text: Title: I try use one backbone and neck to achieve a multitask model (include pose and seg)
  Body: ### Search before asking
  
  - [x] I have searched the Ultralytics YOLO [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/orgs/ultralytics/discussions) and found no similar questions.
  
  
  ### Question
  
  I have already reviewed the related topics in the issue and Repositories .
  **Such as:**
  https://github.com/ultralytics/ultralytics/issues/6949
  https://github.com/ultralytics/ultralytics/pull/5219
  https://github.com/ultralytics/ultralytics/issues/5073
  https://github.com/yermandy/ultralytics/tree/multi-task-model
  https://github.com/stedavkle/ultralytics/tree/multitask
  https://github.com/JiayuanWang-JW/YOLOv8-multi-task
  
  My `PoSeg` Repositories base on https://github.com/stedavkle/ultralytics/tree/multitask **(Thank stedavkle)**
  
  Now My model has some error:
  During the training process, the accuracy for both keypoints and segmentation masks is 0, as follows:
  ``` shell
        Epoch    GPU_mem   box_loss  pose_loss   seg_loss  kobj_loss   cls_loss   dfl_loss  Instances       Size
        19/20         0G      3.686      9.066      5.869      4.282      1.412     0.7072         55        640: 100%|██████████| 2/2 [00:04<00:00,  2.05s/it]
                   Class     Images  Instances      Box(P          R      mAP50  mAP50-95)     Pose(P          R      mAP50  mAP50-95)     Mask(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00,  3.59it/s]
                     all          4         15          0          0          0          0          0          0          0          0          0          0          0          0
  
        Epoch    GPU_mem   box_loss  pose_loss   seg_loss  kobj_loss   cls_loss   dfl_loss  Instances       Size
        20/20         0G      3.689      10.34      5.701      4.333      1.571     0.7128         83        640: 100%|██████████| 2/2 [00:04<00:00,  2.12s/it]
                   Class     Images  Instances      Box(P          R      mAP50  mAP50-95)     Pose(P          R      mAP50  mAP50-95)     Mask(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:00<00:00,  3.54it/s]
                     all          4         15          0          0          0          0          0          0          0          0          0          0          0          0
  
  ```
  I am not sure which part has gone wrong, leading to the inference accuracy being 0 for all parts
  My yolo-poSeg address : https://github.com/Mosazh/yolo-poSeg
  
  ### Additional
  
  _No response_