diff --git a/llmfoundry/utils/config_utils.py b/llmfoundry/utils/config_utils.py
index 72ca19834b..b6a5acf6d9 100644
--- a/llmfoundry/utils/config_utils.py
+++ b/llmfoundry/utils/config_utils.py
@@ -39,6 +39,7 @@
     'update_batch_size_info',
     'process_init_device',
     'log_config',
+    'log_dataset_uri',
 ]
 
 
@@ -508,7 +509,6 @@ def log_config(cfg: Dict[str, Any]) -> None:
 
     if 'mlflow' in loggers and mlflow.active_run():
         mlflow.log_params(params=cfg)
-        _log_dataset_uri(cfg)
 
 
 def _parse_source_dataset(cfg: Dict[str, Any]) -> List[Tuple[str, str, str]]:
@@ -619,12 +619,15 @@ def _process_data_source(
         log.warning('DataSource Not Found.')
 
 
-def _log_dataset_uri(cfg: Dict[str, Any]) -> None:
+def log_dataset_uri(cfg: Dict[str, Any]) -> None:
     """Logs dataset tracking information to MLflow.
 
     Args:
         cfg (DictConfig): A config dictionary of a run
     """
+    loggers = cfg.get('loggers', None) or {}
+    if 'mlflow' not in loggers or not mlflow.active_run():
+        return
     # Figure out which data source to use
     data_paths = _parse_source_dataset(cfg)
 
diff --git a/scripts/train/train.py b/scripts/train/train.py
index e0c2b8a94f..bfeec14e0b 100644
--- a/scripts/train/train.py
+++ b/scripts/train/train.py
@@ -55,6 +55,7 @@
     TRAIN_CONFIG_KEYS,
     TrainConfig,
     log_config,
+    log_dataset_uri,
     make_dataclass_and_log_config,
     pop_config,
     process_init_device,
@@ -530,6 +531,7 @@ def main(cfg: DictConfig) -> Trainer:
     if train_cfg.log_config:
         log.info('Logging config')
         log_config(logged_cfg)
+    log_dataset_uri(logged_cfg)
     torch.cuda.empty_cache()
     gc.collect()
 
diff --git a/tests/utils/test_mlflow_logging.py b/tests/utils/test_mlflow_logging.py
index 04a600d44c..d2dd5f4689 100644
--- a/tests/utils/test_mlflow_logging.py
+++ b/tests/utils/test_mlflow_logging.py
@@ -7,8 +7,8 @@
 import pytest
 
 from llmfoundry.utils.config_utils import (
-    _log_dataset_uri,
     _parse_source_dataset,
+    log_dataset_uri,
 )
 
 mlflow = pytest.importorskip('mlflow')
@@ -84,10 +84,12 @@ def test_log_dataset_uri():
         }},
         source_dataset_train='huggingface/train_dataset',
         source_dataset_eval='huggingface/eval_dataset',
+        loggers={'mlflow': {}},
     )
 
-    with patch('mlflow.log_input') as mock_log_input:
-        _log_dataset_uri(cfg)
+    with patch('mlflow.log_input') as mock_log_input, \
+         patch('mlflow.active_run', return_value=True):
+        log_dataset_uri(cfg)
         assert mock_log_input.call_count == 2
         meta_dataset_calls = [
             args[0] for args, _ in mock_log_input.call_args_list