def save_model(self):
        """
        Method to save the trained model.
        #ToDo: Works for English Language now. Multiple language support needs to
        # be added.

        """
        # Save the model to the outputs directory for capture
        output_dir = "outputs"
        os.makedirs(output_dir, exist_ok=True)

        # Save a trained model, configuration and tokenizer
        model_to_save = (
            self.model.module if hasattr(self.model, "module") else self.model
        )

        # If we save using the predefined names, we can load using `from_pretrained`
        output_model_file = "outputs/bert-large-uncased"
        output_config_file = "outputs/bert_config.json"

        torch.save(model_to_save.state_dict(), output_model_file)
        model_to_save.config.to_json_file(output_config_file)

        Method to save the trained model.
        #ToDo: Works for English Language now. Multiple language support needs to
        # be added.

        
utils_nlp/models/bert/sequence_classification_distributed.py