diff --git a/Biblioteka_DL/dllib-mlflow.py b/Biblioteka_DL/dllib-mlflow.py
index c005850..80a74b1 100644
--- a/Biblioteka_DL/dllib-mlflow.py
+++ b/Biblioteka_DL/dllib-mlflow.py
@@ -20,7 +20,7 @@ from sacred.observers import MongoObserver
 
 # EPOCHS = int(sys.argv[1])
 
-#
+# mlflow.set_tracking_uri("http://172.17.0.1:5000")
 mlflow.set_experiment("s444356")
 
 class Model(nn.Module):
@@ -307,21 +307,13 @@ def my_main(epochs):
     tracking_url_type_store = urlparse(mlflow.get_tracking_uri()).scheme
     # print(tracking_url_type_store)
 
-    # if tracking_url_type_store != "file":
-    #     mlflow.pytorch.log_model(model, "model", registered_model_name="s444356", signature=siganture,
-    #                              input_example=input_example)
-    # else:
-    #     mlflow.pytorch.log_model(model, "model", signature=siganture, input_example=input_example)
-    #     mlflow.pytorch.save_model(model, "my_model", signature=siganture, input_example=input_example)
-
-
-    mlflow.pytorch.log_model(model, "model", signature=siganture, input_example=input_example)
-    mlflow.pytorch.save_model(model, "my_model", signature=siganture, input_example=input_example)
-
-    mlflow.set_tracking_uri("http://172.17.0.1:5000")
     if tracking_url_type_store != "file":
         mlflow.pytorch.log_model(model, "model", registered_model_name="s444356", signature=siganture,
                                  input_example=input_example)
+    else:
+        mlflow.pytorch.log_model(model, "model", signature=siganture, input_example=input_example)
+        mlflow.pytorch.save_model(model, "my_model", signature=siganture, input_example=input_example)
+
 
     for epoch in range(1, epochs + 1):
         print("Epoch #", epoch)
diff --git a/Jenkinsfile_train-sacred b/Jenkinsfile_train-sacred
index f9cb9cb..06fcf45 100644
--- a/Jenkinsfile_train-sacred
+++ b/Jenkinsfile_train-sacred
@@ -17,7 +17,6 @@ pipeline {
 	stage('Script'){
 		steps {
                         copyArtifacts filter: '*', projectName: 's444356-create-dataset'
-			sh 'rm -r my_model'
 			sh "python Biblioteka_DL/dllib-mlflow.py $EPOCHS"
 			archiveArtifacts artifacts: 'games_model.pkl'
 			sh 'ls -al'