text: _base_ = './sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480-800_3x_bdd100k.py'
  
  model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
  optimizer = dict(_delete_=True, type='AdamW', lr=0.000025/2, weight_decay=0.0001)
  data = dict(
      samples_per_gpu=1,
      workers_per_gpu=1,
  )