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metadata
license: other
tags:
  - generated_from_keras_callback
model-index:
  - name: nateraw/mit-b0-finetuned-sidewalks-v2
    results: []

nateraw/mit-b0-finetuned-sidewalks-v2

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

  • Train Loss: 0.4495
  • Validation Loss: 0.4797
  • Validation Mean Iou: 0.3035
  • Validation Mean Accuracy: 0.3702
  • Validation Overall Accuracy: 0.8468
  • Validation Per Category Iou: [0.00000000e+00 7.52163526e-01 8.46563375e-01 7.16396797e-01 7.38850637e-01 3.93073019e-01 nan 3.31795957e-01 4.92991567e-01 0.00000000e+00 8.11302090e-01 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 5.16059849e-01 0.00000000e+00 0.00000000e+00 6.56058294e-01 1.25948501e-02 2.66942435e-01 5.34406894e-01 0.00000000e+00 nan 0.00000000e+00 2.27750085e-01 4.86381323e-04 0.00000000e+00 8.48618960e-01 7.25828093e-01 9.17747637e-01 8.28380212e-03 6.74590297e-02 1.51281596e-01 0.00000000e+00]
  • Validation Per Category Accuracy: [0.00000000e+00 8.75360044e-01 9.43650850e-01 8.78658645e-01 7.76578096e-01 4.85757596e-01 nan 4.30901582e-01 7.54126335e-01 0.00000000e+00 9.30112537e-01 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 6.42914247e-01 0.00000000e+00 0.00000000e+00 7.57605356e-01 1.27102686e-02 6.50888458e-01 6.94757080e-01 0.00000000e+00 nan 0.00000000e+00 2.91727649e-01 4.86381323e-04 0.00000000e+00 9.42251577e-01 8.60753175e-01 9.56778008e-01 8.51551074e-03 1.38756779e-01 1.83583708e-01 0.00000000e+00]
  • Epoch: 7

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:

  • optimizer: {'name': 'Adam', 'learning_rate': 6e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Validation Loss Validation Mean Iou Validation Mean Accuracy Validation Overall Accuracy Validation Per Category Iou Validation Per Category Accuracy Epoch
1.4089 0.8220 0.1975 0.2427 0.7701 [0. 0.58353931 0.7655921 0.04209491 0.53135026 0.11779776
    nan 0.07709853 0.15950712 0.         0.69634813 0.
  1.     0.         0.         0.         0.         0.
    

0.61456822 0. 0.24971248 0.27129675 0. nan 0. 0.07697324 0. 0. 0.78576516 0.61267064 0.84564576 0. 0. 0.08904216 0. ] | [0. 0.88026971 0.93475302 0.04216372 0.5484085 0.13285614 nan 0.08669707 0.19044773 0. 0.90089024 0. 0. 0. 0. 0. 0. 0. 0.76783975 0. 0.42102101 0.28659817 0. nan 0. 0.08671771 0. 0. 0.89590301 0.74932576 0.9434814 0. 0. 0.14245566 0. ] | 0 | | 0.8462 | 0.6135 | 0.2551 | 0.2960 | 0.8200 | [0. 0.66967645 0.80571406 0.56416239 0.66692248 0.24744912 nan 0.23994505 0.28962463 0. 0.76504783 0. 0. 0. 0. 0.14111353 0. 0. 0.6924468 0. 0.27988701 0.41876094 0. nan 0. 0.14755829 0. 0. 0.81614463 0.68429711 0.87710938 0. 0. 0.11234171 0. ] | [0. 0.83805933 0.94928385 0.59586511 0.72913519 0.30595504 nan 0.3128234 0.34805831 0. 0.87847495 0. 0. 0. 0. 0.14205167 0. 0. 0.87543619 0. 0.36001144 0.49498574 0. nan 0. 0.18179115 0. 0. 0.92867923 0.7496178 0.92220166 0. 0. 0.15398549 0. ] | 1 | | 0.7134 | 0.5660 | 0.2780 | 0.3320 | 0.8286 | [0. 0.64791461 0.83800512 0.67301044 0.68120631 0.27361472 nan 0.26715802 0.43596999 0. 0.78649287 0. 0. 0. 0. 0.41256964 0. 0. 0.71114766 0. 0.31646321 0.44682442 0. nan 0. 0.17132551 0. 0. 0.81845697 0.67536699 0.88940936 0. 0. 0.1304862 0. ] | [0. 0.85958877 0.92084269 0.82341633 0.74725972 0.33495972 nan 0.40755277 0.56591531 0. 0.90641721 0. 0. 0. 0. 0.48144408 0. 0. 0.88294811 0. 0.46962078 0.47517397 0. nan 0. 0.20631607 0. 0. 0.90956851 0.85856042 0.94107052 0. 0. 0.16669713 0. ] | 2 | | 0.6320 | 0.5173 | 0.2894 | 0.3454 | 0.8435 | [0. 0.70789146 0.84902296 0.65266358 0.76099965 0.32934391 nan 0.29576422 0.43988204 0. 0.79276447 0. 0. 0. 0. 0.42668367 0. 0. 0.71717911 0. 0.32151249 0.50084444 0. nan 0. 0.18711455 0. 0. 0.82903803 0.68990498 0.8990059 0. 0.00213015 0.14819771 0. ] | [0. 0.84048763 0.93514369 0.68355212 0.88302113 0.458816 nan 0.38623272 0.69456442 0. 0.92379471 0. 0. 0. 0. 0.50677438 0. 0. 0.90362965 0. 0.4662386 0.57368294 0. nan 0. 0.23281768 0. 0. 0.9001526 0.86786434 0.95195314 0. 0.00333751 0.18532191 0. ] | 3 | | 0.5609 | 0.5099 | 0.2920 | 0.3599 | 0.8385 | [0. 0.70817583 0.84131144 0.66573523 0.81449696 0.38891117 nan 0.28124784 0.42659255 0. 0.80855146 0. 0. 0. 0. 0.46011866 0. 0. 0.65458792 0. 0.28411565 0.46758138 0. nan 0. 0.21849067 0. 0. 0.83829062 0.71207623 0.89929169 0. 0.02846127 0.13782635 0. ] | [0. 0.88632871 0.91269832 0.79044294 0.88368528 0.57405218 nan 0.35035973 0.77610775 0. 0.8889696 0. 0. 0. 0. 0.6020786 0. 0. 0.74586521 0. 0.61602403 0.54519561 0. nan 0. 0.28447396 0. 0. 0.94520232 0.85544414 0.95994042 0. 0.04680851 0.21407134 0. ] | 4 | | 0.5256 | 0.4741 | 0.3045 | 0.3598 | 0.8558 | [0.00000000e+00 7.50159008e-01 8.53654462e-01 6.44928131e-01 7.90455244e-01 4.33599913e-01 nan 3.33472954e-01 4.74502513e-01 0.00000000e+00 8.01366017e-01 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 4.67653814e-01 0.00000000e+00 0.00000000e+00 7.27412479e-01 0.00000000e+00 4.18946113e-01 5.04714837e-01 0.00000000e+00 nan 0.00000000e+00 2.00373855e-01 0.00000000e+00 0.00000000e+00 8.50200795e-01 7.41636173e-01 9.08320534e-01 2.77259907e-04 0.00000000e+00 1.45430716e-01 0.00000000e+00] | [0.00000000e+00 8.86487233e-01 9.05201886e-01 7.23139265e-01 8.91929263e-01 7.26675641e-01 nan 4.36386295e-01 6.64378543e-01 0.00000000e+00 8.89056843e-01 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 5.65450644e-01 0.00000000e+00 0.00000000e+00 9.27446136e-01 0.00000000e+00 5.36031025e-01 5.84198054e-01 0.00000000e+00 nan 0.00000000e+00 2.42514534e-01 0.00000000e+00 0.00000000e+00 9.31954754e-01 8.26849708e-01 9.59880377e-01 2.79039335e-04 0.00000000e+00 1.77106051e-01 0.00000000e+00] | 5 | | 0.4761 | 0.4922 | 0.3036 | 0.3754 | 0.8517 | [0.00000000e+00 7.18490241e-01 8.54701589e-01 5.90903088e-01 8.21902743e-01 4.76229883e-01 nan 3.32447673e-01 4.80642540e-01 0.00000000e+00 8.02904449e-01 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 4.73285636e-01 0.00000000e+00 0.00000000e+00 7.16608930e-01 0.00000000e+00 3.16598081e-01 5.12540924e-01 0.00000000e+00 nan 0.00000000e+00 2.27702968e-01 0.00000000e+00 0.00000000e+00 8.51831675e-01 7.39827330e-01 9.07152231e-01 5.59070700e-04 3.70370370e-02 1.56538301e-01 0.00000000e+00] | [0.00000000e+00 9.20834531e-01 8.92075255e-01 7.48664032e-01 9.03709011e-01 7.40703529e-01 nan 4.40828188e-01 7.92719139e-01 0.00000000e+00 9.21593374e-01 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 6.90292855e-01 0.00000000e+00 0.00000000e+00 8.42229041e-01 0.00000000e+00 4.75170857e-01 6.72591473e-01 0.00000000e+00 nan 0.00000000e+00 2.94713089e-01 0.00000000e+00 0.00000000e+00 9.26034809e-01 8.39522012e-01 9.66679296e-01 6.06188900e-04 1.12807676e-01 2.07280968e-01 0.00000000e+00] | 6 | | 0.4495 | 0.4797 | 0.3035 | 0.3702 | 0.8468 | [0.00000000e+00 7.52163526e-01 8.46563375e-01 7.16396797e-01 7.38850637e-01 3.93073019e-01 nan 3.31795957e-01 4.92991567e-01 0.00000000e+00 8.11302090e-01 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 5.16059849e-01 0.00000000e+00 0.00000000e+00 6.56058294e-01 1.25948501e-02 2.66942435e-01 5.34406894e-01 0.00000000e+00 nan 0.00000000e+00 2.27750085e-01 4.86381323e-04 0.00000000e+00 8.48618960e-01 7.25828093e-01 9.17747637e-01 8.28380212e-03 6.74590297e-02 1.51281596e-01 0.00000000e+00] | [0.00000000e+00 8.75360044e-01 9.43650850e-01 8.78658645e-01 7.76578096e-01 4.85757596e-01 nan 4.30901582e-01 7.54126335e-01 0.00000000e+00 9.30112537e-01 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 6.42914247e-01 0.00000000e+00 0.00000000e+00 7.57605356e-01 1.27102686e-02 6.50888458e-01 6.94757080e-01 0.00000000e+00 nan 0.00000000e+00 2.91727649e-01 4.86381323e-04 0.00000000e+00 9.42251577e-01 8.60753175e-01 9.56778008e-01 8.51551074e-03 1.38756779e-01 1.83583708e-01 0.00000000e+00] | 7 |

Framework versions

  • Transformers 4.24.0
  • TensorFlow 2.9.2
  • Datasets 2.7.0
  • Tokenizers 0.13.2