code: def tfrbert_exp() -> cfg.ExperimentConfig:
      """Defines a TFR-BERT experiment."""
      config = cfg.ExperimentConfig(
          task=premade.TFRBertConfig(
              train_data=premade.TFRBertDataConfig(),
              validation_data=premade.TFRBertDataConfig(
                  is_training=False, drop_remainder=False
              ),
          ),
          trainer=cfg.TrainerConfig(
              optimizer_config=optimization.OptimizationConfig(
                  {
                      "optimizer": {
                          "type": "adamw",
                          "adamw": {
                              "weight_decay_rate": 0.01,
                              "exclude_from_weight_decay": [
                                  "LayerNorm",
                                  "layer_norm",
                                  "bias",
                              ],
                          },
                      },
                      "learning_rate": {
                          "type": "polynomial",
                          "polynomial": {
                              "initial_learning_rate": 3e-5,
                              "end_learning_rate": 0.0,
                          },
                      },
                      "warmup": {"type": "polynomial"},
                  }
              )
          ),
          restrictions=[
              "task.train_data.is_training != None",
              "task.validation_data.is_training != None",
          ],
      )
      config.task.model.encoder.type = "bert"
      return config
  
label_desc: Use image node_id 1 for calling a global function with example usage: tfrbert_exp() and returns: config