Save the optimizer status for future retraining

[diegovalenzuelaiturra]

I think it would be useful if the optimizer state was also saved, for a future retraining from a checkpoint

• torch.save(optimizer.state_dict(), path_to_optimizer)

[lorenlugosch]

Good call---I'll work on adding that. Also, when you restart training, it loads the previous state but starts at epoch 1, so that needs to be fixed too.