Restore full quality params now that GPU is available

- Max slices: 80 (use all audio)
- Batch size: 8
- Default epochs: 20
- Slider max: 50

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

app.py

@@ -112,7 +112,7 @@ def train_voice_model(audio_file, model_name, epochs, progress=gr.Progress()):
             model_name=model_name,
             epochs=int(epochs),
             sample_rate=40000,
-            batch_size=4,
+            batch_size=8,
             progress_callback=progress_callback,
         )
 
@@ -295,10 +295,10 @@ with gr.Blocks(
                     )
                     train_epochs = gr.Slider(
                         minimum=5,
-                        maximum=30,
-                        value=10,
+                        maximum=50,
+                        value=20,
                         step=5,
-                        label="Nombre d'époques (utilisé uniquement avec GPU)",
+                        label="Nombre d'époques (plus = meilleure qualité, ~3-5 min avec GPU)",
                     )
                     train_btn = gr.Button(
                         "Lancer l'entraînement",

pipeline/training.py

@@ -95,7 +95,7 @@ def preprocess(model_name: str, audio_path: str, sample_rate: int = 40000):
     segment_len_16k = int(3.5 * 16000)
     hop_16k = int(3.0 * 16000)
 
-    MAX_SLICES = 30  # Limit for CPU-feasible training
+    MAX_SLICES = 80  # Use all available audio for better quality
 
     n_slices = 0
     idx = 0
@@ -229,8 +229,8 @@ def extract_features(model_name: str, sample_rate: int = 40000, f0_method: str =
 def train_model(
     model_name: str,
     sample_rate: int = 40000,
-    total_epochs: int = 10,
-    batch_size: int = 4,
+    total_epochs: int = 20,
+    batch_size: int = 8,
 ):
     """
     Train RVC v2 model. Runs IN-PROCESS with mp.Process patched to avoid