diff --git a/Jenkinsfile_evaluation b/Jenkinsfile_evaluation
index 066c982..404a504 100644
--- a/Jenkinsfile_evaluation
+++ b/Jenkinsfile_evaluation
@@ -11,31 +11,46 @@ pipeline {
             description: 'Which build to use for copying artifacts',
             name: 'WHICH_BUILD_TRAIN'
         )
+        buildSelector(
+            defaultSelector: lastSuccessful(),
+            description: 'Which build to use for copying artifacts',
+            name: 'WHICH_BUILD_EVAL'
+        ) 
+        gitParameter branchFilter: 'origin/(.*)', defaultValue: 'master', name: 'BRANCH', type: 'PT_BRANCH'
 	}
     stages {
 		stage('copyArtifacts') {
             steps {
                 copyArtifacts fingerprintArtifacts: true, projectName: 's434804-create-dataset', selector: buildParameter('BUILD_SELECTOR')
                 copyArtifacts fingerprintArtifacts: true, projectName: 's434804-training/master', selector: buildParameter('WHICH_BUILD_TRAIN')
+                copyArtifacts optional: true, fingerprintArtifacts: true, projectName: 's434804-evaluation/master', selector: buildParameter('WHICH_BUILD_EVAL')
             }
         }
         stage('evaluation') {
 			steps {
+                sh 'buildNumber=$(echo $BUILD_NUMBER)'
+                sh 'python3 ./lab06-eval.py $BUILD_NUMBER'
                 sh 'chmod +x tensor-eval.py'
                 sh 'python3 "tensor-eval.py" >> evaluation.txt'
+                sh 'python3 tensor-plot.py'
 			}
 		}
 		stage('archiveArtifacts') {
 			steps{
 				archiveArtifacts 'evaluation.txt'
+                archiveArtifacts 'evaluation_plot.png'
 			}
 		}
-        stage('sendMail') {
-            steps{
-                emailext body: currentBuild.result ?: 'EVALUATION SUCCESS',
-                subject: 's434804',
-                to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
-            }
-        }
     }
+    post {
+        success {
+            mail body: 'SUCCESS', subject: 's434804', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
+        }
+        failure {
+            mail body: 'FAILURE', subject: 's434804', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
+        }
+        changed {
+            mail body: 'CHANGED', subject: 's434804', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
+        }
+   }
 }
\ No newline at end of file
diff --git a/tensor-eval.py b/tensor-eval.py
index 873f39d..43f978b 100644
--- a/tensor-eval.py
+++ b/tensor-eval.py
@@ -1,21 +1,28 @@
-import numpy as np
 import pandas as pd
+import sys
 from sklearn.linear_model import LinearRegression
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import mean_squared_error as rmse
-
 reg = LinearRegression()
 
 alldata = pd.read_csv(
-    'test.csv', header=0, skipinitialspace=True,
-     usecols=['total_vaccinations', 'people_vaccinated', 'daily_vaccinations' ,'daily_vaccinations_per_million']).dropna()
+    'test.csv', header=0,
+     usecols=['total_vaccinations', 'daily_vaccinations', 'people_fully_vaccinated']).dropna()
 
-X = alldata[[c for c in alldata.columns if c != 'daily_vaccinations']]
-y = alldata['daily_vaccinations']
+X = alldata['total_vaccinations'].to_numpy().ravel().reshape(-1, 1)
+y = alldata['daily_vaccinations'].to_numpy().ravel().reshape(-1, 1)
 
 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 6)
 lin_reg = reg.fit(X_train, y_train)
 score = lin_reg.score(X_test, y_test)
 prediction = lin_reg.predict(X_test)
+
+build_no = sys.argv[1] if len(sys.argv) > 1 else 0
+data = {"rmse": [rmse], "build": [build_no]}
+df = pd.DataFrame(data=data)
+
+with open("evaluation.csv", "a") as f:
+    df.to_csv(f, header=f.tell() == 0, index=False)
+
 print("RMSE:", rmse(y_test, prediction, squared=False))
 print("Score:", score)
\ No newline at end of file
diff --git a/tensor-plot.py b/tensor-plot.py
new file mode 100644
index 0000000..58fddf1
--- /dev/null
+++ b/tensor-plot.py
@@ -0,0 +1,6 @@
+import pandas as pd
+from matplotlib import pyplot as plt
+
+df = pd.read_csv("evaluation.csv")
+df.plot(x="build", y="rmse")
+plt.savefig("evaluation_plot.png")
\ No newline at end of file