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URL: https://huggingface.co/merve/rfdetr-roadsign-agree1

⇱ merve/rfdetr-roadsign-agree1 · Hugging Face

rfdetr-roadsign-agree1

This model is a fine-tuned version of merve/rfdetr-roadsign-agree1 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 14.1117
  • Map: 0.5959
  • Map 50: 0.6882
  • Map 75: 0.6482
  • Map Small: 0.1579
  • Map Medium: 0.3972
  • Map Large: 0.6024
  • Mar 1: 0.7847
  • Mar 10: 0.8778
  • Mar 100: 0.8874
  • Mar Small: 0.275
  • Mar Medium: 0.7115
  • Mar Large: 0.8983
  • Map Bus Stop: 0.9337
  • Mar 100 Bus Stop: 0.95
  • Map Do Not Enter: 0.8604
  • Mar 100 Do Not Enter: 0.9
  • Map Do Not Stop: 0.1781
  • Mar 100 Do Not Stop: 0.9429
  • Map Do Not Turn L: 0.2737
  • Mar 100 Do Not Turn L: 0.8889
  • Map Do Not Turn R: 0.7614
  • Mar 100 Do Not Turn R: 0.9667
  • Map Do Not U Turn: 0.5779
  • Mar 100 Do Not U Turn: 0.9273
  • Map Enter Left Lane: 0.7363
  • Mar 100 Enter Left Lane: 0.9667
  • Map Green Light: 0.6934
  • Mar 100 Green Light: 0.8
  • Map Left Right Lane: 0.6518
  • Mar 100 Left Right Lane: 0.9833
  • Map No Parking: 0.3872
  • Mar 100 No Parking: 0.9556
  • Map Parking: 0.5651
  • Mar 100 Parking: 0.8875
  • Map Ped Crossing: 0.8565
  • Mar 100 Ped Crossing: 0.9353
  • Map Ped Zebra Cross: -1.0
  • Mar 100 Ped Zebra Cross: -1.0
  • Map Railway Crossing: 0.5375
  • Mar 100 Railway Crossing: 0.95
  • Map Red Light: 0.2355
  • Mar 100 Red Light: 0.5789
  • Map Stop: 0.9092
  • Mar 100 Stop: 0.9615
  • Map T Intersection L: 0.6185
  • Mar 100 T Intersection L: 0.9333
  • Map Traffic Light: 0.3229
  • Mar 100 Traffic Light: 0.6875
  • Map U Turn: 0.8555
  • Mar 100 U Turn: 0.925
  • Map Warning: 0.7491
  • Mar 100 Warning: 0.8739
  • Map Yellow Light: 0.2148
  • Mar 100 Yellow Light: 0.7333

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: 1e-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
7.1263 1.0 135 14.2796 0.5219 0.6064 0.5668 0.1319 0.3799 0.5262 0.7712 0.8669 0.8811 0.275 0.5021 0.9025 0.9135 0.9333 0.8678 0.92 0.1951 0.7429 0.1862 0.9111 0.5399 0.95 0.3958 0.9273 0.5769 0.95 0.6585 0.8176 0.7105 0.975 0.4354 0.9222 0.5259 0.85 0.7624 0.9235 -1.0 -1.0 0.3379 0.94 0.2276 0.6105 0.855 0.9538 0.3366 0.9333 0.2778 0.775 0.811 0.95 0.5744 0.8696 0.2502 0.7667
7.0985 2.0 270 14.0585 0.519 0.6098 0.5633 0.1706 0.3898 0.5212 0.7687 0.8639 0.8778 0.3 0.5135 0.8951 0.8687 0.9167 0.8826 0.9133 0.1674 0.8429 0.185 0.9 0.6606 0.9667 0.3293 0.9091 0.4655 0.95 0.6863 0.7941 0.6468 0.9833 0.3678 0.9556 0.475 0.875 0.8113 0.9412 -1.0 -1.0 0.3282 0.95 0.2056 0.6053 0.8779 0.9462 0.3762 0.9 0.2965 0.75 0.8258 0.925 0.6316 0.8652 0.291 0.6667
7.1367 3.0 405 13.7739 0.5529 0.6398 0.6013 0.188 0.3986 0.5584 0.7759 0.8885 0.898 0.3 0.7469 0.9116 0.8966 0.9167 0.8647 0.9067 0.1779 0.9571 0.3493 0.9222 0.5427 0.975 0.5786 0.9273 0.7091 1.0 0.6781 0.7941 0.5452 0.9833 0.3847 0.9667 0.4656 0.875 0.7886 0.9471 -1.0 -1.0 0.3688 0.95 0.2428 0.6474 0.8904 0.9462 0.4676 0.9333 0.3578 0.6875 0.8304 1.0 0.6667 0.8913 0.2528 0.7333
7.0008 4.0 540 13.9335 0.5647 0.6489 0.6179 0.0711 0.3881 0.57 0.7869 0.8718 0.885 0.225 0.6469 0.9018 0.8916 0.9167 0.8761 0.9067 0.1597 0.8571 0.2533 0.9 0.6444 0.9583 0.4088 0.9364 0.6317 0.95 0.6334 0.8059 0.6543 0.9667 0.4699 0.9556 0.5149 0.875 0.7512 0.9529 -1.0 -1.0 0.5247 0.96 0.2484 0.5895 0.8907 0.9308 0.5683 0.9333 0.3522 0.775 0.9 0.925 0.7052 0.9043 0.2151 0.7
6.8060 5.0 675 14.0214 0.5497 0.6341 0.5963 0.1656 0.369 0.5582 0.7805 0.8712 0.8896 0.3 0.6729 0.9043 0.9252 0.95 0.8459 0.9133 0.1701 0.8 0.3239 0.9 0.5946 0.9583 0.3397 0.9 0.6518 0.9667 0.6702 0.8118 0.6674 0.9667 0.398 0.9556 0.5133 0.8875 0.8392 0.9412 -1.0 -1.0 0.432 0.95 0.275 0.6421 0.9332 0.9538 0.3413 0.9333 0.2288 0.7625 0.8555 0.95 0.7276 0.8826 0.2605 0.7667
6.6288 6.0 810 13.9245 0.5743 0.6603 0.6297 0.1315 0.4167 0.5769 0.7769 0.8703 0.8803 0.225 0.5115 0.8992 0.9303 0.95 0.8729 0.9067 0.1912 0.8286 0.2602 0.8667 0.7311 0.9583 0.5245 0.9091 0.6474 0.95 0.6631 0.8 0.6294 0.975 0.4061 0.9556 0.5272 0.8625 0.8696 0.9412 -1.0 -1.0 0.4255 0.93 0.2636 0.5895 0.9041 0.9385 0.5445 0.9333 0.2585 0.725 0.9002 0.975 0.722 0.8783 0.2152 0.7333
6.5468 7.0 945 14.0766 0.5777 0.6643 0.6284 0.1262 0.3692 0.5868 0.7806 0.8728 0.8854 0.25 0.6687 0.8992 0.9252 0.95 0.8756 0.9267 0.1682 0.9286 0.2721 0.8889 0.7242 0.9417 0.4321 0.9091 0.7477 0.9667 0.668 0.8059 0.6723 0.975 0.4022 0.9778 0.55 0.9125 0.8823 0.9471 -1.0 -1.0 0.3901 0.94 0.2485 0.5421 0.8873 0.9308 0.5632 0.9333 0.2599 0.75 0.9 0.9 0.7691 0.8826 0.2157 0.7
6.6567 8.0 1080 14.0353 0.5987 0.6867 0.6513 0.1556 0.3961 0.6035 0.7793 0.8781 0.8902 0.3 0.7365 0.9014 0.9338 0.9667 0.8679 0.9133 0.1841 0.9714 0.2545 0.8778 0.7593 0.9667 0.6702 0.9455 0.7099 0.95 0.668 0.8118 0.7205 0.975 0.3969 0.9444 0.5367 0.9 0.8504 0.9353 -1.0 -1.0 0.5086 0.94 0.234 0.5947 0.9414 0.9615 0.6096 0.9333 0.3307 0.7 0.8258 0.975 0.7555 0.8739 0.2155 0.6667
6.4302 9.0 1215 14.0288 0.5966 0.683 0.6482 0.1579 0.3948 0.6031 0.7856 0.8772 0.8896 0.275 0.7052 0.9005 0.9365 0.95 0.8601 0.9133 0.1758 0.9286 0.2565 0.8889 0.7642 0.9667 0.6331 0.9545 0.7303 0.9833 0.68 0.8 0.694 0.975 0.389 0.9556 0.5644 0.8875 0.8644 0.9412 -1.0 -1.0 0.502 0.94 0.2334 0.5632 0.8965 0.9538 0.6077 0.9333 0.3126 0.75 0.8554 0.9 0.7619 0.8739 0.2144 0.7333
6.5195 10.0 1350 14.1117 0.5959 0.6882 0.6482 0.1579 0.3972 0.6024 0.7847 0.8778 0.8874 0.275 0.7115 0.8983 0.9337 0.95 0.8604 0.9 0.1781 0.9429 0.2737 0.8889 0.7614 0.9667 0.5779 0.9273 0.7363 0.9667 0.6934 0.8 0.6518 0.9833 0.3872 0.9556 0.5651 0.8875 0.8565 0.9353 -1.0 -1.0 0.5375 0.95 0.2355 0.5789 0.9092 0.9615 0.6185 0.9333 0.3229 0.6875 0.8555 0.925 0.7491 0.8739 0.2148 0.7333

Framework versions

  • Transformers 5.12.1
  • Pytorch 2.12.0+cu130
  • Datasets 5.0.0
  • Tokenizers 0.22.2
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