def METHOD_NAME(self) -> NlpParameterSubspace:
    return NlpParameterSubspace(
        gradient_accumulation_steps=(
            _convert_to_rest_object(self.gradient_accumulation_steps)
            if self.gradient_accumulation_steps is not None
            else None
        ),
        learning_rate=_convert_to_rest_object(self.learning_rate) if self.learning_rate is not None else None,
        learning_rate_scheduler=(
            _convert_to_rest_object(self.learning_rate_scheduler)
            if self.learning_rate_scheduler is not None
            else None
        ),
        model_name=_convert_to_rest_object(self.model_name) if self.model_name is not None else None,
        number_of_epochs=(
            _convert_to_rest_object(self.number_of_epochs) if self.number_of_epochs is not None else None
        ),
        training_batch_size=(
            _convert_to_rest_object(self.training_batch_size) if self.training_batch_size is not None else None
        ),
        validation_batch_size=(
            _convert_to_rest_object(self.validation_batch_size) if self.validation_batch_size is not None else None
        ),
        warmup_ratio=_convert_to_rest_object(self.warmup_ratio) if self.warmup_ratio is not None else None,
        weight_decay=_convert_to_rest_object(self.weight_decay) if self.weight_decay is not None else None,
    )