Updates

args and kwargs are now consistently typed throughout the code.
Re-works the way strip_training_data works in the model to allow it to be more flexible. The new function is now called trained_state_dict and will return the state of the final trained model. The function accepts arbitrary arguments for further flexibility.
Progress bars now restart correctly when training on iteration. Previously the progress bar would restart at 0 instead of using the last saved iteration.
Saved checkpoints now have epoch numbers starting at 1 instead of 0.
Improved running loss system. The model now contains a table of running losses that is automatically updated from the main loss table and is reset at the end of every iteration cycle.

Full Changelog