diff --git a/docs/en/macros/train-args.md b/docs/en/macros/train-args.md
index 924bd313..e9e026e6 100644
--- a/docs/en/macros/train-args.md
+++ b/docs/en/macros/train-args.md
@@ -20,6 +20,7 @@
 | `seed`            | `0`      | Sets the random seed for training, ensuring reproducibility of results across runs with the same configurations.                                                                                                                                             |
 | `deterministic`   | `True`   | Forces deterministic algorithm use, ensuring reproducibility but may affect performance and speed due to the restriction on non-deterministic algorithms.                                                                                                    |
 | `single_cls`      | `False`  | Treats all classes in multi-class datasets as a single class during training. Useful for binary classification tasks or when focusing on object presence rather than classification.                                                                         |
+| `classes`         | `None`   | Specifies a list of class IDs to train on. Useful for filtering out and focusing only on certain classes during training.                                                                                                                                    |
 | `rect`            | `False`  | Enables rectangular training, optimizing batch composition for minimal padding. Can improve efficiency and speed but may affect model accuracy.                                                                                                              |
 | `cos_lr`          | `False`  | Utilizes a cosine [learning rate](https://www.ultralytics.com/glossary/learning-rate) scheduler, adjusting the learning rate following a cosine curve over epochs. Helps in managing learning rate for better convergence.                                   |
 | `close_mosaic`    | `10`     | Disables mosaic [data augmentation](https://www.ultralytics.com/glossary/data-augmentation) in the last N epochs to stabilize training before completion. Setting to 0 disables this feature.                                                                |