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README.md
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Using CodeCarbon, the model's carbon footprint and energy consumption will be tracked, this information will help ensure the model's alignment with the sustainability objectives of the Frugal AI Challenge.
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## Results:
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Since
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Indeed, a high accuracy in
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That is what I've been dealing with when reaching 0.91 accuracy of the model and 0.81 mean_iou on the train dataset:
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I can see over-fitting while over-performance on the train dataset (see picture below)
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As a data scientist, another model has been trained and evaluated on the
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Using CodeCarbon, the model's carbon footprint and energy consumption will be tracked, this information will help ensure the model's alignment with the sustainability objectives of the Frugal AI Challenge.
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## Results:
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Since this challenge's evaluation is based on 20% of the train dataset, we need to be vigilant when discussing model performance.
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Indeed, a high accuracy in this part of the train dataset could hide the over-fitting of the model.
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That is what I've been dealing with when reaching 0.91 accuracy of the model and 0.81 mean_iou on the train dataset:
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I can see over-fitting while over-performance on the train dataset (see picture below).
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Due to this challenge evaluation criteria ,this model is used for submission and is called [yolo11_tr_20012025_frugalAIchal.pt](https://huggingface.co/spaces/tom-b974/Frugal_AI_image_2025/blob/main/yolo11_tr_20012025_frugalAIchal.pt)
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<img src="https://cdn-uploads.huggingface.co/production/uploads/666354284044e2b1c3287c22/LptPoEeSGH22MG_XftxdP.png" alt="Results on train dataset evaluation" width="600">
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As a professional data scientist, another model has been trained and evaluated on the "val" dataset (see picture below -soon)
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