed in the same fashion. It's also mentioned in the pytorch docs [here](https://pytorch.org/docs/stable/generated/torch.load.html) (see the note about GPU RAM surge).


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