diff --git a/src/tias_judge_model/training/cross_validation.py b/src/tias_judge_model/training/cross_validation.py
index aa80e85..e03dc6c 100644
--- a/src/tias_judge_model/training/cross_validation.py
+++ b/src/tias_judge_model/training/cross_validation.py
@@ -15,7 +15,7 @@
 
 import logging
 import time
-from collections.abc import Sequence
+from collections.abc import Mapping, Sequence
 from dataclasses import dataclass, field
 from pathlib import Path
 
@@ -200,9 +200,9 @@
         for name, counts in group_counts.items():
             logger.info("%s: %s のグループ別枚数 %s", prefix, name, counts)
 
-        train_idx = np.array([position[r.image_path] for r in train_records], dtype=np.int64)
-        val_idx = np.array([position[r.image_path] for r in val_records], dtype=np.int64)
-        held_idx = np.array([position[r.image_path] for r in held_records], dtype=np.int64)
+        train_idx = _positions(train_records, position)
+        val_idx = _positions(val_records, position)
+        held_idx = _positions(held_records, position)
 
         seed_everything(seed)
         model = create_model(config.model.name, pretrained=config.model.pretrained).to(device)
@@ -270,6 +270,11 @@
     return result
 
 
+def _positions(records: Sequence[ManifestRecord], position: Mapping[str, int]) -> np.ndarray:
+    # `(N,)` の int64．各レコードの manifest 上の位置（0 始まり）．
+    return np.array([position[r.image_path] for r in records], dtype=np.int64)
+
+
 def _make_loader(
     images: np.ndarray,
     labels: np.ndarray,
diff --git a/src/tias_judge_model/training/loop.py b/src/tias_judge_model/training/loop.py
index d67f706..0074708 100644
--- a/src/tias_judge_model/training/loop.py
+++ b/src/tias_judge_model/training/loop.py
@@ -13,7 +13,6 @@
 import time
 from collections.abc import Callable
 from dataclasses import dataclass, field
-from typing import Any
 
 import numpy as np
 import torch
@@ -66,11 +65,6 @@
     history: list[EpochRecord] = field(default_factory=list)
     seconds: float = 0.0
 
-    @property
-    def epochs_run(self) -> int:
-        """実際に回したエポック数."""
-        return len(self.history)
-
 
 def seed_everything(seed: int) -> None:
     """`random`・`numpy`・`torch`（CUDA を含む）の乱数 seed を固定する.
@@ -261,19 +255,3 @@
     if not logits:
         return np.zeros((0, 0), dtype=np.float32), np.zeros((0,), dtype=np.int64)
     return np.concatenate(logits), np.concatenate(labels)
-
-
-def summarize_history(history: list[EpochRecord]) -> dict[str, Any]:
-    """エポックの記録から所要時間の要約（エポック数・1 エポックあたり平均秒数）を返す.
-
-    Args:
-        history: エポックごとの記録．
-
-    Returns:
-        `{"epochs_run", "mean_epoch_seconds"}`．
-    """
-    seconds = [h.seconds for h in history]
-    return {
-        "epochs_run": len(history),
-        "mean_epoch_seconds": float(np.mean(seconds)) if seconds else None,
-    }