Update README.md

README.md

@@ -60,11 +60,11 @@ Using CodeCarbon, the model's carbon footprint and energy consumption will be tr
 Since this challenge's evaluation is based on 20% of the train dataset, we need to be vigilant when discussing model performance.  
 Indeed, a high accuracy in this part of the train dataset could hide the over-fitting of the model.
 
-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: 
+That is what I've been dealing with when reaching 0.911 accuracy of the model and 0.817 mean_iou on the train dataset: 
 I can see over-fitting while over-performance on the train dataset (see picture below).  
 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)
 <img src="https://cdn-uploads.huggingface.co/production/uploads/666354284044e2b1c3287c22/LptPoEeSGH22MG_XftxdP.png" alt="over-fitting" width="600">
 
-As a professional data scientist, another model has been trained and evaluated on the "val" dataset (see picture below)
+As a professional data scientist, I have trained anther model that has been evaluated on the "val" dataset (see picture below)
 <img src="https://cdn-uploads.huggingface.co/production/uploads/666354284044e2b1c3287c22/k00JqZDpHxGqKMweZQzw0.png" alt="No over-fitting" width="600">
 Still reaching a model accuracy of 0.907 and max iou of 0.808.