diff --git a/llama_stack/apis/post_training/post_training.py b/llama_stack/apis/post_training/post_training.py
index 1c2d2d6e2..8e1edbe87 100644
--- a/llama_stack/apis/post_training/post_training.py
+++ b/llama_stack/apis/post_training/post_training.py
@@ -58,6 +58,7 @@ class TrainingConfig(BaseModel):
     n_epochs: int
     max_steps_per_epoch: int
     gradient_accumulation_steps: int
+    max_validation_steps: int
     data_config: DataConfig
     optimizer_config: OptimizerConfig
     efficiency_config: Optional[EfficiencyConfig] = 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 1b6c508a7..a2ef1c5dd 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
@@ -137,6 +137,7 @@ class LoraFinetuningSingleDevice:
         self.global_step = 0
 
         self._gradient_accumulation_steps = training_config.gradient_accumulation_steps
+        self.max_validation_steps = training_config.max_validation_steps
 
         self._clip_grad_norm = 1.0
         self._enable_activation_checkpointing = (
@@ -583,7 +584,7 @@ class LoraFinetuningSingleDevice:
         log.info("Starting validation...")
         pbar = tqdm(total=len(self._validation_dataloader))
         for idx, batch in enumerate(self._validation_dataloader):
-            if idx == 10:
+            if idx == self.max_validation_steps:
                 break
             torchtune_utils.batch_to_device(batch, self._device)