diff --git a/requirements.txt b/requirements.txt
index 46cd464..3b48ecf 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -33,7 +33,7 @@ starlette==0.27.0
 sympy==1.12
 tomli==2.0.1
 tomlkit==0.12.1
-torch==2.1.0+cpu
+torch==1.10.0
 torchaudio==2.1.0+cpu
 torchvision==0.16.0+cpu
 typing_extensions==4.8.0
diff --git a/src/main.py b/src/main.py
index 243a31e..ee031a6 100644
--- a/src/main.py
+++ b/src/main.py
@@ -1,3 +1,4 @@
+import logging
 from PIL import Image
 import torch
 import torch.nn as nn
@@ -6,6 +7,8 @@
 from torch.utils.data import DataLoader
 import numpy as np
 
+logging.basicConfig(filename='training.log', level=logging.ERROR)
+
 # Step 1: Load MNIST Data and Preprocess
 transform = transforms.Compose([
     transforms.ToTensor(),
@@ -39,10 +42,13 @@ def forward(self, x):
 epochs = 3
 for epoch in range(epochs):
     for images, labels in trainloader:
-        optimizer.zero_grad()
-        output = model(images)
-        loss = criterion(output, labels)
-        loss.backward()
-        optimizer.step()
+        try:
+            optimizer.zero_grad()
+            output = model(images)
+            loss = criterion(output, labels)
+            loss.backward()
+            optimizer.step()
+        except Exception as e:
+            logging.exception("Error occurred during training: %s", e)
 
 torch.save(model.state_dict(), "mnist_model.pth")
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