minor changes

Author: FrancescoSaverioZuppichini

intermediate_source/torchvision_tutorial.rst

@@ -56,7 +56,7 @@ If your model returns the above methods, they will make it work for both
 training and evaluation, and will use the evaluation scripts from
 ``pycocotools``.
 
-One note on the ``labels``. The model expects class ``0`` to be always the 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*. If in your image you have booth classes, your ``labels`` tensor should look like ``[1,2]``.
+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 booth 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),