# config/train_ar30.yaml
# Action Recognition 训练 — 基于 SubPattern 靶向生成的 30 题
# 对比基线: v2-360 的 AR 题（100% 单帧，训练无效）
# 本次: AR30 题（6 种失败子模式靶向，跨段时序）

harness:
  workspace_dir: "workspaces/train-ar30"
  store_dir: store
  mode: train
  run_id: train_ar30_v1
  concurrency: 24
  max_steps: 40
  skill_mode: auto
  n_samples: 0
  questions: "generated-ar30"
  skills_version: v1
  prompts_version: v1
  epochs: 3
  # CE-Gate 参数（沿用 default.yaml）
  gate_e_confirm: 20.0
  gate_e_provisional: 3.0
  gate_w_net_min: 2
  gate_delta_min: 0.02
  gate_lambda_dir: -0.642
  gate_e_rollback: 10.0
  gate_block: 8
  gate_n_max: 40
  gate_p_low: 0.05
  gate_p_high: 0.95
  gate_probe_quota: 0.2
  gate_gamma_decay: 0.9
  gate_cooldown_steps: 2
  gate_guard_err: 0.10
  # 进化参数
  edit_budget_start: 5
  edit_budget_end: 2
  skill_update_mode: patch
  appendix_consolidate_threshold: 6
  # 池配置 — per_category 单题型
  pool_split_mode: per_category
  task_types:
    - "Action Recognition"
  train_ratio: 0.667
  test_questions: "benchmarks/Video-MME"
  run_holdout_eval: false
  # mini-batch
  batch_size: 10
  min_class_per_batch: 2
  batch_correct_ratio: 0.5
  momentum_samples: 20
  eval_min_per_class: 2
  trainable_min_units: 8
  early_stop_patience: 4
  test_size: 63
  diag_size: 20
  diag_correct_ratio: 0.5
  val_size: 10
  val_correct_ratio: 0.5
  use_slow_momentum: true

embed:
  backend: "local"
  model_name: "BAAI/bge-base-zh-v1.5"
  embed_dim: 768
  device: "cuda"
