diff --git a/server/trainers/cnn_bilstm_attention_trainer.py b/server/trainers/cnn_bilstm_attention_trainer.py
index c8d4147..47b100f 100644
--- a/server/trainers/cnn_bilstm_attention_trainer.py
+++ b/server/trainers/cnn_bilstm_attention_trainer.py
@@ -132,7 +132,7 @@ def train_with_cnn_bilstm_attention(product_id, model_identifier, product_df, st
     loss_curve_path = plot_loss_curve(
         loss_history['train'],
         loss_history['val'],
-        product_name,
+        model_identifier,
         'cnn_bilstm_attention',
         model_dir=model_dir
     )
diff --git a/server/trainers/mlstm_trainer.py b/server/trainers/mlstm_trainer.py
index d3d0bf1..1cb0233 100644
--- a/server/trainers/mlstm_trainer.py
+++ b/server/trainers/mlstm_trainer.py
@@ -393,19 +393,9 @@ def train_product_model_with_mlstm(
     
     emit_progress("生成损失曲线...", progress=95)
     
-    # 确定模型保存目录（支持多店铺）
-    if store_id:
-        # 为特定店铺创建子目录
-        store_model_dir = os.path.join(model_dir, 'mlstm', store_id)
-        os.makedirs(store_model_dir, exist_ok=True)
-        loss_curve_filename = f"{product_id}_mlstm_{version}_loss_curve.png"
-        loss_curve_path = os.path.join(store_model_dir, loss_curve_filename)
-    else:
-        # 全局模型保存在global目录
-        global_model_dir = os.path.join(model_dir, 'mlstm', 'global')
-        os.makedirs(global_model_dir, exist_ok=True)
-        loss_curve_filename = f"{product_id}_mlstm_{version}_global_loss_curve.png"
-        loss_curve_path = os.path.join(global_model_dir, loss_curve_filename)
+    # 确定模型保存目录
+    loss_curve_filename = f"{model_identifier}_mlstm_{version}_loss_curve.png"
+    loss_curve_path = os.path.join(model_dir, loss_curve_filename)
     
     # 绘制损失曲线并保存到模型目录
     plt.figure(figsize=(10, 6))