diff --git a/sagemaker-train/src/sagemaker/train/evaluate/base_evaluator.py b/sagemaker-train/src/sagemaker/train/evaluate/base_evaluator.py
index d53981ca43..4bf718b050 100644
--- a/sagemaker-train/src/sagemaker/train/evaluate/base_evaluator.py
+++ b/sagemaker-train/src/sagemaker/train/evaluate/base_evaluator.py
@@ -21,6 +21,7 @@
     from sagemaker.core.helper.session_helper import Session
 
 from sagemaker.train.base_trainer import BaseTrainer
+from sagemaker.train.common_utils.finetune_utils import _resolve_mlflow_resource_arn
 # Module-level logger
 _logger = logging.getLogger(__name__)
 
@@ -163,8 +164,6 @@ def _resolve_dataset(cls, v):
     @validator('mlflow_resource_arn', pre=True, always=True)
     def _resolve_mlflow_arn(cls, v, values):
         """Resolve MLflow resource ARN using default experience logic if not provided."""
-        from ..common_utils.finetune_utils import _resolve_mlflow_resource_arn
-        
         # Get sagemaker_session from values
         sagemaker_session = values.get('sagemaker_session')
         if sagemaker_session is None:
@@ -709,6 +708,10 @@ def _get_base_template_context(
         Returns:
             dict: Base template context dictionary
         """
+        # Resolve MLflow ARN if not already resolved (e.g. session was None at construction time)
+        if not self.mlflow_resource_arn and self.sagemaker_session:
+            self.mlflow_resource_arn = _resolve_mlflow_resource_arn(self.sagemaker_session)
+
         # Generate default mlflow_experiment_name if not provided
         # This is required by AWS when ModelPackageGroupArn is not provided in training jobs
         mlflow_experiment_name = self.mlflow_experiment_name
diff --git a/sagemaker-train/tests/unit/train/evaluate/test_base_evaluator.py b/sagemaker-train/tests/unit/train/evaluate/test_base_evaluator.py
index 55ded87bd7..5676add83a 100644
--- a/sagemaker-train/tests/unit/train/evaluate/test_base_evaluator.py
+++ b/sagemaker-train/tests/unit/train/evaluate/test_base_evaluator.py
@@ -925,6 +925,37 @@ def test_get_base_template_context(self, mock_resolve, mock_session, mock_model_
         assert context['dataset_artifact_arn'] == DEFAULT_ARTIFACT_ARN
         assert 'action_arn_prefix' in context
 
+    @patch("sagemaker.train.common_utils.model_resolution._resolve_base_model")
+    @patch("sagemaker.train.evaluate.base_evaluator._resolve_mlflow_resource_arn")
+    def test_get_base_template_context_deferred_mlflow_resolution(self, mock_resolve_mlflow, mock_resolve, mock_session, mock_model_info):
+        """Test that mlflow_resource_arn is resolved in _get_base_template_context when session was None at construction."""
+        mock_resolve.return_value = mock_model_info
+        # Validator returns None because session was None at construction time
+        mock_resolve_mlflow.return_value = None
+
+        evaluator = BaseEvaluator(
+            model=DEFAULT_MODEL,
+            s3_output_path=DEFAULT_S3_OUTPUT,
+            model_package_group=DEFAULT_MODEL_PACKAGE_GROUP_ARN,
+            sagemaker_session=mock_session,
+        )
+        # Simulate the case where ARN was not resolved at construction (session was None)
+        evaluator.mlflow_resource_arn = None
+
+        resolved_arn = "arn:aws:sagemaker:us-west-2:123456789012:mlflow-tracking-server/deferred"
+        mock_resolve_mlflow.return_value = resolved_arn
+
+        context = evaluator._get_base_template_context(
+            role_arn=DEFAULT_ROLE_ARN,
+            region=DEFAULT_REGION,
+            account_id="123456789012",
+            model_package_group_arn=DEFAULT_MODEL_PACKAGE_GROUP_ARN,
+            resolved_model_artifact_arn=DEFAULT_ARTIFACT_ARN,
+        )
+
+        assert context['mlflow_resource_arn'] == resolved_arn
+        mock_resolve_mlflow.assert_called_with(mock_session)
+
 
 class TestResolveModelArtifacts:
     """Tests for model artifacts resolution."""