# SAM2 LoRA Fine-tuning Configuration

model:
  checkpoint: ../sam2/checkpoints/sam2.1_hiera_small.pt
  config: sam2.1_hiera_s.yaml

data:
  root: ./crack500
  train_file: ./crack500/train.txt
  val_file: ./crack500/val.txt
  test_file: ./crack500/test.txt
  expand_ratio: 0.05  # Bbox expansion ratio

training:
  epochs: 50
  batch_size: 4
  learning_rate: 0.0001  # 1e-4
  weight_decay: 0.01
  gradient_accumulation_steps: 4

  # Early stopping
  patience: 10

  # Loss weights
  dice_weight: 0.5
  focal_weight: 0.5
  use_skeleton_loss: true
  skeleton_weight: 0.2

lora:
  strategy: B  # A (decoder-only), B (decoder+encoder), C (full)

system:
  num_workers: 4
  use_amp: true  # Mixed precision training
  save_freq: 5  # Save checkpoint every N epochs

wandb:
  use_wandb: false
  project: sam2-crack-lora
  entity: null

# Strategy-specific recommendations:
# Strategy A: batch_size=8, gradient_accumulation_steps=2, lr=1e-4, epochs=30
# Strategy B: batch_size=4, gradient_accumulation_steps=4, lr=5e-5, epochs=50
# Strategy C: batch_size=2, gradient_accumulation_steps=8, lr=3e-5, epochs=80