diff --git a/src/llmtuner/webui/components/train.py b/src/llmtuner/webui/components/train.py
index bfec4c4b..daefa1a8 100644
--- a/src/llmtuner/webui/components/train.py
+++ b/src/llmtuner/webui/components/train.py
@@ -123,7 +123,7 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
     with gr.Accordion(label="LoRA config", open=False) as lora_tab:
         with gr.Row():
             lora_rank = gr.Slider(value=8, minimum=1, maximum=1024, step=1, scale=1)
-            lora_alpha = gr.Slider(value=16, minimum=1, maximum=2048, step=0.1, scale=1)
+            lora_alpha = gr.Slider(value=16, minimum=1, maximum=2048, step=1, scale=1)
             lora_dropout = gr.Slider(value=0.1, minimum=0, maximum=1, step=0.01, scale=1)
             lora_target = gr.Textbox(scale=2)
 
diff --git a/src/llmtuner/webui/runner.py b/src/llmtuner/webui/runner.py
index c6fd4ae6..ba84e2c1 100644
--- a/src/llmtuner/webui/runner.py
+++ b/src/llmtuner/webui/runner.py
@@ -144,7 +144,7 @@ class Runner:
             args["name_module_trainable"] = get("train.name_module_trainable")
         elif args["finetuning_type"] == "lora":
             args["lora_rank"] = int(get("train.lora_rank"))
-            args["lora_alpha"] = float(get("train.lora_alpha"))
+            args["lora_alpha"] = int(get("train.lora_alpha"))
             args["lora_dropout"] = float(get("train.lora_dropout"))
             args["lora_target"] = get("train.lora_target") or get_module(get("top.model_name"))
             args["use_rslora"] = get("train.use_rslora")