diff --git a/pytorch-example-evaluate.py b/pytorch-example-evaluate.py
index fb68af5..7db5957 100644
--- a/pytorch-example-evaluate.py
+++ b/pytorch-example-evaluate.py
@@ -1,3 +1,4 @@
+from numpy.lib.function_base import average
 from sklearn.model_selection import train_test_split
 import torch
 import torch.nn as nn
@@ -7,6 +8,8 @@ import torch.nn.functional as F
 from torch.utils.data import DataLoader, TensorDataset, random_split
 from sklearn import preprocessing
 from sklearn.metrics import accuracy_score
+from sklearn.metrics import f1_score
+from sklearn.metrics import mean_squared_error
 import sys
 
 class LogisticRegressionModel(torch.nn.Module):
@@ -43,6 +46,10 @@ output_dim = 1
 model = LogisticRegressionModel(input_dim, output_dim)
 
 pred = model(fTest)
-accuracy = accuracy_score(fTest, np.argmax(pred.detach(), axis = 1))
+accuracy = accuracy_score(tTest, np.argmax(pred.detach().numpy(), axis = 1))
+f1 = f1_score(tTest, np.argmax(pred.detach().numpy(), axis = 1, average = None))
+rmse = mean_squared_error(tTest, np.argmax(pred.detach().numpy()))
 
-print(f'Accuracy: {accuracy}')
\ No newline at end of file
+print(f'Accuracy: {accuracy}')
+print(f'F1: {f1_score}')
+print(f'RMSE: {rmse}')
\ No newline at end of file