Instructions to use merve/rfdetr-roadsign-agree2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use merve/rfdetr-roadsign-agree2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="merve/rfdetr-roadsign-agree2")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("merve/rfdetr-roadsign-agree2") model = AutoModelForObjectDetection.from_pretrained("merve/rfdetr-roadsign-agree2") - Notebooks
- Google Colab
- Kaggle
rfdetr-roadsign-agree2
This model is a fine-tuned version of Roboflow/rf-detr-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 11.2676
- Map: 0.2815
- Map 50: 0.3324
- Map 75: 0.2924
- Map Small: 0.7112
- Map Medium: 0.3387
- Map Large: 0.2795
- Mar 1: 0.761
- Mar 10: 0.8776
- Mar 100: 0.8871
- Mar Small: 0.7333
- Mar Medium: 0.56
- Mar Large: 0.8946
- Map Bus Stop: -1.0
- Mar 100 Bus Stop: -1.0
- Map Do Not Enter: 0.4958
- Mar 100 Do Not Enter: 0.9083
- Map Do Not Stop: 0.2217
- Mar 100 Do Not Stop: 0.9267
- Map Do Not Turn L: 0.1535
- Mar 100 Do Not Turn L: 0.875
- Map Do Not Turn R: 0.3799
- Mar 100 Do Not Turn R: 1.0
- Map Do Not U Turn: 0.2976
- Mar 100 Do Not U Turn: 0.9375
- Map Enter Left Lane: 0.4876
- Mar 100 Enter Left Lane: 0.96
- Map Green Light: 0.3737
- Mar 100 Green Light: 0.7818
- Map Left Right Lane: 0.5669
- Mar 100 Left Right Lane: 0.9875
- Map No Parking: 0.2065
- Mar 100 No Parking: 0.9333
- Map Parking: 0.3454
- Mar 100 Parking: 0.8333
- Map Ped Crossing: 0.3321
- Mar 100 Ped Crossing: 0.9333
- Map Ped Zebra Cross: 0.1713
- Mar 100 Ped Zebra Cross: 0.9556
- Map Railway Crossing: 0.2636
- Mar 100 Railway Crossing: 0.96
- Map Red Light: 0.1826
- Mar 100 Red Light: 0.6917
- Map Stop: 0.2961
- Mar 100 Stop: 0.9444
- Map T Intersection L: 0.0455
- Mar 100 T Intersection L: 0.975
- Map Traffic Light: 0.0292
- Mar 100 Traffic Light: 0.5214
- Map U Turn: 0.1684
- Mar 100 U Turn: 0.8833
- Map Warning: 0.2717
- Mar 100 Warning: 0.9846
- Map Yellow Light: 0.3402
- Mar 100 Yellow Light: 0.75
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 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 Enter Left Lane | Mar 100 Enter Left Lane | 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 T Intersection L | Mar 100 T Intersection L | 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 Bus Stop | Mar 100 Bus Stop |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 24.1352 | 1.0 | 133 | 16.5739 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0004 | 0.0075 | 0.0419 | 0.0 | 0.0 | 0.0446 | 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 | 0.0004 | 0.3444 | 0.0 | 0.0 | 0.0001 | 0.0333 | 0.0 | 0.0 | 0.0003 | 0.3889 | 0.0 | 0.0 | 0.0 | 0.0714 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -1.0 | -1.0 |
| 11.3730 | 2.0 | 266 | 13.0612 | 0.003 | 0.0096 | 0.0013 | 0.0 | 0.0007 | 0.003 | 0.0628 | 0.1418 | 0.1668 | 0.0 | 0.0261 | 0.1718 | -1.0 | -1.0 | 0.0071 | 0.0333 | 0.0 | 0.0 | 0.0064 | 0.15 | 0.0003 | 0.6 | 0.0148 | 0.5375 | 0.0046 | 0.0867 | 0.0003 | 0.0182 | 0.0 | 0.0 | 0.0006 | 0.0267 | 0.0 | 0.0 | 0.0067 | 0.6889 | 0.0 | 0.0 | 0.0025 | 0.2733 | 0.0004 | 0.0583 | 0.001 | 0.0222 | 0.0 | 0.0 | 0.0009 | 0.1571 | 0.0 | 0.0 | 0.0136 | 0.6846 | 0.0 | 0.0 |
| 8.8875 | 3.0 | 399 | 10.9539 | 0.0303 | 0.043 | 0.0309 | 0.0 | 0.0351 | 0.0399 | 0.2939 | 0.4263 | 0.4514 | 0.0 | 0.3194 | 0.4565 | -1.0 | -1.0 | 0.0146 | 0.275 | 0.0013 | 0.04 | 0.0129 | 0.875 | 0.0167 | 0.9 | 0.0623 | 0.8188 | 0.0108 | 0.8067 | 0.014 | 0.5591 | 0.0217 | 0.925 | 0.0152 | 0.72 | 0.0 | 0.0 | 0.1779 | 0.8389 | 0.0 | 0.0 | 0.0758 | 0.4667 | 0.0028 | 0.3667 | 0.0015 | 0.1667 | 0.0 | 0.0 | 0.0751 | 0.2 | 0.0 | 0.0 | 0.0522 | 0.8692 | 0.0505 | 0.2 |
| 8.0101 | 4.0 | 532 | 10.3960 | 0.0556 | 0.0749 | 0.0614 | 0.2322 | 0.0872 | 0.0564 | 0.5017 | 0.6379 | 0.6541 | 0.2667 | 0.3933 | 0.6667 | -1.0 | -1.0 | 0.0574 | 0.8583 | 0.1067 | 0.8733 | 0.0091 | 0.75 | 0.0105 | 0.9 | 0.0687 | 0.9187 | 0.1162 | 0.9067 | 0.1253 | 0.6409 | 0.0825 | 0.9875 | 0.0338 | 0.9 | 0.0109 | 0.2667 | 0.1453 | 0.9 | 0.0027 | 0.1 | 0.0589 | 0.6933 | 0.0208 | 0.475 | 0.1237 | 0.9111 | 0.0 | 0.0 | 0.0047 | 0.3 | 0.0021 | 0.35 | 0.1065 | 0.9 | 0.0267 | 0.45 |
| 7.6896 | 5.0 | 665 | 9.7700 | 0.1189 | 0.1398 | 0.1249 | 0.2738 | 0.2094 | 0.1176 | 0.7129 | 0.8363 | 0.8521 | 0.4667 | 0.5744 | 0.8531 | -1.0 | -1.0 | 0.0373 | 0.8833 | 0.0837 | 0.9333 | 0.0784 | 0.9 | 0.0696 | 0.9 | 0.2365 | 0.9438 | 0.1113 | 0.9533 | 0.2727 | 0.7545 | 0.3578 | 1.0 | 0.1671 | 0.88 | 0.0801 | 0.9 | 0.1694 | 0.9611 | 0.0164 | 0.9444 | 0.0878 | 0.8867 | 0.0426 | 0.5833 | 0.0788 | 0.9333 | 0.0208 | 0.7 | 0.032 | 0.3714 | 0.0165 | 0.8667 | 0.3041 | 0.9462 | 0.1146 | 0.8 |
| 7.2895 | 6.0 | 798 | 10.1798 | 0.1817 | 0.2111 | 0.2012 | 0.4419 | 0.2374 | 0.174 | 0.7467 | 0.876 | 0.8856 | 0.7 | 0.5694 | 0.8919 | -1.0 | -1.0 | 0.281 | 0.9 | 0.117 | 0.88 | 0.0341 | 0.925 | 0.0457 | 1.0 | 0.2552 | 0.9563 | 0.3588 | 0.9467 | 0.3751 | 0.7727 | 0.4468 | 1.0 | 0.1211 | 0.9533 | 0.3992 | 0.9 | 0.3758 | 0.9333 | 0.0244 | 0.9333 | 0.1971 | 0.8933 | 0.087 | 0.65 | 0.1371 | 0.9556 | 0.0342 | 0.95 | 0.0103 | 0.4929 | 0.0487 | 0.9 | 0.2468 | 0.9692 | 0.0385 | 0.8 |
| 7.1047 | 7.0 | 931 | 10.5961 | 0.2343 | 0.2785 | 0.2469 | 0.5509 | 0.3183 | 0.224 | 0.7346 | 0.8715 | 0.8775 | 0.6667 | 0.5267 | 0.8884 | -1.0 | -1.0 | 0.3472 | 0.9 | 0.2627 | 0.9133 | 0.0537 | 0.9 | 0.1563 | 0.95 | 0.203 | 0.925 | 0.3604 | 0.96 | 0.3856 | 0.8091 | 0.6891 | 0.9875 | 0.2315 | 0.94 | 0.404 | 0.9333 | 0.3475 | 0.9056 | 0.0602 | 0.9222 | 0.2107 | 0.96 | 0.0876 | 0.5833 | 0.2681 | 0.9556 | 0.0447 | 0.95 | 0.022 | 0.4929 | 0.0469 | 0.85 | 0.2312 | 0.9615 | 0.2744 | 0.75 |
| 6.7722 | 8.0 | 1064 | 10.8932 | 0.2772 | 0.3205 | 0.2946 | 0.7332 | 0.3556 | 0.2815 | 0.7724 | 0.8719 | 0.8835 | 0.7667 | 0.5444 | 0.8923 | -1.0 | -1.0 | 0.5526 | 0.9083 | 0.2559 | 0.9133 | 0.0974 | 0.9 | 0.604 | 1.0 | 0.3144 | 0.9563 | 0.4236 | 0.9467 | 0.3985 | 0.8045 | 0.4066 | 0.9625 | 0.2183 | 0.9267 | 0.3085 | 0.8667 | 0.3855 | 0.9278 | 0.1283 | 0.9444 | 0.3619 | 0.98 | 0.1817 | 0.75 | 0.1262 | 0.9333 | 0.1153 | 0.95 | 0.0181 | 0.5357 | 0.0779 | 0.8667 | 0.3141 | 0.9462 | 0.2555 | 0.65 |
| 6.6882 | 9.0 | 1197 | 11.2337 | 0.2837 | 0.3344 | 0.2945 | 0.6943 | 0.3481 | 0.28 | 0.7655 | 0.8737 | 0.8819 | 0.7667 | 0.545 | 0.8913 | -1.0 | -1.0 | 0.4763 | 0.925 | 0.205 | 0.9133 | 0.1515 | 0.9 | 0.5 | 1.0 | 0.3449 | 0.9375 | 0.4165 | 0.94 | 0.4026 | 0.7864 | 0.5967 | 1.0 | 0.1763 | 0.94 | 0.259 | 0.8 | 0.3273 | 0.9278 | 0.2502 | 0.9222 | 0.2404 | 0.96 | 0.175 | 0.7 | 0.2389 | 0.9333 | 0.0678 | 0.975 | 0.0455 | 0.55 | 0.1536 | 0.85 | 0.2937 | 0.9769 | 0.3521 | 0.7 |
| 6.5118 | 10.0 | 1330 | 11.2676 | 0.2815 | 0.3324 | 0.2924 | 0.7112 | 0.3387 | 0.2795 | 0.761 | 0.8776 | 0.8871 | 0.7333 | 0.56 | 0.8946 | -1.0 | -1.0 | 0.4958 | 0.9083 | 0.2217 | 0.9267 | 0.1535 | 0.875 | 0.3799 | 1.0 | 0.2976 | 0.9375 | 0.4876 | 0.96 | 0.3737 | 0.7818 | 0.5669 | 0.9875 | 0.2065 | 0.9333 | 0.3454 | 0.8333 | 0.3321 | 0.9333 | 0.1713 | 0.9556 | 0.2636 | 0.96 | 0.1826 | 0.6917 | 0.2961 | 0.9444 | 0.0455 | 0.975 | 0.0292 | 0.5214 | 0.1684 | 0.8833 | 0.2717 | 0.9846 | 0.3402 | 0.75 |
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-roadsign-agree2
Base model
Roboflow/rf-detr-base