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Update overlap_mask description. (#17324)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Mohammed Yasin 2024-11-05 08:20:48 +08:00 • committed by GitHub
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docs/en/macros/train-args.md
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@ -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. |