Update `overlap_mask` description. (#17324)

Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

docs/en/macros/train-args.md

@@ -43,7 +43,7 @@
 | `kobj`            | `2.0`    | Weight of the keypoint objectness loss in pose estimation models, balancing detection confidence with pose accuracy.                                                                                                                                         |
 | `label_smoothing` | `0.0`    | Applies label smoothing, softening hard labels to a mix of the target label and a uniform distribution over labels, can improve generalization.                                                                                                              |
 | `nbs`             | `64`     | Nominal batch size for normalization of loss.                                                                                                                                                                                                                |
-| `overlap_mask`    | `True`   | Determines whether segmentation masks should overlap during training, applicable in [instance segmentation](https://www.ultralytics.com/glossary/instance-segmentation) tasks.                                                                               |
+| `overlap_mask`    | `True`   | Determines whether object masks should be merged into a single mask for training, or kept separate for each object. In case of overlap, the smaller mask is overlayed on top of the larger mask during merge.                                                |
 | `mask_ratio`      | `4`      | Downsample ratio for segmentation masks, affecting the resolution of masks used during training.                                                                                                                                                             |
 | `dropout`         | `0.0`    | Dropout rate for regularization in classification tasks, preventing overfitting by randomly omitting units during training.                                                                                                                                  |
 | `val`             | `True`   | Enables validation during training, allowing for periodic evaluation of model performance on a separate dataset.                                                                                                                                             |

ultralytics/cfg/default.yaml

@@ -36,7 +36,7 @@ profile: False # (bool) profile ONNX and TensorRT speeds during training for log
 freeze: None # (int | list, optional) freeze first n layers, or freeze list of layer indices during training
 multi_scale: False # (bool) Whether to use multiscale during training
 # Segmentation
-overlap_mask: True # (bool) masks should overlap during training (segment train only)
+overlap_mask: True # (bool) merge object masks into a single image mask during training (segment train only)
 mask_ratio: 4 # (int) mask downsample ratio (segment train only)
 # Classification
 dropout: 0.0 # (float) use dropout regularization (classify train only)