model:
  name: "hfl/chinese-macbert-large"
  hidden_size: 1024
  num_heads: 8
  dropout: 0.1
  use_lora: false

data:
  train_path: "data/processed/train.jsonl"
  val_path: "data/processed/val.jsonl"
  test_path: "data/processed/test.jsonl"
  max_persona_len: 128
  max_context_len: 512
  max_response_len: 256
  max_history_turns: 5

training:
  epochs: 10
  batch_size: 16
  lr: 2e-5
  warmup_steps: 200
  weight_decay: 0.01
  gradient_clip: 1.0
  eval_steps: 200
  save_steps: 500

loss_weights:
  binary: 1.0
  level: 1.0
  primary: 1.0
  fine: 1.0

evaluation:
  binary_threshold: 0.5
  fine_threshold: 0.4

logging:
  project: "CompanionGuard-RL"
  run_name: "detector-macbert"
  use_wandb: true

output:
  checkpoint_dir: "checkpoints/detector"