def make_train_state(save_path, early_stopping_patience):
    """Create training state dictionary to keep track of improvements during training."""
    return {'stop_early': False,
            'early_stopping_step': 0,
            'early_stopping_patience': early_stopping_patience,
            'steps': 0,
            'min_val_loss': float('Inf'),
            'train_loss': [],
            'val_loss': [],
            'save_path': save_path}