diff --git a/ultralytics/yolo/engine/model.py b/ultralytics/yolo/engine/model.py
index de3dc8d..6d3168b 100644
--- a/ultralytics/yolo/engine/model.py
+++ b/ultralytics/yolo/engine/model.py
@@ -250,6 +250,8 @@ class YOLO:
             self.predictor.setup_model(model=self.model, verbose=is_cli)
         else:  # only update args if predictor is already setup
             self.predictor.args = get_cfg(self.predictor.args, overrides)
+            if 'project' in overrides or 'name' in overrides:
+                self.predictor.save_dir = self.predictor.get_save_dir()
         return self.predictor.predict_cli(source=source) if is_cli else self.predictor(source=source, stream=stream)
 
     def track(self, source=None, stream=False, persist=False, **kwargs):
diff --git a/ultralytics/yolo/engine/predictor.py b/ultralytics/yolo/engine/predictor.py
index 32fea52..5a37878 100644
--- a/ultralytics/yolo/engine/predictor.py
+++ b/ultralytics/yolo/engine/predictor.py
@@ -65,14 +65,13 @@ class BasePredictor:
     Attributes:
         args (SimpleNamespace): Configuration for the predictor.
         save_dir (Path): Directory to save results.
-        done_setup (bool): Whether the predictor has finished setup.
+        done_warmup (bool): Whether the predictor has finished setup.
         model (nn.Module): Model used for prediction.
         data (dict): Data configuration.
         device (torch.device): Device used for prediction.
         dataset (Dataset): Dataset used for prediction.
         vid_path (str): Path to video file.
         vid_writer (cv2.VideoWriter): Video writer for saving video output.
-        annotator (Annotator): Annotator used for prediction.
         data_path (str): Path to data.
     """
 
@@ -85,9 +84,7 @@ class BasePredictor:
             overrides (dict, optional): Configuration overrides. Defaults to None.
         """
         self.args = get_cfg(cfg, overrides)
-        project = self.args.project or Path(SETTINGS['runs_dir']) / self.args.task
-        name = self.args.name or f'{self.args.mode}'
-        self.save_dir = increment_path(Path(project) / name, exist_ok=self.args.exist_ok)
+        self.save_dir = self.get_save_dir()
         if self.args.conf is None:
             self.args.conf = 0.25  # default conf=0.25
         self.done_warmup = False
@@ -108,6 +105,11 @@ class BasePredictor:
         self.callbacks = _callbacks or callbacks.get_default_callbacks()
         callbacks.add_integration_callbacks(self)
 
+    def get_save_dir(self):
+        project = self.args.project or Path(SETTINGS['runs_dir']) / self.args.task
+        name = self.args.name or f'{self.args.mode}'
+        return increment_path(Path(project) / name, exist_ok=self.args.exist_ok)
+
     def preprocess(self, im):
         """Prepares input image before inference.