Save state on train end

[gesen2egee]

Based on the current implementation, the state is saved as frequently as it is with LoRA.

However, given the significant file size of the state, even with the use of save_last_n_XX to manage and delete old states, it remains cumbersome, especially for those who need to save a large number of step versions (approximately 100-200 steps) to pick up the optimal training outcomes.

This minor modification introduces
--save_state_on_train_end allowing the preservation of only the final state at the end of training. This facilitates the continuation of training for under-trained models.

It has been observed that, compared to resuming with weights, resuming from the state provides a more stable and similar descent curve to the original training process.

[kohya-ss]

Thank you! This makes a big sense.