diff --git a/llama_stack/apis/common/training_types.py b/llama_stack/apis/common/training_types.py
index a9e3cac7c..b4bd1b0c6 100644
--- a/llama_stack/apis/common/training_types.py
+++ b/llama_stack/apis/common/training_types.py
@@ -26,4 +26,4 @@ class Checkpoint(BaseModel):
     epoch: int
     post_training_job_id: str
     path: str
-    training_metric: Optional[PostTrainingMetric] = None
+    training_metrics: Optional[PostTrainingMetric] = None
diff --git a/llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py b/llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py
index ec72fedb5..b832d40ec 100644
--- a/llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py
+++ b/llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py
@@ -544,13 +544,13 @@ class LoraFinetuningSingleDevice:
             )
             if self.training_config.data_config.validation_dataset_id:
                 validation_loss, perplexity = await self.validation()
-                training_metreic = PostTrainingMetric(
+                training_metrics = PostTrainingMetric(
                     epoch=curr_epoch,
                     train_loss=loss_to_log,
                     validation_loss=validation_loss,
                     perplexity=perplexity,
                 )
-                checkpoint.training_metric = training_metreic
+                checkpoint.training_metrics = training_metrics
             checkpoints.append(checkpoint)
 
         return (memory_stats, checkpoints)