How to increase YOLOS precision?

moschimonsters · October 27, 2023, 8:52am

I created a custom dataset (400 images with 4 categories, split 80(train) - 20(validation)) for detecting layout elements in scanned pages (images, tables, headers, etc.). I finetuned the hustvl/yolos-base model with it using the tutorial from Niels Rogge:

github.com

NielsRogge/Transformers-Tutorials/blob/master/YOLOS/Fine_tuning_YOLOS_for_object_detection_on_custom_dataset_(balloon).ipynb

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        "## Fine-tuning YOLOS on a custom dataset for object detection\n",
        "\n",

This file has been truncated. show original

The finetuning is working and the model is detecting the things i want on test images, but often the bounding box predictions are not as precise as i want them to be and the confidence for some (correctly) detected objects is very low.

So what option (if any) would be promising to get better precision from the model?

more training data
longer training
changing hyperparameters

Thanks for any help and suggestions in advance. I attached the loss plot for more info.

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How to increase YOLOS precision?

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