diff --git a/tests/networks/utils/test_replace_module.py b/tests/networks/utils/test_replace_module.py
index 9c0752d1c5..cc67b91571 100644
--- a/tests/networks/utils/test_replace_module.py
+++ b/tests/networks/utils/test_replace_module.py
@@ -71,7 +71,7 @@ def test_replace(self, name, strict_match, match_device, device):
         # all replaced modules should be ReLU
         for r in replaced:
             self.assertIsInstance(r[1], torch.nn.ReLU)
-        # if a specfic module was named, check that the name matches exactly
+        # if a specific module was named, check that the name matches exactly
         if name == "features.denseblock1.denselayer1.layers.relu1":
             self.assertEqual(replaced[0][0], name)
 
diff --git a/tests/utils/test_look_up_option.py b/tests/utils/test_look_up_option.py
index 75560b4ac4..96adda9473 100644
--- a/tests/utils/test_look_up_option.py
+++ b/tests/utils/test_look_up_option.py
@@ -72,7 +72,7 @@ def test_no_found(self):
         with self.assertRaisesRegex(ValueError, "did you mean"):
             look_up_option(3, {1: "a", 2: "b", "c": 3})
         with self.assertRaisesRegex(ValueError, "did.*empty"):
-            look_up_option("empy", _CaseEnum)
+            look_up_option("empty", _CaseEnum)
         with self.assertRaisesRegex(ValueError, "Unsupported"):
             look_up_option(_CaseEnum1.EMPTY, _CaseEnum)
         with self.assertRaisesRegex(ValueError, "Unsupported"):
diff --git a/tests/utils/test_profiling.py b/tests/utils/test_profiling.py
index da41a8ef69..56649ccb93 100644
--- a/tests/utils/test_profiling.py
+++ b/tests/utils/test_profiling.py
@@ -72,7 +72,7 @@ def test_profile_transforms(self):
         self.assertIsInstance(dt, datetime.datetime)
 
     def test_profile_multithread(self):
-        """Test resulst are gathered from multiple threads using ThreadDataLoader."""
+        """Test results are gathered from multiple threads using ThreadDataLoader."""
         ds = Dataset([self.test_image] * 4, self.scale)
         dl = ThreadDataLoader(ds, batch_size=4, num_workers=4, use_thread_workers=True)