diff --git a/llms/mlx_lm/lora.py b/llms/mlx_lm/lora.py
index fdc400c6..b68c99ab 100644
--- a/llms/mlx_lm/lora.py
+++ b/llms/mlx_lm/lora.py
@@ -324,7 +324,7 @@ def evaluate_model(args, model: nn.Module, tokenizer: TokenizerWrapper, test_set
             delta=args.delta,
             loss_type=args.dpo_loss_type,
         )
-        print(f"Test loss {test_loss:.8f}, Rewards: {test_rewards[0]:.8f}, {test_rewards[1]:.8f}")
+        print(f"Test loss {test_loss:.3f}, Rewards: {test_rewards[0]:.3f}, {test_rewards[1]:.3f}")
     else:
         test_loss = evaluate(
             model=model,
diff --git a/llms/mlx_lm/tuner/dpo_trainer.py b/llms/mlx_lm/tuner/dpo_trainer.py
index 8979ec0d..2f4a74b6 100644
--- a/llms/mlx_lm/tuner/dpo_trainer.py
+++ b/llms/mlx_lm/tuner/dpo_trainer.py
@@ -327,7 +327,7 @@ def train_dpo(
             if rank == 0:
                 print(
                     f"Iter {it}: "
-                    f"Val loss {val_loss:.8f}, "
+                    f"Val loss {val_loss:.3f}, "
                     f"Val chosen reward {val_rewards[0]:.3f}, "
                     f"Val rejected reward {val_rewards[1]:.3f}, "
                     f"Val accuracy {val_metrics['accuracies']:.3f}, "
@@ -375,7 +375,7 @@ def train_dpo(
             
             if rank == 0:
                 print(
-                    f"Iter {it}: Train loss {train_loss:.8f}, "
+                    f"Iter {it}: Train loss {train_loss:.3f}, "
                     f"Chosen reward {train_rewards[0]:.3f}, "
                     f"Rejected reward {train_rewards[1]:.3f}, "
                     f"Accuracy {avg_metrics['accuracies']:.3f}, "