Instructions to use merve/rfdetr-roadsign-agree1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use merve/rfdetr-roadsign-agree1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="merve/rfdetr-roadsign-agree1")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("merve/rfdetr-roadsign-agree1") model = AutoModelForObjectDetection.from_pretrained("merve/rfdetr-roadsign-agree1") - Notebooks
- Google Colab
- Kaggle
rfdetr-roadsign-agree1
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: 10.9431
- Map: 0.2977
- Map 50: 0.3348
- Map 75: 0.3316
- Map Small: -1.0
- Map Medium: 0.2581
- Map Large: 0.312
- Mar 1: 0.8002
- Mar 10: 0.914
- Mar 100: 0.9207
- Mar Small: -1.0
- Mar Medium: 0.7952
- Mar Large: 0.9256
- Map Bus Stop: 0.0168
- Mar 100 Bus Stop: 0.8
- Map Do Not Enter: 0.7351
- Mar 100 Do Not Enter: 0.9647
- Map Do Not Stop: 0.2201
- Mar 100 Do Not Stop: 0.9556
- Map Do Not Turn L: 0.6354
- Mar 100 Do Not Turn L: 0.95
- Map Do Not Turn R: 0.2183
- Mar 100 Do Not Turn R: 0.9625
- Map Do Not U Turn: 0.1473
- Mar 100 Do Not U Turn: 0.9556
- Map Enter Left Lane: 0.0736
- Mar 100 Enter Left Lane: 0.96
- Map Green Light: 0.6003
- Mar 100 Green Light: 0.85
- Map Left Right Lane: 0.6462
- Mar 100 Left Right Lane: 0.9462
- Map No Parking: 0.5851
- Mar 100 No Parking: 0.9357
- Map Parking: 0.4673
- Mar 100 Parking: 0.92
- Map Ped Crossing: 0.2841
- Mar 100 Ped Crossing: 0.9786
- Map Ped Zebra Cross: 0.1496
- Mar 100 Ped Zebra Cross: 1.0
- Map Railway Crossing: 0.1275
- Mar 100 Railway Crossing: 1.0
- Map Red Light: 0.264
- Mar 100 Red Light: 0.8421
- Map Stop: 0.1531
- Mar 100 Stop: 0.96
- Map T Intersection L: 0.1283
- Mar 100 T Intersection L: 0.9556
- Map Traffic Light: 0.0914
- Mar 100 Traffic Light: 0.7714
- Map U Turn: 0.3491
- Mar 100 U Turn: 0.8857
- Map Warning: 0.2874
- Mar 100 Warning: 0.9118
- Map Yellow Light: 0.0724
- Mar 100 Yellow Light: 0.8286
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 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 22.2876 | 1.0 | 142 | 16.3031 | 0.0001 | 0.0003 | 0.0 | -1.0 | 0.0003 | 0.0001 | 0.0014 | 0.0147 | 0.0393 | -1.0 | 0.0143 | 0.0389 | 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 | 0.0071 | 0.0 | 0.0 | 0.0012 | 0.4357 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0579 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0006 | 0.3235 | 0.0 | 0.0 |
| 10.6298 | 2.0 | 284 | 12.8967 | 0.0036 | 0.0072 | 0.0027 | -1.0 | 0.0005 | 0.0037 | 0.1123 | 0.1862 | 0.2092 | -1.0 | 0.0119 | 0.2121 | 0.0 | 0.0 | 0.0005 | 0.0824 | 0.0032 | 0.4 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0067 | 0.6111 | 0.0261 | 0.56 | 0.0005 | 0.04 | 0.0096 | 0.5923 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0144 | 0.7571 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0684 | 0.01 | 0.5133 | 0.0 | 0.0 | 0.0033 | 0.1214 | 0.0 | 0.0 | 0.0015 | 0.6471 | 0.0 | 0.0 |
| 9.1796 | 3.0 | 426 | 10.0319 | 0.021 | 0.0271 | 0.0244 | -1.0 | 0.0084 | 0.0215 | 0.2869 | 0.3829 | 0.4119 | -1.0 | 0.1671 | 0.4206 | 0.0 | 0.0 | 0.011 | 0.7647 | 0.19 | 0.8778 | 0.0067 | 0.1667 | 0.0009 | 0.125 | 0.022 | 0.7111 | 0.0123 | 0.78 | 0.0242 | 0.575 | 0.0485 | 0.9462 | 0.0021 | 0.0714 | 0.0 | 0.0 | 0.0103 | 0.8714 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0039 | 0.4105 | 0.054 | 0.7 | 0.0026 | 0.1 | 0.0209 | 0.7071 | 0.0 | 0.0 | 0.0291 | 0.8 | 0.0017 | 0.0429 |
| 8.1664 | 4.0 | 568 | 10.4812 | 0.0656 | 0.0865 | 0.0802 | -1.0 | 0.1081 | 0.071 | 0.5479 | 0.6705 | 0.6938 | -1.0 | 0.4738 | 0.7013 | 0.0 | 0.0 | 0.0949 | 0.8882 | 0.0636 | 0.9222 | 0.0726 | 0.95 | 0.013 | 0.9375 | 0.0375 | 0.8222 | 0.0077 | 0.86 | 0.2439 | 0.725 | 0.248 | 0.9769 | 0.0458 | 0.8857 | 0.0856 | 0.46 | 0.0296 | 0.9 | 0.0379 | 0.6 | 0.0329 | 0.8571 | 0.03 | 0.6105 | 0.037 | 0.6933 | 0.0114 | 0.7 | 0.0507 | 0.6357 | 0.104 | 0.1 | 0.1279 | 0.8588 | 0.0029 | 0.1857 |
| 7.6975 | 5.0 | 710 | 10.0715 | 0.1155 | 0.134 | 0.1298 | -1.0 | 0.1498 | 0.1175 | 0.6555 | 0.7709 | 0.7932 | -1.0 | 0.6648 | 0.7822 | 0.0069 | 0.15 | 0.1771 | 0.9176 | 0.0417 | 0.9333 | 0.5852 | 0.95 | 0.0468 | 0.9625 | 0.0499 | 0.8333 | 0.0281 | 0.9 | 0.2321 | 0.765 | 0.2894 | 0.9846 | 0.1371 | 0.8786 | 0.0747 | 0.74 | 0.0535 | 0.9 | 0.1351 | 0.94 | 0.0409 | 0.9429 | 0.0632 | 0.7895 | 0.0452 | 0.9 | 0.0384 | 0.9 | 0.0573 | 0.6714 | 0.0051 | 0.2286 | 0.1829 | 0.9118 | 0.1361 | 0.4571 |
| 7.3315 | 6.0 | 852 | 10.2709 | 0.2027 | 0.2351 | 0.2261 | -1.0 | 0.1476 | 0.2131 | 0.7523 | 0.8761 | 0.8919 | -1.0 | 0.7338 | 0.8934 | 0.0072 | 0.7667 | 0.4716 | 0.9588 | 0.2372 | 0.9444 | 0.5703 | 0.95 | 0.065 | 0.9875 | 0.1324 | 0.9333 | 0.2099 | 0.9 | 0.3541 | 0.705 | 0.3525 | 0.9538 | 0.2255 | 0.9643 | 0.4336 | 0.86 | 0.1226 | 0.9857 | 0.1742 | 1.0 | 0.0449 | 1.0 | 0.0991 | 0.7895 | 0.1388 | 0.94 | 0.0922 | 0.9333 | 0.1329 | 0.7286 | 0.049 | 0.8286 | 0.3198 | 0.9 | 0.0232 | 0.7 |
| 7.0127 | 7.0 | 994 | 10.6621 | 0.2583 | 0.297 | 0.292 | -1.0 | 0.2075 | 0.2737 | 0.7821 | 0.8987 | 0.9113 | -1.0 | 0.7214 | 0.916 | 0.0088 | 0.8 | 0.5416 | 0.9647 | 0.2519 | 0.9444 | 0.3862 | 0.95 | 0.1977 | 0.9625 | 0.183 | 0.9333 | 0.0794 | 0.96 | 0.4767 | 0.805 | 0.4321 | 0.9615 | 0.4624 | 0.9643 | 0.42 | 0.9 | 0.2141 | 0.9786 | 0.4402 | 0.96 | 0.1659 | 1.0 | 0.1552 | 0.8211 | 0.0993 | 0.9533 | 0.1092 | 0.9556 | 0.0837 | 0.7786 | 0.353 | 0.8571 | 0.2944 | 0.8882 | 0.0701 | 0.8 |
| 7.1040 | 8.0 | 1136 | 10.9497 | 0.2791 | 0.3239 | 0.3177 | -1.0 | 0.2893 | 0.2894 | 0.7796 | 0.9057 | 0.911 | -1.0 | 0.8038 | 0.9138 | 0.0104 | 0.8167 | 0.7457 | 0.9647 | 0.2607 | 0.9556 | 0.6601 | 0.95 | 0.1946 | 0.9625 | 0.1462 | 0.9333 | 0.0503 | 0.92 | 0.5829 | 0.82 | 0.6416 | 0.9385 | 0.4414 | 0.9571 | 0.2341 | 0.84 | 0.2178 | 0.9857 | 0.2576 | 0.98 | 0.1035 | 0.9857 | 0.2389 | 0.8474 | 0.0761 | 0.9667 | 0.0919 | 0.9556 | 0.0841 | 0.7286 | 0.4107 | 0.8714 | 0.3392 | 0.9235 | 0.0737 | 0.8286 |
| 6.7829 | 9.0 | 1278 | 10.9346 | 0.3122 | 0.3543 | 0.3489 | -1.0 | 0.2803 | 0.3296 | 0.7948 | 0.9115 | 0.9192 | -1.0 | 0.8043 | 0.924 | 0.0184 | 0.8 | 0.6986 | 0.9647 | 0.229 | 0.9667 | 0.7064 | 0.95 | 0.2178 | 0.975 | 0.123 | 0.9556 | 0.2597 | 0.94 | 0.6141 | 0.835 | 0.6359 | 0.9462 | 0.568 | 0.9571 | 0.4532 | 0.9 | 0.2597 | 0.9857 | 0.3434 | 0.98 | 0.1308 | 0.9714 | 0.263 | 0.8684 | 0.0932 | 0.9533 | 0.1229 | 0.9556 | 0.1165 | 0.7357 | 0.3089 | 0.9 | 0.3132 | 0.9059 | 0.0813 | 0.8571 |
| 6.9093 | 10.0 | 1420 | 10.9431 | 0.2977 | 0.3348 | 0.3316 | -1.0 | 0.2581 | 0.312 | 0.8002 | 0.914 | 0.9207 | -1.0 | 0.7952 | 0.9256 | 0.0168 | 0.8 | 0.7351 | 0.9647 | 0.2201 | 0.9556 | 0.6354 | 0.95 | 0.2183 | 0.9625 | 0.1473 | 0.9556 | 0.0736 | 0.96 | 0.6003 | 0.85 | 0.6462 | 0.9462 | 0.5851 | 0.9357 | 0.4673 | 0.92 | 0.2841 | 0.9786 | 0.1496 | 1.0 | 0.1275 | 1.0 | 0.264 | 0.8421 | 0.1531 | 0.96 | 0.1283 | 0.9556 | 0.0914 | 0.7714 | 0.3491 | 0.8857 | 0.2874 | 0.9118 | 0.0724 | 0.8286 |
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-agree1
Base model
Roboflow/rf-detr-base