diff --git a/Jenkinsfile_4 b/Jenkinsfile_4
index dfd2423..7cb2e22 100644
--- a/Jenkinsfile_4
+++ b/Jenkinsfile_4
@@ -23,21 +23,9 @@ pipeline {
                 }
             }
     }
-      //stage('Run Script') {
-            //steps {
-               //script {
-                //sh "chmod +x -R ${env.WORKSPACE}"             
-                //sh './make_statistic.sh | tee output_statistic.txt'
-                // sh 'docker build . -t jhenyk/ium:latest'
-                // sh 'docker run jhenyk/ium:latest'
-                  //sh 'node --version'
-               //}
-            //}
-        
-    //}
       stage('Archive Output') {
          steps {
-            archiveArtifacts 'testresults.txt'
+            archiveArtifacts 'metrics.txt'
          }
       }
    }
diff --git a/__pycache__/train.cpython-38.pyc b/__pycache__/train.cpython-38.pyc
index e6316ba..ad75a99 100644
Binary files a/__pycache__/train.cpython-38.pyc and b/__pycache__/train.cpython-38.pyc differ
diff --git a/metrics.txt b/metrics.txt
new file mode 100644
index 0000000..cfe1361
--- /dev/null
+++ b/metrics.txt
@@ -0,0 +1,4 @@
+Accuracy: 0.5466666666666666 
+Precision: 0.5466666666666666 
+Recall: 1.0 
+F-score: 0.7068965517241379 
diff --git a/test.py b/test.py
index 4aa4ddb..dcedbd2 100644
--- a/test.py
+++ b/test.py
@@ -81,4 +81,27 @@ if __name__ == '__main__':
                 the_file.write(f'data: {item[0][i]} \n true value: {item[1][i]} \n prediction: {item[2][i]}\n')
                 print(f'data: {item[0][i]} \n true value: {item[1][i]} \n prediction: {item[2][i]}\n')
 
+    tp = 0
+    tn = 0
+    fp = 0
+    fn = 0
+
+    for item in testdata:
+        for i in range(len(item)):
+            if int(item[1][i]) and int(item[2][i]):
+                tp += 1
+            elif not int(item[1][i]) and not int(item[2][i]):
+                tn += 1
+            elif not int(item[1][i]) and int(item[2][i]):
+                fp += 1
+            elif int(item[1][i]) and not int(item[2][i]):
+                fn += 1
+
+    accuracy = (tp + tn) / (tp + tn + fp + fn)
+    precision = tp / (tp + fp)
+    recall = tp / (tp + fn)
+    fscore = (2 * precision * recall) / (precision + recall)
+
+    with open('metrics.txt', 'w') as the_file:
+        the_file.write(f'Accuracy: {accuracy} \nPrecision: {precision} \nRecall: {recall} \nF-score: {fscore} \n')
     
\ No newline at end of file