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Docs improvements and redirect fixes (#16287)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2024-09-15 00:27:46 +02:00 • committed by GitHub
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docs/en/modes/val.md
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@ -47,7 +47,7 @@ These are the notable functionalities offered by YOLOv8's Val mode:
## Usage Examples
Validate trained YOLOv8n model accuracy on the COCO8 dataset. No argument need to passed as the `model` retains its training `data` and arguments as model attributes. See Arguments section below for a full list of export arguments.
Validate trained YOLOv8n model accuracy on the COCO8 dataset. No arguments are needed as the `model` retains its training `data` and arguments as model attributes. See Arguments section below for a full list of export arguments.
!!! example
@ -165,7 +165,7 @@ These benefits ensure that your models are evaluated thoroughly and can be optim
### Can I validate my YOLOv8 model using a custom dataset?
Yes, you can validate your YOLOv8 model using a custom dataset. Specify the `data` argument with the path to your dataset configuration file. This file should include paths to the validation data, class names, and other relevant details.
Yes, you can validate your YOLOv8 model using a [custom dataset](https://docs.ultralytics.com/datasets/). Specify the `data` argument with the path to your dataset configuration file. This file should include paths to the validation data, class names, and other relevant details.
Example in Python: