diff --git a/ludwig/models/llm.py b/ludwig/models/llm.py
index c632cccc1db..d74a16e56c0 100644
--- a/ludwig/models/llm.py
+++ b/ludwig/models/llm.py
@@ -226,24 +226,6 @@ def initialize_adapter(self):
                 from peft import MODEL_TYPE_TO_PEFT_MODEL_MAPPING, PeftConfig
 
                 peft_config = PeftConfig.from_pretrained(self.config_obj.adapter.pretrained_adapter_weights)
-                peft_dict = peft_config.to_dict()
-
-                # Need to update the peft config with some of the values from config_obj because not all of them are set
-                for param_name, param_value in self.config_obj.adapter.to_config().to_dict().items():
-                    # Not all parameters are supported by all models, so we only add the parameter to the load kwargs
-                    # if it is supported by the model.
-                    if param_value is None:
-                        # param_name and param_value come from the config object and contain default
-                        # values for the adapter. Examples of parameters with missing values might be:
-                        # 'auto_mapping', 'base_model_name_or_path', and 'task_type'.
-                        # Note that some of these values might already be set in peft_config, which comes from HF
-                        # directly (specifically, adapter_config.json in the model repo), and we don't want to override
-                        # those values with None.
-                        continue
-                    if param_name not in peft_dict:
-                        # If any parameters are not set in adapter_config.json in HF, we want to populate them with the
-                        # appropriate default values.
-                        setattr(peft_config, param_name, param_value)
 
                 self.model = MODEL_TYPE_TO_PEFT_MODEL_MAPPING[peft_config.task_type].from_pretrained(
                     self.model, self.config_obj.adapter.pretrained_adapter_weights