feat(harness): add Action Recognition training experiment

- PerCategoryPoolStrategy: filter test pool by task_types
- RunConfig: add run_holdout_eval toggle (default true)
- load_config: fix YAML task_types list-to-tuple conversion
- Runner: conditionally skip _holdout_four_way when disabled
- CLI: add --no-run-holdout-eval flag
- New config/train_action_recognition.yaml (3 epochs, per_category)
- New scripts/train_action_recognition.sh (baseline + seed + train)

app/harness/config.py

@@ -90,6 +90,7 @@ class RunConfig:
         pool_split_mode: 池划分策略，"global"（全局统一划分）/ "per_category"（按类别独立划分）。
         train_ratio: 训练集占比，范围 (0, 1)。
         test_questions: 测试题目集路径（相对路径）。
+        run_holdout_eval: 是否在 epoch 末执行 held-out 四向评估，默认 True。
     """
 
     # ── 必填字段（无默认值，来自 YAML 或 CLI） ──
@@ -145,6 +146,7 @@ class RunConfig:
     pool_split_mode: str = "global"
     train_ratio: float = 0.667
     test_questions: str = "benchmarks/Video-MME"
+    run_holdout_eval: bool = True
 
 
 def _validate(config: RunConfig) -> None:
@@ -439,6 +441,10 @@ def load_config(
         if field_name in yaml_data:
             yaml_data[field_name] = Path(yaml_data[field_name])
 
+    # Phase 4b: 类型转换 — task_types list → tuple
+    if "task_types" in yaml_data and yaml_data["task_types"] is not None:
+        yaml_data["task_types"] = tuple(yaml_data["task_types"])
+
     # Phase 5: 构造并校验
     config = RunConfig(**{k: v for k, v in yaml_data.items() if k in valid_fields})
     _validate(config)