code: def get_bert_default_config() -> Dict:
      return {
          "cuda": False,
          "pretrain_cls": False,
          "batch_size": 32,
          "num_epochs": 1,
          "num_pretrain_epochs": 10,
          "save_best_model": False,
          "hidden_dim": 768,
          "embedding_dimension": 768,
          "gen_embedding_dim": 768,
          "label_embedding_dim": 400,
          "fixed_classifier": False,
          "lambda_sparsity": 1.0,
          "lambda_continuity": 0,
          "lambda_anti": 1.0,
          "target_sparsity": 0.3,
          "training_stop_thresh": 5,
          "count_pieces": 4,
          "fine_tuning": True,
          "bert_explainers": True,
          "dropout_rate": 0.3,
          "layer_num": 1,
          "embedding_dim": 100,
          "exploration_rate": 0.05,
          "lambda_acc_gap": 1.2,
          "lr": 2e-4,
          "train_batch_size": 32,
          "test_batch_size": 32,
      }
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_bert_default_config() and returns: dict