code: def create_metadata(self):
      metric_mapping = infer_metric_tags_from_eval_results(
          self.eval_results
      )
  
      metadata = {}
      metadata = _insert_values_as_list(
          metadata, "language", self.language
      )
      metadata = _insert_value(metadata, "license", self.license)
      if (
          self.finetuned_from is not None
          and isinstance(self.finetuned_from, str)
          and len(self.finetuned_from) > 0
      ):
          metadata = _insert_value(
              metadata, "base_model", self.finetuned_from
          )
      metadata = _insert_values_as_list(metadata, "tags", self.tags)
      metadata = _insert_values_as_list(
          metadata, "datasets", self.dataset_tags
      )
      metadata = _insert_values_as_list(
          metadata, "metrics", list(metric_mapping.keys())
      )
      metadata["model-index"] = self.create_model_index(metric_mapping)
  
      return metadata
  
imports: import copy
  import json
  import os
  import warnings
  from dataclasses import dataclass
  from pathlib import Path
  from typing import Any, Dict, List, Optional, Union
  import requests
  import yaml
  from huggingface_hub import model_info
  from huggingface_hub.utils import HFValidationError
  from .None import __version__
  from .models.auto.modeling_auto import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES, MODEL_FOR_CAUSAL_LM_MAPPING_NAMES, MODEL_FOR_CTC_MAPPING_NAMES, MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES, MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES, MODEL_FOR_MASKED_LM_MAPPING_NAMES, MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES, MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES, MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES, MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES, MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES, MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING_NAMES, MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES, MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING_NAMES
  from .training_args import ParallelMode
  from .utils import MODEL_CARD_NAME, cached_file, is_datasets_available, is_offline_mode, is_tf_available, is_tokenizers_available, is_torch_available, logging
label_desc: Use image node_id 3 for calling the TrainingSummary obj's underlying member method code with example usage: obj.create_metadata() and returns: metadata