fix: fine-tune config and generator improvements

scripts/train.py: fix max_seq_len 256→320 (must match pretrained checkpoint);
increase epochs 15→50 and patience 5→10 to give the small corpus enough
gradient steps; reduce warmup 20→10 (was 22% of total steps).

scripts/generate.py: default to prepending the tonic chord when --prefix is
not given; add --no-tonic-anchor to opt out.

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

scripts/generate.py

@@ -80,6 +80,8 @@ def main() -> None:
     ap.add_argument("--prefix", default=None,
                     help='Space-separated chord symbols in the requested key, '
                          'e.g. "Cmaj7 Am7".  Used as generation context.')
+    ap.add_argument("--no-tonic-anchor", action="store_true", dest="no_tonic_anchor",
+                    help="Do not prepend the tonic chord when --prefix is not given.")
     ap.add_argument("--temperature", type=float, default=1.0,
                     help="Sampling temperature (default: 1.0).")
     ap.add_argument("--top-p", type=float, default=0.9, dest="top_p",
@@ -112,7 +114,14 @@ def main() -> None:
     model = _load_model(args.checkpoint, device)
 
     target_key = f"{args.key}_{args.mode}"
-    prefix_chords = args.prefix.split() if args.prefix else None
+
+    if args.prefix:
+        prefix_chords = args.prefix.split()
+    elif not args.no_tonic_anchor:
+        # Default: anchor to tonic so generation stays in key.
+        prefix_chords = [args.key + ("m" if args.mode == "minor" else "")]
+    else:
+        prefix_chords = None
 
     period = generate_period(
         model=model,

scripts/train.py

@@ -54,13 +54,17 @@ TRAIN_CFG = TrainConfig(
     data_dir=DATA_DIR,
     output=CHECKPOINT,
     init_from=INIT_FROM,
-    epochs=15,
+    # Small corpus (~45 train files) → ~6 batches/epoch.
+    # 50 epochs × 6 = ~300 gradient steps; patience=10 gives a 60-step window.
+    epochs=50,
     batch_size=8,
     lr=1e-5,
-    warmup_steps=20,
+    warmup_steps=10,
+    patience=10,
     seed=42,
     device="auto",
-    max_seq_len=256,
+    # Must match pretrained checkpoint (max_seq_len=320).
+    max_seq_len=320,
 )