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panels_detection_rtdetr_augmented

cems-official / panels_detection_rtdetr_augmented

Run on huggingface.co
huggingface.co
Total runs: 41
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: January 28 2025
object-detection

Introduction of panels_detection_rtdetr_augmented

Model Details of panels_detection_rtdetr_augmented

panels_detection_rtdetr_augmented

This model is a fine-tuned version of PekingU/rtdetr_r50vd_coco_o365 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 11.6296
  • Map: 0.3213
  • Map 50: 0.4135
  • Map 75: 0.3518
  • Map Small: -1.0
  • Map Medium: 0.3783
  • Map Large: 0.3553
  • Mar 1: 0.4928
  • Mar 10: 0.6752
  • Mar 100: 0.7037
  • Mar Small: -1.0
  • Mar Medium: 0.6061
  • Mar Large: 0.7483
  • Map Radar (small): 0.5808
  • Mar 100 Radar (small): 0.8786
  • Map Ship management system (small): 0.5966
  • Mar 100 Ship management system (small): 0.92
  • Map Radar (large): 0.4528
  • Mar 100 Radar (large): 0.8791
  • Map Ship management system (large): 0.3872
  • Mar 100 Ship management system (large): 0.7909
  • Map Ship management system (top): 0.0691
  • Mar 100 Ship management system (top): 0.4606
  • Map Ecdis (large): 0.5355
  • Mar 100 Ecdis (large): 0.9675
  • Map Visual observation (small): 0.0737
  • Mar 100 Visual observation (small): 0.4625
  • Map Ecdis (small): 0.1395
  • Mar 100 Ecdis (small): 0.7269
  • Map Ship management system (table top): 0.4579
  • Mar 100 Ship management system (table top): 0.7886
  • Map Thruster control: 0.6539
  • Mar 100 Thruster control: 0.8051
  • Map Visual observation (left): 0.0287
  • Mar 100 Visual observation (left): 0.68
  • Map Visual observation (mid): 0.3207
  • Mar 100 Visual observation (mid): 0.8643
  • Map Visual observation (right): 0.0554
  • Mar 100 Visual observation (right): 0.3434
  • Map Bow thruster: 0.3348
  • Mar 100 Bow thruster: 0.5414
  • Map Me telegraph: 0.1335
  • Mar 100 Me telegraph: 0.4462
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: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • num_epochs: 7
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 Radar (small) Mar 100 Radar (small) Map Ship management system (small) Mar 100 Ship management system (small) Map Radar (large) Mar 100 Radar (large) Map Ship management system (large) Mar 100 Ship management system (large) Map Ship management system (top) Mar 100 Ship management system (top) Map Ecdis (large) Mar 100 Ecdis (large) Map Visual observation (small) Mar 100 Visual observation (small) Map Ecdis (small) Mar 100 Ecdis (small) Map Ship management system (table top) Mar 100 Ship management system (table top) Map Thruster control Mar 100 Thruster control Map Visual observation (left) Mar 100 Visual observation (left) Map Visual observation (mid) Mar 100 Visual observation (mid) Map Visual observation (right) Mar 100 Visual observation (right) Map Bow thruster Mar 100 Bow thruster Map Me telegraph Mar 100 Me telegraph
13.9695 1.0 397 10.0163 0.3803 0.4426 0.4211 -1.0 0.1813 0.4182 0.473 0.6233 0.6668 -1.0 0.2905 0.723 0.7986 0.9304 0.7716 0.8692 0.64 0.8977 0.755 0.9314 0.6867 0.825 0.5981 0.9114 0.0035 0.2479 0.0222 0.5462 0.0057 0.1943 0.347 0.6538 0.0713 0.8457 0.8377 0.9296 0.1466 0.7755 0.0085 0.2241 0.0113 0.2192
9.2622 2.0 794 10.2351 0.3974 0.4931 0.4332 -1.0 0.2228 0.445 0.5301 0.71 0.7368 -1.0 0.4306 0.802 0.6618 0.8518 0.7252 0.8985 0.6294 0.9101 0.5849 0.9512 0.2206 0.7462 0.7716 0.9395 0.1063 0.65 0.3025 0.7808 0.2306 0.5857 0.4876 0.6692 0.1283 0.79 0.7163 0.9243 0.1375 0.6075 0.1795 0.3897 0.0786 0.3577
8.5303 3.0 1191 10.6114 0.3654 0.461 0.4119 -1.0 0.3299 0.4011 0.5161 0.6549 0.6805 -1.0 0.5465 0.726 0.4555 0.8125 0.5593 0.8738 0.5899 0.9023 0.5174 0.9331 0.6654 0.776 0.5733 0.9474 0.0044 0.3417 0.1021 0.65 0.4821 0.7629 0.5739 0.7385 0.0344 0.6443 0.6124 0.9113 0.0047 0.183 0.2301 0.469 0.0755 0.2615
7.5942 4.0 1588 10.6910 0.3713 0.4655 0.4153 -1.0 0.3216 0.4096 0.5192 0.7053 0.7348 -1.0 0.5924 0.7774 0.477 0.9054 0.53 0.8246 0.6131 0.9163 0.682 0.9256 0.3668 0.7375 0.6206 0.9588 0.0394 0.5417 0.2502 0.8038 0.3822 0.7714 0.5989 0.7795 0.0859 0.7386 0.5168 0.8748 0.033 0.3755 0.2842 0.5 0.0901 0.3692
7.1852 5.0 1985 11.2027 0.3509 0.4465 0.3924 -1.0 0.3647 0.3834 0.5005 0.6647 0.6945 -1.0 0.5923 0.7444 0.6041 0.875 0.5835 0.92 0.525 0.9093 0.4951 0.8802 0.0482 0.4538 0.5599 0.9526 0.1357 0.6854 0.1454 0.5654 0.4369 0.78 0.5702 0.7436 0.0257 0.6986 0.6137 0.9026 0.0238 0.1472 0.3685 0.4966 0.1273 0.4077
6.7939 6.0 2382 11.7260 0.3268 0.4241 0.3584 -1.0 0.3432 0.3648 0.4913 0.6762 0.7024 -1.0 0.5875 0.7525 0.5857 0.9089 0.5419 0.9215 0.4826 0.8713 0.4597 0.8091 0.0875 0.4625 0.5416 0.9684 0.0606 0.4271 0.1499 0.8154 0.5105 0.7971 0.5793 0.7744 0.0363 0.6771 0.3423 0.8452 0.0563 0.283 0.3597 0.5172 0.1087 0.4577
6.6729 7.0 2779 11.6296 0.3213 0.4135 0.3518 -1.0 0.3783 0.3553 0.4928 0.6752 0.7037 -1.0 0.6061 0.7483 0.5808 0.8786 0.5966 0.92 0.4528 0.8791 0.3872 0.7909 0.0691 0.4606 0.5355 0.9675 0.0737 0.4625 0.1395 0.7269 0.4579 0.7886 0.6539 0.8051 0.0287 0.68 0.3207 0.8643 0.0554 0.3434 0.3348 0.5414 0.1335 0.4462
Framework versions
  • Transformers 4.46.0
  • Pytorch 2.5.0+cu121
  • Datasets 3.0.2
  • Tokenizers 0.20.1

Runs of cems-official panels_detection_rtdetr_augmented on huggingface.co

41
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3-day runs
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