diff --git a/synapse_net/training/supervised_training.py b/synapse_net/training/supervised_training.py
index 3a2cebc0..1c463238 100644
--- a/synapse_net/training/supervised_training.py
+++ b/synapse_net/training/supervised_training.py
@@ -201,6 +201,7 @@ def supervised_training(
     in_channels: int = 1,
     out_channels: int = 2,
     mask_channel: bool = False,
+    checkpoint_path: Optional[str] = None,
     **loader_kwargs,
 ):
     """Run supervised segmentation training.
@@ -243,6 +244,7 @@ def supervised_training(
         out_channels: The number of output channels of the UNet.
         mask_channel: Whether the last channels in the labels should be used for masking the loss.
             This can be used to implement more complex masking operations and is not compatible with `ignore_label`.
+        checkpoint_path: Path to the directory where 'best.pt' resides; continue training this model.
         loader_kwargs: Additional keyword arguments for the dataloader.
     """
     train_loader = get_supervised_loader(train_paths, raw_key, label_key, patch_shape, batch_size,
@@ -265,6 +267,9 @@ def supervised_training(
         model = get_2d_model(out_channels=out_channels, in_channels=in_channels)
     else:
         model = get_3d_model(out_channels=out_channels, in_channels=in_channels)
+    
+    if checkpoint_path:
+        model = torch_em.util.load_model(checkpoint=checkpoint_path)
 
     loss, metric = None, None
     # No ignore label -> we can use default loss.