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segformer-finetuned-rwymarkings-3k-steps

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metadata
license: other
base_model: nvidia/mit-b0
tags:
  - image-segmentation
  - vision
  - generated_from_trainer
model-index:
  - name: segformer-finetuned-rwymarkings-3k-steps
    results: []

segformer-finetuned-rwymarkings-3k-steps

This model is a fine-tuned version of nvidia/mit-b0 on the Spatiallysaying/rwymarkings dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0182
  • Mean Iou: 0.0441
  • Mean Accuracy: 0.0510
  • Overall Accuracy: 0.0800
  • Accuracy Backgound : nan
  • Accuracy Tdz: 0.0908
  • Accuracy Aim: 0.2203
  • Accuracy Desig: 0.0
  • Accuracy Rwythr: 0.0971
  • Accuracy Thrbar: 0.0
  • Accuracy Disp: 0.0
  • Accuracy Chevron: 0.0
  • Accuracy Arrow: 0.0
  • Iou Backgound : 0.0
  • Iou Tdz: 0.0818
  • Iou Aim: 0.2189
  • Iou Desig: 0.0
  • Iou Rwythr: 0.0958
  • Iou Thrbar: 0.0
  • Iou Disp: 0.0
  • Iou Chevron: 0.0
  • Iou Arrow: 0.0

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: 6e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 1337
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: polynomial
  • training_steps: 3000

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Accuracy Backgound Accuracy Tdz Accuracy Aim Accuracy Desig Accuracy Rwythr Accuracy Thrbar Accuracy Disp Accuracy Chevron Accuracy Arrow Iou Backgound Iou Tdz Iou Aim Iou Desig Iou Rwythr Iou Thrbar Iou Disp Iou Chevron Iou Arrow
1.6294 1.0 173 0.5448 0.0 0.0 0.0 nan 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
0.3371 2.0 346 0.1107 0.0 0.0 0.0 nan 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
0.0724 3.0 519 0.0483 0.0 0.0 0.0 nan 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
0.0508 4.0 692 0.0331 0.0 0.0 0.0 nan 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
0.0369 5.0 865 0.0289 0.0002 0.0002 0.0004 nan 0.0 0.0019 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0019 0.0 0.0 0.0 0.0 0.0 0.0
0.0272 6.0 1038 0.0276 0.0106 0.0120 0.0195 nan 0.0107 0.0853 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0105 0.0845 0.0 0.0 0.0 0.0 0.0 0.0
0.0258 7.0 1211 0.0233 0.0066 0.0075 0.0122 nan 0.0118 0.0480 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0117 0.0480 0.0 0.0 0.0 0.0 0.0 0.0
0.0235 8.0 1384 0.0221 0.0150 0.0171 0.0277 nan 0.0233 0.1108 0.0 0.0024 0.0 0.0 0.0 0.0 0.0 0.0224 0.1107 0.0 0.0024 0.0 0.0 0.0 0.0
0.0213 9.0 1557 0.0209 0.0177 0.0200 0.0326 nan 0.0237 0.1351 0.0 0.0016 0.0 0.0 0.0 0.0 0.0 0.0231 0.1346 0.0 0.0016 0.0 0.0 0.0 0.0
0.0201 10.0 1730 0.0206 0.0277 0.0318 0.0512 nan 0.0595 0.1734 0.0 0.0211 0.0 0.0 0.0 0.0 0.0 0.0559 0.1726 0.0 0.0211 0.0 0.0 0.0 0.0
0.0203 11.0 1903 0.0198 0.0246 0.0281 0.0450 nan 0.0463 0.1512 0.0 0.0277 0.0 0.0 0.0 0.0 0.0 0.0432 0.1505 0.0 0.0277 0.0 0.0 0.0 0.0
0.0172 12.0 2076 0.0192 0.0377 0.0435 0.0690 nan 0.0744 0.2145 0.0 0.0592 0.0 0.0 0.0 0.0 0.0 0.0680 0.2119 0.0 0.0589 0.0 0.0 0.0 0.0
0.0168 13.0 2249 0.0189 0.0331 0.0381 0.0607 nan 0.0704 0.1884 0.0 0.0462 0.0 0.0 0.0 0.0 0.0 0.0645 0.1876 0.0 0.0461 0.0 0.0 0.0 0.0
0.0169 14.0 2422 0.0185 0.0383 0.0442 0.0701 nan 0.0786 0.2124 0.0 0.0628 0.0 0.0 0.0 0.0 0.0 0.0716 0.2112 0.0 0.0623 0.0 0.0 0.0 0.0
0.0172 15.0 2595 0.0184 0.0476 0.0551 0.0864 nan 0.0917 0.2463 0.0 0.1028 0.0 0.0 0.0 0.0 0.0 0.0830 0.2443 0.0 0.1013 0.0 0.0 0.0 0.0
0.0159 16.0 2768 0.0182 0.0523 0.0615 0.0964 nan 0.1202 0.2493 0.0 0.1225 0.0 0.0 0.0 0.0 0.0 0.1044 0.2468 0.0 0.1199 0.0 0.0 0.0 0.0
0.0163 17.0 2941 0.0181 0.0492 0.0571 0.0892 nan 0.0987 0.2414 0.0 0.1167 0.0 0.0 0.0 0.0 0.0 0.0885 0.2397 0.0 0.1146 0.0 0.0 0.0 0.0
0.0152 17.3410 3000 0.0182 0.0441 0.0510 0.0800 nan 0.0908 0.2203 0.0 0.0971 0.0 0.0 0.0 0.0 0.0 0.0818 0.2189 0.0 0.0958 0.0 0.0 0.0 0.0

Framework versions

  • Transformers 4.43.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1