ultralytics 8.0.141 create new SettingsManager (#3790)

docs/modes/val.md

@@ -19,14 +19,14 @@ Validate trained YOLOv8n model accuracy on the COCO128 dataset. No argument need
 !!! example ""
 
     === "Python"
-    
+
         ```python
         from ultralytics import YOLO
-        
+
         # Load a model
         model = YOLO('yolov8n.pt')  # load an official model
         model = YOLO('path/to/best.pt')  # load a custom model
-        
+
         # Validate the model
         metrics = model.val()  # no arguments needed, dataset and settings remembered
         metrics.box.map    # map50-95
@@ -35,7 +35,7 @@ Validate trained YOLOv8n model accuracy on the COCO128 dataset. No argument need
         metrics.box.maps   # a list contains map50-95 of each category
         ```
     === "CLI"
-    
+
         ```bash
         yolo detect val model=yolov8n.pt  # val official model
         yolo detect val model=path/to/best.pt  # val custom model
@@ -61,4 +61,4 @@ Validation settings for YOLO models refer to the various hyperparameters and con
 | `plots`       | `False` | show plots during training                                         |
 | `rect`        | `False` | rectangular val with each batch collated for minimum padding       |
 | `split`       | `val`   | dataset split to use for validation, i.e. 'val', 'test' or 'train' |
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+|