diff --git a/diffsynth/trainers/text_to_image.py b/diffsynth/trainers/text_to_image.py
index 6dc24e6..3177474 100644
--- a/diffsynth/trainers/text_to_image.py
+++ b/diffsynth/trainers/text_to_image.py
@@ -18,6 +18,7 @@ class LightningModelForT2ILoRA(pl.LightningModule):
         self.learning_rate = learning_rate
         self.use_gradient_checkpointing = use_gradient_checkpointing
         self.state_dict_converter = state_dict_converter
+        self.lora_alpha = None
 
 
     def load_models(self):
@@ -34,6 +35,7 @@ class LightningModelForT2ILoRA(pl.LightningModule):
     
     def add_lora_to_model(self, model, lora_rank=4, lora_alpha=4, lora_target_modules="to_q,to_k,to_v,to_out", init_lora_weights="gaussian"):
         # Add LoRA to UNet
+        self.lora_alpha = lora_alpha
         if init_lora_weights == "kaiming":
             init_lora_weights = True
             
@@ -94,7 +96,7 @@ class LightningModelForT2ILoRA(pl.LightningModule):
             if name in trainable_param_names:
                 lora_state_dict[name] = param
         if self.state_dict_converter is not None:
-            lora_state_dict = self.state_dict_converter(lora_state_dict)
+            lora_state_dict = self.state_dict_converter(lora_state_dict, alpha=self.lora_alpha)
         checkpoint.update(lora_state_dict)