feat : train CLI 新增 val_split/val_step/metrics/log 参数

- --val_split 从训练集按比例切分验证集
- --val_step 控制验证间隔 optimizer step 数
- --metrics 自定义日志指标列表，默认 loss lr
- --log_dir / --log_interval 控制日志输出目录和频率

scripts/tools/train.py

@@ -135,6 +135,36 @@ def parse_args() -> argparse.Namespace:
         default="checkpoint",
         help="Directory to save checkpoints.",
     )
+    parser.add_argument(
+        "--val_split",
+        type=float,
+        default=None,
+        help="Ratio to split from training dataset for validation (e.g. 0.05).",
+    )
+    parser.add_argument(
+        "--val_step",
+        type=int,
+        default=1000,
+        help="Number of optimizer steps between validation runs.",
+    )
+    parser.add_argument(
+        "--metrics",
+        nargs="*",
+        default=["loss", "lr"],
+        help="Metrics to log (e.g. --metrics loss lr val_loss). Default: loss lr.",
+    )
+    parser.add_argument(
+        "--log_dir",
+        type=str,
+        default="checkpoint/logs",
+        help="Directory for metric logs.",
+    )
+    parser.add_argument(
+        "--log_interval",
+        type=int,
+        default=100,
+        help="Number of batch iterations between metric logs.",
+    )
     parser.add_argument(
         "--grpo_sync_interval",
         type=int,
@@ -234,6 +264,11 @@ def train(
     warmup_ratio: float,
     ckpt_interval: int,
     ckpt_dir: str,
+    val_split: float,
+    val_step: int,
+    metrics: list[str],
+    log_dir: str,
+    log_interval: int,
     dpo_beta: float,
     grpo_clip_eps: float,
     grpo_kl_coef: float,
@@ -341,6 +376,11 @@ def train(
         parallel_mode=parallel_mode,
         device_type=device_type,
         start_method=start_method,
+        val_split=val_split,
+        val_step=val_step,
+        metrics=metrics,
+        log_dir=log_dir,
+        log_interval=log_interval,
         gradient_checkpointing_modules=grad_ckpt_modules,
         executor_kwargs=executor_kwargs,
         extra_kwargs=strategy_kwargs,