stage-3d: cockpit /train page — datasets + adapters + training metadata

New /train route lists built JSONL datasets (examples, size) and trained
adapters with their base model, hyperparameters, dataset provenance, and
loss history. train_qlora.py now records train_loss + per-step loss_history
into training_meta.json so future runs surface a loss curve in the cockpit.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

scripts/train_qlora.py

@@ -114,12 +114,18 @@ def main() -> None:
             report_to="none",
         ),
     )
-    trainer.train()
+    train_result = trainer.train()
 
     final_dir = output_dir / "final"
     final_dir.mkdir(parents=True, exist_ok=True)
     model.save_pretrained(str(final_dir))
     tokenizer.save_pretrained(str(final_dir))
+
+    loss_history = [
+        {"step": h["step"], "loss": h["loss"], "epoch": h.get("epoch")}
+        for h in trainer.state.log_history
+        if "loss" in h
+    ]
     (output_dir / "training_meta.json").write_text(json.dumps({
         "base_model": args.base_model,
         "lora_r": args.lora_r,
@@ -129,6 +135,8 @@ def main() -> None:
         "datasets": [str(p) for p in paths],
         "examples": len(examples),
         "seed": args.seed,
+        "train_loss": train_result.training_loss,
+        "loss_history": loss_history,
     }, indent=2))
     print(f"[psyc-train] adapter saved → {final_dir}")