diff --git a/train.py b/train.py
index 80b535a..2cd66be 100755
--- a/train.py
+++ b/train.py
@@ -21,7 +21,7 @@ logging.basicConfig(level=logging.WARN)
 logger = logging.getLogger(__name__)
 
 mlflow.set_tracking_uri("http://172.17.0.1:5000")
-mlflow.set_experiment("s123456")
+mlflow.set_experiment("s123456-new")
 
 def eval_metrics(actual, pred):
     rmse = np.sqrt(mean_squared_error(actual, pred))
@@ -94,6 +94,6 @@ if __name__ == "__main__":
             # There are other ways to use the Model Registry, which depends on the use case,
             # please refer to the doc for more information:
             # https://mlflow.org/docs/latest/model-registry.html#api-workflow
-            mlflow.sklearn.log_model(lr, "wines-model", registered_model_name="ElasticnetWineModel", signature=signature)
+            mlflow.sklearn.log_model(lr, "wines-model", registered_model_name="ElasticnetWineModel_s123456", signature=signature)
         else:
             mlflow.sklearn.log_model(lr, "model", signature=signature)