diff --git a/intermediate_source/torchvision_tutorial.rst b/intermediate_source/torchvision_tutorial.rst
index 9aa6515df09..1f7c6fcde8a 100644
--- a/intermediate_source/torchvision_tutorial.rst
+++ b/intermediate_source/torchvision_tutorial.rst
@@ -64,7 +64,7 @@ training and evaluation, and will use the evaluation scripts from
 One note on the ``labels``. The model considers class ``0`` as background. If your dataset does not contain the background class, you should not have ``0`` in your ``labels``. For example, assuming you have just two classes, *cat* and *dog*, you can define ``1`` (not ``0``) to represent *cats* and ``2`` to represent *dogs*. So, for instance, if one of the images has both classes, your ``labels`` tensor should look like ``[1,2]``.
 
 Additionally, if you want to use aspect ratio grouping during training
-(so that each batch only contains images with similar aspect ratio),
+(so that each batch only contains images with similar aspect ratios),
 then it is recommended to also implement a ``get_height_and_width``
 method, which returns the height and the width of the image. If this
 method is not provided, we query all elements of the dataset via