diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index d99c26a5de..088b0fb71e 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -1936,7 +1936,7 @@ class Trainer(
 
         if self.loggers and self.num_training_batches < self.log_every_n_steps:
             rank_zero_warn(
-                f"The number of training samples ({self.num_training_batches}) is smaller than the logging interval"
+                f"The number of training batches ({self.num_training_batches}) is smaller than the logging interval"
                 f" Trainer(log_every_n_steps={self.log_every_n_steps}). Set a lower value for log_every_n_steps if"
                 " you want to see logs for the training epoch.",
                 category=PossibleUserWarning,
diff --git a/tests/trainer/test_dataloaders.py b/tests/trainer/test_dataloaders.py
index 08d54e05bf..66b5be243b 100644
--- a/tests/trainer/test_dataloaders.py
+++ b/tests/trainer/test_dataloaders.py
@@ -702,11 +702,11 @@ def test_warning_with_small_dataloader_and_logging_interval(tmpdir):
     dataloader = DataLoader(RandomDataset(32, length=10))
     model.train_dataloader = lambda: dataloader
 
-    with pytest.warns(UserWarning, match=r"The number of training samples \(10\) is smaller than the logging interval"):
+    with pytest.warns(UserWarning, match=r"The number of training batches \(10\) is smaller than the logging interval"):
         trainer = Trainer(default_root_dir=tmpdir, max_epochs=1, log_every_n_steps=11)
         trainer.fit(model)
 
-    with pytest.warns(UserWarning, match=r"The number of training samples \(1\) is smaller than the logging interval"):
+    with pytest.warns(UserWarning, match=r"The number of training batches \(1\) is smaller than the logging interval"):
         trainer = Trainer(default_root_dir=tmpdir, max_epochs=1, log_every_n_steps=2, limit_train_batches=1)
         trainer.fit(model)