feat: spectral metrics per eval sample in experiment summary

Computes hf_energy_ratio (>4kHz), spectral_centroid_hz, spectral_rolloff_hz
at each save_every checkpoint. Logged to console and stored in
experiment_summary.json under results.spectral_metrics[step].

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

nodes/selva_lora_scheduler.py

@@ -429,6 +429,7 @@ class SelvaLoraScheduler:
                 duration          = time.monotonic() - t_start
                 loss_history      = r["loss_history"]
                 grad_norm_history = r.get("grad_norm_history", [])
+                spectral_metrics  = r.get("spectral_metrics", {})
                 run_start_step    = r.get("start_step", 0)
                 smoothed          = _smooth_losses(loss_history) if loss_history else []
 
@@ -460,6 +461,7 @@ class SelvaLoraScheduler:
                     ),
                     "loss_history":         [round(v, 6) for v in loss_history],
                     "grad_norm_history":    grad_norm_history,
+                    "spectral_metrics":     {str(k): v for k, v in spectral_metrics.items()},
                     "log_interval":         log_interval,
                     "duration_seconds":     round(duration, 1),
                 }