diff --git a/lnp_ml/modeling/final_train_optuna_cv.py b/lnp_ml/modeling/final_train_optuna_cv.py
index 4eeb0e7..8046e4e 100644
--- a/lnp_ml/modeling/final_train_optuna_cv.py
+++ b/lnp_ml/modeling/final_train_optuna_cv.py
@@ -282,8 +282,8 @@ def run_optuna_cv(
         
         # 搜索训练超参数
         dropout = trial.suggest_float("dropout", 0.1, 0.5)
-        lr = trial.suggest_float("lr", 1e-5, 3e-4, log=True)
-        weight_decay = trial.suggest_float("weight_decay", 1e-5, 1e-3, log=True)
+        lr = trial.suggest_float("lr", 1e-5, 1e-3, log=True)
+        weight_decay = trial.suggest_float("weight_decay", 1e-5, 1e-1, log=True)
         backbone_lr_ratio = trial.suggest_float("backbone_lr_ratio", 0.01, 1.0, log=True)
         
         # 3-fold CV
diff --git a/lnp_ml/modeling/nested_cv_optuna.py b/lnp_ml/modeling/nested_cv_optuna.py
index 0d5ba11..0f7781c 100644
--- a/lnp_ml/modeling/nested_cv_optuna.py
+++ b/lnp_ml/modeling/nested_cv_optuna.py
@@ -395,8 +395,8 @@ def run_inner_optuna(
         
         # 搜索训练超参数
         dropout = trial.suggest_float("dropout", 0.1, 0.5)
-        lr = trial.suggest_float("lr", 1e-5, 3e-4, log=True)
-        weight_decay = trial.suggest_float("weight_decay", 1e-5, 1e-3, log=True)
+        lr = trial.suggest_float("lr", 1e-5, 1e-3, log=True)
+        weight_decay = trial.suggest_float("weight_decay", 1e-5, 1e-1, log=True)
         backbone_lr_ratio = trial.suggest_float("backbone_lr_ratio", 0.01, 1.0, log=True)
         
         # 内层 3-fold CV