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Rfdetr Road Signs Agree1

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: 16.2265 Map: 0.2689 Map 50: 0.3209 Map 75: 0.2914 Map Small: 0.1286...

Sourcehuggingface.co/merve/rfdetr-road-signs-agree1/tree/435ded477b1e2af1701b2101388947c7db946da4
KindOtherBase modelRoboflow/rf-detr-mediumVersionRevision 435ded4Cgrade

Model source

Kind
Other
File size
128 MB
Base model
Roboflow/rf-detr-medium
Version
vRevision 435ded4
Updated
Sep 16, 2026
Downloads
7
Source
Hugging Face

Source description

rfdetr-road-signs-agree1

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: 16.2265
  • Map: 0.2689
  • Map 50: 0.3209
  • Map 75: 0.2914
  • Map Small: 0.1286
  • Map Medium: 0.2837
  • Map Large: 0.2816
  • Mar 1: 0.8019
  • Mar 10: 0.8631
  • Mar 100: 0.8721
  • Mar Small: 0.3889
  • Mar Medium: 0.65
  • Mar Large: 0.8778
  • Map Bus Stop: 0.4038
  • Mar 100 Bus Stop: 0.925
  • Map Do Not Enter: 0.4978
  • Mar 100 Do Not Enter: 0.8467
  • Map Do Not Stop: 0.0699
  • Mar 100 Do Not Stop: 0.9556
  • Map Do Not Turn L: 0.3458
  • Mar 100 Do Not Turn L: 0.875
  • Map Do Not Turn R: 0.1562
  • Mar 100 Do Not Turn R: 0.95
  • Map Do Not U Turn: 0.3238
  • Mar 100 Do Not U Turn: 0.95
  • Map Enter Left Lane: 0.0153
  • Mar 100 Enter Left Lane: 0.9
  • Map Green Light: 0.3311
  • Mar 100 Green Light: 0.6143
  • Map Left Right Lane: 0.6104
  • Mar 100 Left Right Lane: 0.9833
  • Map No Parking: 0.2497
  • Mar 100 No Parking: 0.8842
  • Map Parking: 0.9
  • Mar 100 Parking: 0.9
  • Map Ped Crossing: 0.1528
  • Mar 100 Ped Crossing: 0.9545
  • Map Ped Zebra Cross: 0.0137
  • Mar 100 Ped Zebra Cross: 1.0
  • Map Railway Crossing: 0.0997
  • Mar 100 Railway Crossing: 0.7667
  • Map Red Light: 0.1385
  • Mar 100 Red Light: 0.6875
  • Map Stop: 0.0998
  • Mar 100 Stop: 0.9571
  • Map T Intersection L: 0.0476
  • Mar 100 T Intersection L: 1.0
  • Map Traffic Light: 0.4625
  • Mar 100 Traffic Light: 0.7049
  • Map U Turn: 0.0343
  • Mar 100 U Turn: 0.8
  • Map Warning: 0.6763
  • Mar 100 Warning: 0.86
  • Map Yellow Light: 0.0174
  • Mar 100 Yellow Light: 0.8

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 LossEpochStepValidation LossMapMap 50Map 75Map SmallMap MediumMap LargeMar 1Mar 10Mar 100Mar SmallMar MediumMar LargeMap Bus StopMar 100 Bus StopMap Do Not EnterMar 100 Do Not EnterMap Do Not StopMar 100 Do Not StopMap Do Not Turn LMar 100 Do Not Turn LMap Do Not Turn RMar 100 Do Not Turn RMap Do Not U TurnMar 100 Do Not U TurnMap Enter Left LaneMar 100 Enter Left LaneMap Green LightMar 100 Green LightMap Left Right LaneMar 100 Left Right LaneMap No ParkingMar 100 No ParkingMap ParkingMar 100 ParkingMap Ped CrossingMar 100 Ped CrossingMap Ped Zebra CrossMar 100 Ped Zebra CrossMap Railway CrossingMar 100 Railway CrossingMap Red LightMar 100 Red LightMap StopMar 100 StopMap T Intersection LMar 100 T Intersection LMap Traffic LightMar 100 Traffic LightMap U TurnMar 100 U TurnMap WarningMar 100 WarningMap Yellow LightMar 100 Yellow Light
28.08221.014323.46300.00010.00020.00010.00.00050.00010.00270.01130.01660.00.0020.0180.00.00.00.00.00.00.00.00.00050.11670.00.00.00.00.00.00.00070.03890.00.01580.00.00.00.00.00.00.00.00.00.00.00010.07140.00.00.00.04590.00.00.00010.060.00.0
13.76662.028617.03240.0020.00570.00120.00.00050.0020.03920.0760.09880.00.0050.10580.00.00.00410.26670.00.00.00.00.00.00.01290.20.00.00.00.00.00510.28890.00.00.00.00.00350.42730.00.00.00.00.00.00.00.00.00.00.00070.19340.00.00.01510.6980.00.0
10.88683.042914.34610.02870.04690.02880.08140.10760.01970.25610.34080.36120.23330.3250.34270.00.00.01790.70670.03790.62220.00110.150.00670.60830.03820.94170.00.00.19380.37140.06220.91110.02350.47370.00.00.05020.87270.00.00.00.00.01280.16250.01030.45710.00.00.02380.50820.00.00.12350.80.00.0
10.02764.057213.84260.08860.12130.0970.17070.24330.09240.56640.66460.6840.37780.5960.68870.2580.90.05590.80.03060.94440.04170.90.0280.94170.07750.94170.00.00.32250.53570.06450.96110.06150.78950.04090.90.06670.95450.00.00.00810.550.0620.6250.19930.87140.00710.90.2230.65570.00820.30.30520.8940.00.0
9.51805.071516.26130.11930.15870.13650.13290.24080.12240.65710.74680.76490.34440.6390.7720.10240.90.060.84670.03880.94440.09520.850.05990.94170.2160.9250.00930.90.3130.63570.14560.92220.1810.87370.06670.80.17540.90910.00.00.00960.58330.07940.71250.08190.91430.0061.00.29370.66390.03340.86670.53840.8740.00.0
8.86346.085815.79900.16960.22260.18050.15440.27180.18470.72740.83580.84660.44440.5820.85620.07940.9250.14040.82670.04630.93330.27340.78750.08730.950.1210.90830.00980.90.28050.49290.3370.92780.34470.86320.450.90.08740.90.01170.90.02630.71670.14870.70630.0580.92860.00961.00.38520.70160.02610.76670.61430.8440.02370.9
8.42107.0100115.30680.22270.27360.24920.16690.30580.23960.80440.87060.88120.38330.6560.88840.15910.9250.22640.87330.06430.96670.34290.86250.11440.95830.26450.95830.01041.00.37660.67860.42950.94440.18890.88420.90.90.09130.91820.00921.00.09290.73330.16270.68750.08020.92860.01891.00.42320.69840.03530.80.65660.8880.030.9
8.24288.0114416.18300.24930.29840.27290.13660.3077...

Sources

1 source
Hugging FacePrimaryVersion 435ded477b1e2af1701b2101388947c7db946da4
huggingface.co/merve/rfdetr-road-signs-agree1/tree/435ded477b1e2af1701b2101388947c7db946da4

Verified Sep 1

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Model artifacts

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final/model.safetensors

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model.safetensors

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Source excerpts

2 excerpts
ReadmeSep 1huggingface.co/merve/rfdetr-road-signs-agree1

--- library_name: transformers license: apache-2.0 base_model: Roboflow/rf-detr-medium tags: - generated_from_trainer model-index: - name: rfdetr-road-signs-agree1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # rfdetr-road-signs-agree1 This model is a fine-tuned version of [Roboflow/rf-detr-medium](https://huggingface.co/Roboflow/rf-detr-medium) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 16.2265 - Map: 0.2689 - Map 50: 0.3209 - Map 75: 0.2914 - Map Small: 0.1286 - Map Medium: 0.2837 - Map Large: 0.2816 - Mar 1: 0.8019 - Mar 10: 0.8631 - Mar 100: 0.8721 - Mar Small: 0.3889 - Mar Medium: 0.65 - Mar Large: 0.8778 - Map Bus Stop: 0.4038 - Mar 100 Bus Stop: 0.925 - Map Do Not Enter: 0.4978 - Mar 100 Do Not Enter: 0.8467 - Map Do Not Stop: 0.0699 - Mar 100 Do Not Stop: 0.9556 - Map Do Not Turn L: 0.3458 - Mar 100 Do Not Turn L: 0.875 - Map Do Not Turn R: 0.1562 - Mar 100 Do Not Turn R: 0.95 - Map Do Not U Turn: 0.3238 - Mar 100 Do Not U Turn: 0.95 - Map Enter Left Lane: 0.0153 - Mar 100 Enter Left Lane: 0.9 - Map Green Light: 0.3311 - Mar 100 Green Light: 0.6143 - Map Left Right Lane: 0.6104 - Mar 100 Left Right Lane: 0.9833 - Map No Parking: 0.2497 - Mar 100 No Parking: 0.8842 - Map Parking: 0.9 - Mar 100 Parking: 0.9 - Map Ped Crossing: 0.1528 - Mar 100 Ped Crossing: 0.9545 - Map Ped Zebra Cross: 0.0137 - Mar 100 Ped Zebra Cross: 1.0 - Map Railway Crossing: 0.0997 - Mar 100 Railway Crossing: 0.7667 - Map Red Light: 0.1385 - Mar 100 Red Light: 0.6875 - Map Stop: 0.0998 - Mar 100 Stop: 0.9571 - Map T Intersection L: 0.0476 - Mar 100 T Intersection L: 1.0 - Map Traffic Light: 0.4625 - Mar 100 Traffic Light: 0.7049 - Map U Turn: 0.0343 - Mar 100 U Turn: 0.8 - Map Warning: 0.6763 - Mar 100 Warning: 0.86 - Map Yellow Light: 0.0174 - Mar 100 Yellow Light: 0.8 ## 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=...

NoteSep 1huggingface.co/merve/rfdetr-road-signs-agree1

Source context: 7 downloads · 0 likes · Pipeline object-detection · Library transformers · Repo merve/rfdetr-road-signs-agree1