diff --git a/ultralytics/yolo/engine/model.py b/ultralytics/yolo/engine/model.py
index e7720e7..15ffd12 100644
--- a/ultralytics/yolo/engine/model.py
+++ b/ultralytics/yolo/engine/model.py
@@ -112,8 +112,9 @@ class YOLO:
         source (str): Accepts all source types accepted by yolo
         **kwargs : Any other args accepted by the predictors. Too see all args check 'configuration' section in the docs
         """
-        kwargs.update(self.overrides)
-        predictor = self.PredictorClass(overrides=kwargs)
+        overrides = self.overrides.copy()
+        overrides.update(kwargs)
+        predictor = self.PredictorClass(overrides=overrides)
 
         # check size type
         sz = predictor.args.imgsz
@@ -136,8 +137,9 @@ class YOLO:
         if not self.model:
             raise Exception("model not initialized!")
 
-        kwargs.update(self.overrides)
-        args = get_config(config=DEFAULT_CONFIG, overrides=kwargs)
+        overrides = self.overrides.copy()
+        overrides.update(kwargs)
+        args = get_config(config=DEFAULT_CONFIG, overrides=overrides)
         args.data = data or args.data
         args.task = self.task
 
diff --git a/ultralytics/yolo/engine/predictor.py b/ultralytics/yolo/engine/predictor.py
index 94b2b72..a1aefc0 100644
--- a/ultralytics/yolo/engine/predictor.py
+++ b/ultralytics/yolo/engine/predictor.py
@@ -46,7 +46,9 @@ class BasePredictor:
 
     def __init__(self, config=DEFAULT_CONFIG, overrides={}):
         self.args = get_config(config, overrides)
-        self.save_dir = increment_path(Path(self.args.project) / self.args.name, exist_ok=self.args.exist_ok)
+        project = overrides.get("project") or self.args.task
+        name = overrides.get("name") or self.args.mode
+        self.save_dir = increment_path(Path("runs") / project / name, exist_ok=self.args.exist_ok)
         (self.save_dir / 'labels' if self.args.save_txt else self.save_dir).mkdir(parents=True, exist_ok=True)
 
         self.done_setup = False
@@ -84,18 +86,6 @@ class BasePredictor:
         if is_url and is_file:
             source = check_file(source)  # download
 
-        # data
-        if self.data:
-            try:
-                if self.data.endswith(".yaml"):
-                    self.data = check_dataset_yaml(self.data)
-                else:
-                    self.data = check_dataset(self.data)
-            except AssertionError as e:
-                LOGGER.info(f"Error ocurred: {e}")
-            finally:
-                LOGGER.info("Predictor will continue without reading the dataset")
-
         # model
         device = select_device(self.args.device)
         model = model or self.args.model
diff --git a/ultralytics/yolo/engine/validator.py b/ultralytics/yolo/engine/validator.py
index aae1daa..f8fcd42 100644
--- a/ultralytics/yolo/engine/validator.py
+++ b/ultralytics/yolo/engine/validator.py
@@ -31,8 +31,11 @@ class BaseValidator:
         self.training = True
         self.speed = None
         self.jdict = None
-        self.save_dir = save_dir if save_dir is not None else \
-            increment_path(Path(self.args.project) / self.args.name, exist_ok=self.args.exist_ok)
+
+        project = self.args.project if self.args.project != "runs/train" else self.args.task
+        name = self.args.name if self.args.name != "exp" else self.args.mode
+        self.save_dir = increment_path(Path("runs") / project / name, exist_ok=self.args.exist_ok)
+        (self.save_dir / 'labels' if self.args.save_txt else self.save_dir).mkdir(parents=True, exist_ok=True)
 
     @smart_inference_mode()
     def __call__(self, trainer=None, model=None):