102 lines
2.4 KiB
YAML
102 lines
2.4 KiB
YAML
# config/default.yaml
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# 全量默认参数，所有非敏感配置的唯一默认值来源。
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# 优先级: CLI args > .env > 此文件。敏感信息在 .env 中管理。
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# ── 建树模块 ──
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tree:
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max_paragraphs_per_l2: 5
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l1_segment_duration: 600.0 # L1 段时长（秒）
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l2_clip_duration: 60.0 # L2 clip 时长（秒）
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l3_fps: 0.5 # L3 帧提取频率（帧/秒）
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l2_representative_frames: 6 # L2 VLM 描述用的代表帧数
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cache_dir: "cache/trees"
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concurrency: 16 # asyncio Semaphore 上限
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subtitle_inject: true # 建树时是否注入 SRT 字幕
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srt_window_sec: 5.0 # 字幕匹配时间窗口（前后各 N 秒）
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# ── Embedding ──
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embed:
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backend: "local"
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model_name: "BAAI/bge-base-zh-v1.5"
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embed_dim: 768
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device: "cpu"
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# ── 可训练检索器 ──
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retriever:
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embed_dim: 768
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num_heads: 4
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L_layers: 2
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L_cycles: 4
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max_rounds: 5
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ffn_expansion: 2.0
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checkpoint: null
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k_l1: 1
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k_l2: 1
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k_l3: 1
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max_paths: 5
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# ── 检索器训练 ──
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train:
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lr: 1.0e-4
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weight_decay: 1.0e-5
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batch_size: 1
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max_epochs_phase1: 30
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max_epochs_phase2: 20
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nav_loss_weight: 1.0
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act_loss_weight: 0.1
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margin_loss_weight: 0.5
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act_lambda_step: 0.1
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act_gamma: 0.9
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eval_interval: 5
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save_dir: "checkpoints"
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dataset: "videomme"
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dataset_path: "data/videomme/splits/train.jsonl"
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# ── Harness 自进化循环 ──
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harness:
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workspace_dir: "workspaces/default"
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store_dir: store
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mode: infer
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concurrency: 12
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max_steps: 15
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skill_mode: auto
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n_samples: 0
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questions: "benchmarks/Video-MME"
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skills_version: v1
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prompts_version: v1
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epochs: 1
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# CE-Gate 参数
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gate_e_confirm: 20.0
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gate_e_provisional: 3.0
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gate_w_net_min: 2
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gate_delta_min: 0.02
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gate_lambda_dir: -0.642
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gate_e_rollback: 10.0
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gate_block: 8
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gate_n_max: 40
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gate_p_low: 0.05
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gate_p_high: 0.95
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gate_probe_quota: 0.2
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gate_gamma_decay: 0.9
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gate_cooldown_steps: 2
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gate_guard_err: 0.10
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# 进化参数
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edit_budget_start: 5
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edit_budget_end: 2
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skill_update_mode: patch
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appendix_consolidate_threshold: 6
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# 数据池
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diag_size: 200
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diag_correct_ratio: 0.5
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val_size: 30
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val_correct_ratio: 0.5
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test_size: 60
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# mini-batch
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batch_size: 15
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min_class_per_batch: 2
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batch_correct_ratio: 0.5
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momentum_samples: 20
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eval_min_per_class: 2
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early_stop_patience: 8
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use_slow_momentum: true
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