General description
All of Ultralytics' Yolo V11 models model fined tuned for billboard detection using the Billboard dataset.
This model was created with 100 epochs using CUDA 12.4 and Pytorch 2.6.0.
Best Metrics Comparison
Model | Precision (Epoch) | Recall (Epoch) | mAP50 (Epoch) | mAP50-95 (Epoch) |
---|---|---|---|---|
YOLO_11n | 0.73613 (epoch: 66) | 0.67308 (epoch: 88) | 0.70351 (epoch: 87) | 0.43033 (epoch: 80) |
YOLO_11s | 0.7225 (epoch: 98) | 0.67735 (epoch: 81) | 0.70855 (epoch: 76) | 0.43518 (epoch: 77) |
YOLO_11m | 0.73249 (epoch: 80) | 0.6745 (epoch: 73) | 0.71053 (epoch: 87) | 0.43404 (epoch: 62) |
YOLO_11l | 0.74729 (epoch: 98) | 0.68174 (epoch: 49) | 0.71778 (epoch: 75) | 0.44731 (epoch: 89) |
YOLO_11x | 0.74299 (epoch: 94) | 0.6688 (epoch: 80) | 0.7113 (epoch: 60) | 0.4437 (epoch: 89) |
Further results can be found in Results Folder.
Created by Mark Colley - supported by Zefwih
- Downloads last month
- 51
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support
HF Inference deployability: The HF Inference API does not support object-detection models for ultralytics
library.
Model tree for maco018/billboard-detection-Yolo11
Base model
Ultralytics/YOLO11