code: def check(self) -> Dict[str, List]:
      errors: Dict[str, List] = {"title": [], "message": []}
  
      if self.training.loss_function == "CrossEntropyLoss":
          if self.dataset.num_classes == 1:
              errors["title"] += [
                  "CrossEntropyLoss requires num_classes > 1"
              ]
              errors["message"] += [
                  "CrossEntropyLoss requires num_classes > 1, "
                  "but num_classes is set to 1."
              ]
      elif self.training.loss_function == "BinaryCrossEntropyLoss":
          if self.dataset.num_classes != 1:
              errors["title"] += [
                  "BinaryCrossEntropyLoss requires num_classes == 1"
              ]
              errors["message"] += [
                  "BinaryCrossEntropyLoss requires num_classes == 1, "
                  "but num_classes is set to {}.".format(
                      self.dataset.num_classes
                  )
              ]
      if self.dataset.parent_id_column not in ["None", None]:
          errors["title"] += [
              "Parent ID column is not supported for classification"
          ]
          errors["message"] += [
              "Parent ID column is not supported for classification datasets."
          ]
  
      return errors
  
imports: import os
  from dataclasses import dataclass, field
  from typing import Any, Dict, List, Tuple
  import llm_studio.src.datasets.text_causal_classification_ds
  import llm_studio.src.plots.text_causal_classification_modeling_plots
  from llm_studio.python_configs.base import DefaultConfig, DefaultConfigProblemBase
  from llm_studio.python_configs.text_causal_language_modeling_config import ConfigNLPAugmentation, ConfigNLPCausalLMArchitecture, ConfigNLPCausalLMDataset, ConfigNLPCausalLMEnvironment, ConfigNLPCausalLMLogging, ConfigNLPCausalLMTokenizer, ConfigNLPCausalLMTraining
  from llm_studio.src import possible_values
  from llm_studio.src.losses import text_causal_classification_modeling_losses
  from llm_studio.src.metrics import text_causal_classification_modeling_metrics
  from llm_studio.src.models import text_causal_classification_modeling_model
  from llm_studio.src.utils.modeling_utils import generate_experiment_name
label_desc: Use image node_id 2 for calling the ConfigProblemBase obj's underlying member method code with example usage: obj.check() and returns: errors