diff --git a/llmfoundry/callbacks/hf_checkpointer.py b/llmfoundry/callbacks/hf_checkpointer.py
index 5103a13d42..c9a56f0c1f 100644
--- a/llmfoundry/callbacks/hf_checkpointer.py
+++ b/llmfoundry/callbacks/hf_checkpointer.py
@@ -114,7 +114,7 @@ def _maybe_get_license_filename(
 
 def _log_model_multiprocess(
     mlflow_logger: MLFlowLogger,
-    composer_logging_level: int,
+    python_logging_level: int,
     transformers_model_path: str,
     flavor: str,
     input_example: dict[str, Any],
@@ -130,7 +130,7 @@ def _log_model_multiprocess(
 
     Inputs:
     - mlflow_logger: MLFlowLogger: MLflow logger object
-    - composer_logging_level: int: logging level for composer
+    - python_logging_level: int: logging level
     - flavor: str: transformers or peft
     - input_example: dict[str, Any]: model serving input example for model
     - log_model_metadata: dict[str, str]: This metadata is currently needed for optimized serving
@@ -139,13 +139,13 @@ def _log_model_multiprocess(
     - registered_model_name: Optional
     """
     # Setup logging for child process. This ensures that any logs from composer are surfaced.
-    if composer_logging_level > 0:
+    if python_logging_level > 0:
         # If logging_level is 0, then the composer logger was unset.
         logging.basicConfig(
             format=
             f'%(asctime)s: rank{dist.get_global_rank()}[%(process)d][%(threadName)s]: %(levelname)s: %(name)s: %(message)s',
         )
-        logging.getLogger('composer').setLevel(composer_logging_level)
+        logging.getLogger('llmfoundry').setLevel(python_logging_level)
     
     log.info("----------------- REACHED MLFLOW LOG MODEL -----------------")
     # monkey patch to prevent duplicate tokenizer upload
@@ -678,6 +678,7 @@ def tensor_hook(
 
             log.debug('Saving Hugging Face checkpoint to disk')
 
+            log.debug(f"UPLOAD_TO_SAVE_FOLDER: {upload_to_save_folder}")
             if upload_to_save_folder:
                 # This context manager casts the TE extra state in io.BytesIO format to tensor format
                 # Needed for proper hf ckpt saving.
@@ -785,7 +786,7 @@ def tensor_hook(
 
                     # Spawn a new process to register the model.
                     # Slower method to register the model via log_model.
-                    log.info('USING MY BRANCH!!!!!!!!!!!!!!')
+                    log.info(f'USING MY BRANCH!!!!!!!!!!!!!! REGISTERED MODEL NAME: {self.mlflow_registered_model_name}')
                     process = SpawnProcess(
                         target=_log_model_multiprocess,
                         kwargs={
@@ -795,8 +796,8 @@ def tensor_hook(
                                 temp_save_dir,
                             'flavor':
                                 'peft' if self.using_peft else 'transformers',
-                            'composer_logging_level':
-                                logging.getLogger('composer').level,
+                            'python_logging_level':
+                                logging.getLogger('llmfoundry').level,
                             'task':
                                 self.mlflow_logging_config['metadata']['task'],
                             'log_model_metadata': self.mlflow_logging_config['metadata'],