update

examples/mpnet_aishell/step_2_train_model.py

@@ -166,6 +166,11 @@ def main():
     generator = MPNetPretrainedModel(config).to(device)
     discriminator = MetricDiscriminatorPretrainedModel(config).to(device)
 
+    # resume training
+    for epoch_i in serialization_dir.glob("epoch-*"):
+        print(epoch_i)
+    exit(0)
+
     # optimizer
     logger.info("prepare optimizer, lr_scheduler")
     num_params = 0
@@ -353,7 +358,7 @@ def main():
         if best_metric is None:
             best_idx_epoch = idx_epoch
             best_metric = pesq_metric
-        elif pesq_metric < best_metric:
+        elif pesq_metric > best_metric:
             best_idx_epoch = idx_epoch
             best_metric = pesq_metric
         else: