diff --git a/0_5_Machine_Learning.py b/0_5_Machine_Learning.py
index 1700766..79ee8c1 100644
--- a/0_5_Machine_Learning.py
+++ b/0_5_Machine_Learning.py
@@ -63,6 +63,7 @@ model_result = pd.DataFrame(columns= ["Model", "Accuracy", "Recall", "F1_score",
 
 # Naive Bayes
 model_result = pipeline_naiveBayes_benchmark(X_train, y_train, X_test, y_test, model_result)
+save_result_set_s3(model_result , "resultat", type_of_activity, type_of_model)
 print("Naive Bayes : Done")
 
 # Logistic Regression
@@ -70,12 +71,16 @@ model_result = pipeline_logreg_benchmark(X_train, y_train, X_test, y_test, model
 print("Logistic : Done")
 
 model_result = pipeline_logreg_cv(X_train, y_train, X_test, y_test, model_result)
+save_result_set_s3(model_result , "resultat", type_of_activity, type_of_model)
 print("Logistic CV : Done")
 
 # Random Forest
 model_result = pipeline_randomF_benchmark(X_train, y_train, X_test, y_test, model_result)
+save_result_set_s3(model_result , "resultat", type_of_activity, type_of_model)
 print("Random Forest : Done")
+
 model_result = pipeline_randomF_cv(X_train, y_train, X_test, y_test, model_result)
+save_result_set_s3(model_result , "resultat", type_of_activity, type_of_model)
 print("Random Forest CV: Done")
 
 # Save result