Update README.md

README.md

@@ -32,7 +32,7 @@ The model leverages the transformer architecture to process image patches and pr
 
 ## Intended uses & limitations
 
-- **Intented Uses:** This model can be used to demonstrate object detection with ViT. It can potentially be used in safety applications to identify individuals wearing or not wearing hardhats in construction sites or industrial environments.
+- **Intended Uses:** This model can be used to demonstrate object detection with ViT. It can potentially be used in safety applications to identify individuals wearing or not wearing hardhats in construction sites or industrial environments.
 - **Limitations:** This model has been limitedly trained and may not generalize well to images with significantly different characteristics, viewpoints, or lighting conditions. It is not intended for production use without further evaluation and validation.
 
 ## Training and evaluation data
@@ -50,7 +50,7 @@ The model leverages the transformer architecture to process image patches and pr
     - Weight decay: 1e-4
     - Batch size: 1
     - Epochs: 3
-    - Max steps: 500
+    - Max steps: 2500
     - Optimizer: AdamW 
 - **Evaluation:** The model was evaluated on the test set using standard object detection metrics, including COCO metrics (Average Precision, Average Recall). 
 - **Hardware:** Training was performed on Google Colab using GPU acceleration.