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segformer-b0-finetuned-segments-toolwear

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metadata
license: other
tags:
  - generated_from_trainer
model-index:
  - name: segformer-b0-finetuned-segments-toolwear
    results: []

segformer-b0-finetuned-segments-toolwear

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

  • Loss: 0.0360
  • Mean Iou: 0.3724
  • Mean Accuracy: 0.7448
  • Overall Accuracy: 0.7448
  • Accuracy Unlabeled: nan
  • Accuracy Tool: nan
  • Accuracy Wear: 0.7448
  • Iou Unlabeled: 0.0
  • Iou Tool: nan
  • Iou Wear: 0.7448

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: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Accuracy Unlabeled Accuracy Tool Accuracy Wear Iou Unlabeled Iou Tool Iou Wear
0.9316 1.18 20 0.9877 0.4510 0.9020 0.9020 nan nan 0.9020 0.0 nan 0.9020
0.6902 2.35 40 0.6556 0.3765 0.7531 0.7531 nan nan 0.7531 0.0 nan 0.7531
0.532 3.53 60 0.4585 0.3435 0.6871 0.6871 nan nan 0.6871 0.0 nan 0.6871
0.4296 4.71 80 0.3832 0.3900 0.7799 0.7799 nan nan 0.7799 0.0 nan 0.7799
0.3318 5.88 100 0.3255 0.3739 0.7478 0.7478 nan nan 0.7478 0.0 nan 0.7478
0.281 7.06 120 0.2480 0.3109 0.6219 0.6219 nan nan 0.6219 0.0 nan 0.6219
0.2405 8.24 140 0.2410 0.2029 0.4059 0.4059 nan nan 0.4059 0.0 nan 0.4059
0.1945 9.41 160 0.1969 0.3366 0.6733 0.6733 nan nan 0.6733 0.0 nan 0.6733
0.1612 10.59 180 0.1776 0.3469 0.6938 0.6938 nan nan 0.6938 0.0 nan 0.6938
0.1653 11.76 200 0.1455 0.3758 0.7515 0.7515 nan nan 0.7515 0.0 nan 0.7515
0.1562 12.94 220 0.1330 0.2652 0.5304 0.5304 nan nan 0.5304 0.0 nan 0.5304
0.1053 14.12 240 0.1145 0.3511 0.7022 0.7022 nan nan 0.7022 0.0 nan 0.7022
0.1017 15.29 260 0.0989 0.3879 0.7757 0.7757 nan nan 0.7757 0.0 nan 0.7757
0.0809 16.47 280 0.0859 0.2622 0.5243 0.5243 nan nan 0.5243 0.0 nan 0.5243
0.0861 17.65 300 0.0761 0.3688 0.7375 0.7375 nan nan 0.7375 0.0 nan 0.7375
0.0695 18.82 320 0.0720 0.3786 0.7572 0.7572 nan nan 0.7572 0.0 nan 0.7572
0.0689 20.0 340 0.0646 0.3964 0.7927 0.7927 nan nan 0.7927 0.0 nan 0.7927
0.0592 21.18 360 0.0657 0.3063 0.6126 0.6126 nan nan 0.6126 0.0 nan 0.6126
0.0635 22.35 380 0.0581 0.3615 0.7230 0.7230 nan nan 0.7230 0.0 nan 0.7230
0.0511 23.53 400 0.0526 0.3622 0.7245 0.7245 nan nan 0.7245 0.0 nan 0.7245
0.0518 24.71 420 0.0543 0.3270 0.6540 0.6540 nan nan 0.6540 0.0 nan 0.6540
0.0448 25.88 440 0.0522 0.4141 0.8282 0.8282 nan nan 0.8282 0.0 nan 0.8282
0.0395 27.06 460 0.0470 0.3519 0.7038 0.7038 nan nan 0.7038 0.0 nan 0.7038
0.04 28.24 480 0.0452 0.3870 0.7740 0.7740 nan nan 0.7740 0.0 nan 0.7740
0.0386 29.41 500 0.0439 0.3801 0.7603 0.7603 nan nan 0.7603 0.0 nan 0.7603
0.0421 30.59 520 0.0437 0.4047 0.8093 0.8093 nan nan 0.8093 0.0 nan 0.8093
0.0356 31.76 540 0.0427 0.3675 0.7349 0.7349 nan nan 0.7349 0.0 nan 0.7349
0.0368 32.94 560 0.0420 0.3604 0.7208 0.7208 nan nan 0.7208 0.0 nan 0.7208
0.0368 34.12 580 0.0408 0.3589 0.7179 0.7179 nan nan 0.7179 0.0 nan 0.7179
0.032 35.29 600 0.0395 0.3664 0.7329 0.7329 nan nan 0.7329 0.0 nan 0.7329
0.03 36.47 620 0.0394 0.3691 0.7382 0.7382 nan nan 0.7382 0.0 nan 0.7382
0.028 37.65 640 0.0383 0.3731 0.7462 0.7462 nan nan 0.7462 0.0 nan 0.7462
0.0304 38.82 660 0.0376 0.3796 0.7592 0.7592 nan nan 0.7592 0.0 nan 0.7592
0.0314 40.0 680 0.0382 0.3602 0.7204 0.7204 nan nan 0.7204 0.0 nan 0.7204
0.0266 41.18 700 0.0385 0.3602 0.7203 0.7203 nan nan 0.7203 0.0 nan 0.7203
0.0305 42.35 720 0.0375 0.3413 0.6827 0.6827 nan nan 0.6827 0.0 nan 0.6827
0.0334 43.53 740 0.0366 0.3632 0.7263 0.7263 nan nan 0.7263 0.0 nan 0.7263
0.0269 44.71 760 0.0359 0.3698 0.7396 0.7396 nan nan 0.7396 0.0 nan 0.7396
0.0352 45.88 780 0.0364 0.3679 0.7359 0.7359 nan nan 0.7359 0.0 nan 0.7359
0.0398 47.06 800 0.0366 0.3504 0.7008 0.7008 nan nan 0.7008 0.0 nan 0.7008
0.0261 48.24 820 0.0361 0.3789 0.7578 0.7578 nan nan 0.7578 0.0 nan 0.7578
0.0252 49.41 840 0.0360 0.3724 0.7448 0.7448 nan nan 0.7448 0.0 nan 0.7448

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.13.3