docs: add observed batching results to training guide

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-06 00:05:16 +02:00
parent 1f8cd6f930
commit 39984f73c2
1 changed files with 2 additions and 0 deletions
@@ -199,6 +199,8 @@ The table below gives a rough scaling guide. Quality and diversity of recordings

 Higher batch size gives smoother loss curves and faster convergence. If you have headroom, prefer larger batches over more steps.

+**Observed results:** batch 16 reaches the same loss in ~2600 steps that batch 1 needed 8000+ steps to reach, with a near-perfectly smooth curve. On a 24 GB GPU, batch 16 is the recommended default for `large_44k`.
+
 ### Rank

 | Rank | Use case |