diff --git a/src/llamafactory/train/trainer_utils.py b/src/llamafactory/train/trainer_utils.py
index 198936eb..2380540e 100644
--- a/src/llamafactory/train/trainer_utils.py
+++ b/src/llamafactory/train/trainer_utils.py
@@ -515,6 +515,22 @@ def create_custom_scheduler(
     num_training_steps: int,
     optimizer: Optional["torch.optim.Optimizer"] = None,
 ) -> None:
+    if training_args.lr_scheduler_type == "warmup_stable_decay":
+        num_warmup_steps = training_args.get_warmup_steps(num_training_steps)
+        remaining_steps = num_training_steps - num_warmup_steps
+        num_stable_steps = remaining_steps // 3  # use 1/3 for stable by default
+        num_decay_steps = remaining_steps - num_stable_steps
+        scheduler_kwargs = training_args.lr_scheduler_kwargs or {}
+        default_kwargs = {
+            "num_stable_steps": num_stable_steps,
+            "num_decay_steps": num_decay_steps,
+        }
+        for key, value in default_kwargs.items():
+            if key not in scheduler_kwargs:
+                scheduler_kwargs[key] = value
+
+        training_args.lr_scheduler_kwargs = scheduler_kwargs
+
     if optimizer is not None and isinstance(optimizer, DummyOptimizer):
         optimizer_dict = optimizer.optimizer_dict
         scheduler_dict: dict[torch.nn.Parameter, torch.optim.lr_scheduler.LRScheduler] = {}