iomgaa
8958eee11b
config/train_videomme.yaml 同时收录待入库的实验配置变更(run_id v2 / concurrency 32 / batch_size 40)。tests/integration/test_v3_contract_e2e.py 的 run_id 断言按 Task 5 显式契约同步修正(原断言依赖旧隐式实例注入)。
64 lines
1.5 KiB
YAML
64 lines
1.5 KiB
YAML
# config/train_action_recognition.yaml
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# Action Recognition 单题型首次训练实验
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# 设计文档: research-wiki/designs/2026-07-14-action-recognition-training-design.md
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harness:
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workspace_dir: "workspaces/train-action-recognition"
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store_dir: store
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mode: train
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run_id: train_ar_v1
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concurrency: 24
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max_steps: 40
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skill_mode: auto
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n_samples: 0
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questions: "generated-v2-360"
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skills_version: v1
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prompts_version: v1
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epochs: 3
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# CE-Gate 参数（沿用 default.yaml）
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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_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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# 池配置 — per_category 单题型
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pool_split_mode: per_category
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task_types:
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- "Action Recognition"
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train_ratio: 0.667
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test_questions: "benchmarks/Video-MME"
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run_holdout_eval: false
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# mini-batch
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batch_size: 10
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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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trainable_min_units: 8
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early_stop_patience: 4
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test_size: 63
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diag_size: 20
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diag_correct_ratio: 0.5
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val_size: 10
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val_correct_ratio: 0.5
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use_slow_momentum: true
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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: "cuda"
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