text: Title: Which hyperparameters are suitable for me?
  Body: ### Search before asking
  
  - [x] I have searched the Ultralytics YOLO [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/ultralytics/ultralytics/discussions) and found no similar questions.
  
  
  ### Question
  
  Hello. I've already done finetuning and just trained YOLOv11 from scratch. But I have the following problem. Your pretrained model works well with the `car` class in some scenes that I need, but poorly in others that I also need. When I do finetuning of your pretrained model, for some reason, where your model coped well, the quality drops, and where it did not recognize anything, everything is fine. For some reason, somehow finetuning spoils what is already good and improves what was bad. I want to adapt YOLOv11 to work at night.
  
  Can you tell me what hyperparameters I need to set so that everything is fine and the way I need it? YOLOv4 just does what it needs to do for some reason. And I want a newer version of YOLO. Maybe I need to freeze something or turn on augmentation?
  
  Here is my training startup configuration:
  ```
  task: detect
  mode: train
  model: yolov11m.yaml
  data: ./yolov11_custom.yaml
  epochs: 500
  time: null
  patience: 100
  batch: 32
  imgsz: 640
  save: true
  save_period: -1
  val_period: 1
  cache: false
  device: 0
  workers: 8
  project: /YOLOv11_m_night_640
  name: yolov11_custom_night
  exist_ok: false
  pretrained: true
  optimizer: auto
  verbose: true
  seed: 0
  deterministic: true
  single_cls: false
  rect: false
  cos_lr: false
  close_mosaic: 10
  resume: false
  amp: true
  fraction: 1.0
  profile: false
  freeze: null
  multi_scale: false
  overlap_mask: true
  mask_ratio: 4
  dropout: 0.0
  val: true
  split: val
  save_json: false
  save_hybrid: false
  conf: null
  iou: 0.7
  max_det: 300
  half: false
  dnn: false
  plots: true
  source: null
  vid_stride: 1
  stream_buffer: false
  visualize: false
  augment: false
  agnostic_nms: false
  classes: null
  retina_masks: false
  embed: null
  show: false
  save_frames: false
  save_txt: false
  save_conf: false
  save_crop: false
  show_labels: true
  show_conf: true
  show_boxes: true
  line_width: null
  format: torchscript
  keras: false
  optimize: false
  int8: false
  dynamic: false
  simplify: false
  opset: null
  workspace: 4
  nms: false
  lr0: 0.01
  lrf: 0.01
  momentum: 0.937
  weight_decay: 0.0005
  warmup_epochs: 3.0
  warmup_momentum: 0.8
  warmup_bias_lr: 0.1
  box: 7.5
  cls: 0.5
  dfl: 1.5
  pose: 12.0
  kobj: 1.0
  label_smoothing: 0.0
  nbs: 64
  hsv_h: 0.015
  hsv_s: 0.7
  hsv_v: 0.4
  degrees: 0.0
  translate: 0.1
  scale: 0.5
  shear: 0.0
  perspective: 0.0
  flipud: 0.0
  fliplr: 0.5
  bgr: 0.0
  mosaic: 1.0
  mixup: 0.0
  copy_paste: 0.0
  auto_augment: randaugment
  erasing: 0.4
  crop_fraction: 1.0
  cfg: null
  tracker: botsort.yaml
  save_dir: /YOLOv11_m_night_640
  ```
  
  my `yolov11_custom.yaml`:
  ```
  path: ./data
  train: ./data/train.txt
  val: /data/val.txt
  
  # Classes
  names:
    0: trailer
    1: train
    2: trafficlight
    3: sign
    4: bus
    5: truck
    6: person
    7: bicycle
    8: motorcycle
    9: car
    10: streetlight
  ```
  
  @glenn-jocher @Y-T-G and others. Please help me.
  
  ### Additional
  
  _No response_