A minor change to fix a bug when using torch.compile()
Author: DongHande
Pull request: yes

When using model = torch.compile(model), the class of new model is changed to OptimizedModule. The function, inspect.signature(self.model.forward), will return ["args", "kargs"], withou "input_ids", "labels", and so on. This will result in the dataset remove all columns and the data sample is a empty dict, and incurs bug when forward propagation. By using "self.model._orig_mod.forward", above problem can be fixed.

# What does this PR do?

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With model = torch.compile(model) operation, the class of the model will change from previous model to "torch._dynamo.eval_frame.OptimizedModule", and thus inspect.signature(self.model.forward) will return ["args", "kargs"] instead of expectable variable names of the model. This results in that the data columns are removed and the incurs bug during training. This pull request can fix this bug. 


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## Who can review?

This is a minor change, and anyone can review it. 

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