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  1. README.md +4 -6
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@@ -41,10 +41,8 @@ The model accurately detects oversized wagon numbers painted on the side of frei
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  | Metric | Score |
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  |--------|-------|
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- | Precision | `XX.X%` |
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- | Recall | `XX.X%` |
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- | F1 Score | `XX.X%` |
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- | Accuracy | `XX.X%` |
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  <!-- 🔧 TODO: Replace XX.X% with your actual metric values -->
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@@ -53,7 +51,7 @@ The model accurately detects oversized wagon numbers painted on the side of frei
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  ### Dataset
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  - **Source:** Custom-annotated dataset of railway wagon images
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- - **Size:** `X,XXX` images <!-- TODO: fill in -->
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  - **Annotation format:** YOLO (bounding boxes)
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  - **Classes:** 1 (big_number)
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  - **Train/Val split:** 80/20
@@ -65,7 +63,7 @@ The model accurately detects oversized wagon numbers painted on the side of frei
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  | Base model | YOLOv8n / YOLOv8s <!-- specify which --> |
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  | Image size | 640 |
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  | Batch size | 16 |
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- | Epochs | `XXX` |
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  | Optimizer | AdamW |
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  | Learning rate | 0.01 |
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  | Device | NVIDIA GPU |
 
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  | Metric | Score |
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  |--------|-------|
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+ | F1 Score | `98.1%` |
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+
 
 
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  <!-- 🔧 TODO: Replace XX.X% with your actual metric values -->
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  ### Dataset
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  - **Source:** Custom-annotated dataset of railway wagon images
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+ - **Size:** 1240X800 images <!-- TODO: fill in -->
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  - **Annotation format:** YOLO (bounding boxes)
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  - **Classes:** 1 (big_number)
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  - **Train/Val split:** 80/20
 
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  | Base model | YOLOv8n / YOLOv8s <!-- specify which --> |
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  | Image size | 640 |
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  | Batch size | 16 |
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+ | Epochs | `4` |
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  | Optimizer | AdamW |
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  | Learning rate | 0.01 |
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  | Device | NVIDIA GPU |