Instructions to use merve/rfdetr-road-signs-agree2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use merve/rfdetr-road-signs-agree2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="merve/rfdetr-road-signs-agree2")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("merve/rfdetr-road-signs-agree2") model = AutoModelForObjectDetection.from_pretrained("merve/rfdetr-road-signs-agree2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
rfdetr-road-signs-agree2
This model is a fine-tuned version of Roboflow/rf-detr-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 13.9987
- Map: 0.185
- Map 50: 0.2141
- Map 75: 0.206
- Map Small: 0.0727
- Map Medium: 0.2826
- Map Large: 0.1566
- Mar 1: 0.7158
- Mar 10: 0.8337
- Mar 100: 0.8425
- Mar Small: 0.225
- Mar Medium: 0.7327
- Mar Large: 0.8234
- Map Bus Stop: 0.5739
- Mar 100 Bus Stop: 1.0
- Map Do Not Enter: 0.151
- Mar 100 Do Not Enter: 0.9462
- Map Do Not Stop: 0.0515
- Mar 100 Do Not Stop: 0.9625
- Map Do Not Turn L: 0.0614
- Mar 100 Do Not Turn L: 1.0
- Map Do Not Turn R: 0.1336
- Mar 100 Do Not Turn R: 0.94
- Map Do Not U Turn: 0.0672
- Mar 100 Do Not U Turn: 0.9222
- Map Enter Left Lane: -1.0
- Mar 100 Enter Left Lane: -1.0
- Map Green Light: 0.5422
- Mar 100 Green Light: 0.8667
- Map Left Right Lane: 0.2297
- Mar 100 Left Right Lane: 0.9778
- Map No Parking: 0.0649
- Mar 100 No Parking: 0.975
- Map Parking: 0.01
- Mar 100 Parking: 0.9667
- Map Ped Crossing: 0.1775
- Mar 100 Ped Crossing: 0.92
- Map Ped Zebra Cross: 0.0
- Mar 100 Ped Zebra Cross: 0.0
- Map Railway Crossing: 0.0396
- Mar 100 Railway Crossing: 0.94
- Map Red Light: 0.0853
- Mar 100 Red Light: 0.4636
- Map Stop: 0.3227
- Mar 100 Stop: 0.9538
- Map Traffic Light: 0.0872
- Mar 100 Traffic Light: 0.7065
- Map U Turn: 0.0204
- Mar 100 U Turn: 0.975
- Map Warning: 0.6498
- Mar 100 Warning: 0.9588
- Map Yellow Light: 0.2469
- Mar 100 Yellow Light: 0.5333
- Map T Intersection L: -1.0
- Mar 100 T Intersection L: -1.0
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.05
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Bus Stop | Mar 100 Bus Stop | Map Do Not Enter | Mar 100 Do Not Enter | Map Do Not Stop | Mar 100 Do Not Stop | Map Do Not Turn L | Mar 100 Do Not Turn L | Map Do Not Turn R | Mar 100 Do Not Turn R | Map Do Not U Turn | Mar 100 Do Not U Turn | Map Green Light | Mar 100 Green Light | Map Left Right Lane | Mar 100 Left Right Lane | Map No Parking | Mar 100 No Parking | Map Parking | Mar 100 Parking | Map Ped Crossing | Mar 100 Ped Crossing | Map Ped Zebra Cross | Mar 100 Ped Zebra Cross | Map Railway Crossing | Mar 100 Railway Crossing | Map Red Light | Mar 100 Red Light | Map Stop | Mar 100 Stop | Map Traffic Light | Mar 100 Traffic Light | Map U Turn | Mar 100 U Turn | Map Warning | Mar 100 Warning | Map Yellow Light | Mar 100 Yellow Light | Map Enter Left Lane | Mar 100 Enter Left Lane | Map T Intersection L | Mar 100 T Intersection L |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45.9286 | 1.0 | 117 | 29.2449 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0019 | 0.0054 | 0.0 | 0.0 | 0.0057 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.1029 | 0.0 | 0.0 | -1.0 | -1.0 | -1.0 | -1.0 |
| 15.6887 | 2.0 | 234 | 20.3756 | 0.0002 | 0.0007 | 0.0001 | 0.0 | 0.0 | 0.0003 | 0.0023 | 0.0211 | 0.0415 | 0.0 | 0.0 | 0.0453 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0444 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0002 | 0.1355 | 0.0 | 0.0 | 0.0043 | 0.6088 | 0.0 | 0.0 | -1.0 | -1.0 | -1.0 | -1.0 |
| 12.5560 | 3.0 | 351 | 16.4438 | 0.0062 | 0.012 | 0.006 | 0.0 | 0.0 | 0.0066 | 0.0468 | 0.085 | 0.1182 | 0.0 | 0.0 | 0.1283 | 0.0 | 0.0 | 0.0141 | 0.2385 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0008 | 0.2444 | 0.0152 | 0.5375 | 0.0 | 0.0 | 0.0001 | 0.05 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0014 | 0.3258 | 0.0 | 0.0 | 0.0862 | 0.85 | 0.0 | 0.0 | -1.0 | -1.0 | -1.0 | -1.0 |
| 10.7193 | 4.0 | 468 | 13.3856 | 0.0183 | 0.0254 | 0.0214 | 0.0 | 0.0521 | 0.0193 | 0.1882 | 0.2513 | 0.2741 | 0.0 | 0.1033 | 0.2766 | 0.0 | 0.0 | 0.0304 | 0.7692 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0029 | 0.3167 | 0.0081 | 0.4056 | 0.0191 | 0.825 | 0.0 | 0.0 | 0.0174 | 0.84 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0237 | 0.5692 | 0.0295 | 0.571 | 0.0 | 0.0 | 0.2174 | 0.9118 | 0.0 | 0.0 | -1.0 | -1.0 | -1.0 | -1.0 |
| 10.0170 | 5.0 | 585 | 13.3941 | 0.0787 | 0.1073 | 0.0886 | 0.0252 | 0.1605 | 0.0601 | 0.435 | 0.5432 | 0.5632 | 0.15 | 0.5753 | 0.5459 | 0.0 | 0.0 | 0.0199 | 0.9077 | 0.0 | 0.0 | 0.0595 | 0.9667 | 0.092 | 0.96 | 0.0181 | 0.9111 | 0.2831 | 0.8 | 0.0501 | 0.9667 | 0.0737 | 0.8375 | 0.0 | 0.0 | 0.0246 | 0.97 | 0.0 | 0.0 | 0.1993 | 0.4 | 0.0323 | 0.2273 | 0.1234 | 0.8769 | 0.0578 | 0.671 | 0.0 | 0.0 | 0.3084 | 0.95 | 0.1541 | 0.2556 | -1.0 | -1.0 | -1.0 | -1.0 |
| 9.6411 | 6.0 | 702 | 12.7907 | 0.0803 | 0.1014 | 0.0911 | 0.0144 | 0.1578 | 0.0668 | 0.4997 | 0.6113 | 0.6256 | 0.1 | 0.61 | 0.6068 | 0.0 | 0.0 | 0.1028 | 0.9462 | 0.0 | 0.0 | 0.0162 | 0.9667 | 0.0417 | 0.96 | 0.0587 | 0.9222 | -1.0 | -1.0 | 0.3469 | 0.85 | 0.068 | 0.9556 | 0.0575 | 0.9375 | 0.0048 | 0.2333 | 0.0588 | 0.95 | 0.0 | 0.0 | 0.0127 | 0.6 | 0.0446 | 0.3 | 0.074 | 0.8923 | 0.057 | 0.6645 | 0.0251 | 0.475 | 0.4683 | 0.9441 | 0.0876 | 0.2889 | -1.0 | -1.0 |
| 9.0429 | 7.0 | 819 | 13.1367 | 0.1297 | 0.1578 | 0.1486 | 0.061 | 0.2856 | 0.1026 | 0.6832 | 0.822 | 0.8312 | 0.1875 | 0.6993 | 0.8165 | 0.0689 | 0.95 | 0.1095 | 0.9615 | 0.0783 | 0.9375 | 0.0369 | 1.0 | 0.1225 | 0.94 | 0.0494 | 0.9444 | -1.0 | -1.0 | 0.5129 | 0.8167 | 0.0868 | 0.9778 | 0.0413 | 0.9625 | 0.0211 | 0.9333 | 0.1412 | 0.94 | 0.0 | 0.0 | 0.0246 | 0.88 | 0.0469 | 0.3909 | 0.127 | 0.9846 | 0.0899 | 0.6839 | 0.0169 | 1.0 | 0.58 | 0.9559 | 0.3108 | 0.5333 | -1.0 | -1.0 |
| 9.1348 | 8.0 | 936 | 13.6453 | 0.1427 | 0.1709 | 0.1623 | 0.0748 | 0.2836 | 0.1126 | 0.7124 | 0.818 | 0.8314 | 0.2125 | 0.742 | 0.8127 | 0.0392 | 1.0 | 0.1617 | 0.9538 | 0.0805 | 0.975 | 0.0277 | 0.9667 | 0.0774 | 0.96 | 0.0586 | 0.9333 | -1.0 | -1.0 | 0.5348 | 0.85 | 0.1807 | 0.9667 | 0.0992 | 0.975 | 0.0154 | 0.9333 | 0.2365 | 0.93 | 0.0 | 0.0 | 0.0381 | 0.78 | 0.0664 | 0.4455 | 0.1491 | 0.9308 | 0.0932 | 0.7161 | 0.0236 | 0.975 | 0.5626 | 0.9618 | 0.2663 | 0.5444 | -1.0 | -1.0 |
| 8.7580 | 9.0 | 1053 | 14.0408 | 0.1607 | 0.1895 | 0.1806 | 0.0819 | 0.297 | 0.1369 | 0.7046 | 0.8278 | 0.8351 | 0.2625 | 0.7227 | 0.8199 | 0.1769 | 1.0 | 0.145 | 0.9462 | 0.1206 | 0.9625 | 0.0458 | 1.0 | 0.0676 | 0.94 | 0.0674 | 0.9111 | -1.0 | -1.0 | 0.5253 | 0.8167 | 0.2417 | 0.9722 | 0.0866 | 0.9625 | 0.0153 | 0.9667 | 0.1702 | 0.93 | 0.0 | 0.0 | 0.0372 | 0.86 | 0.0996 | 0.4818 | 0.2811 | 0.9462 | 0.0924 | 0.7161 | 0.0173 | 0.975 | 0.6062 | 0.9471 | 0.2577 | 0.5333 | -1.0 | -1.0 |
| 8.4909 | 10.0 | 1170 | 13.9987 | 0.185 | 0.2141 | 0.206 | 0.0727 | 0.2826 | 0.1566 | 0.7158 | 0.8337 | 0.8425 | 0.225 | 0.7327 | 0.8234 | 0.5739 | 1.0 | 0.151 | 0.9462 | 0.0515 | 0.9625 | 0.0614 | 1.0 | 0.1336 | 0.94 | 0.0672 | 0.9222 | -1.0 | -1.0 | 0.5422 | 0.8667 | 0.2297 | 0.9778 | 0.0649 | 0.975 | 0.01 | 0.9667 | 0.1775 | 0.92 | 0.0 | 0.0 | 0.0396 | 0.94 | 0.0853 | 0.4636 | 0.3227 | 0.9538 | 0.0872 | 0.7065 | 0.0204 | 0.975 | 0.6498 | 0.9588 | 0.2469 | 0.5333 | -1.0 | -1.0 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.12.1+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2
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Model tree for merve/rfdetr-road-signs-agree2
Base model
Roboflow/rf-detr-medium