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FINAL_ecc_segformer

Image Segmentation
Transformers
PyTorch
segformer
vision
Generated from Trainer
Inference Endpoints
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FINAL_ecc_segformer / README.md
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metadata
license: other
base_model: nvidia/mit-b5
tags:
  - image-segmentation
  - vision
  - generated_from_trainer
model-index:
  - name: FINAL_ecc_segformer
    results: []

FINAL_ecc_segformer

This model is a fine-tuned version of nvidia/mit-b5 on the rishitunu/ecc_crackdetector_dataset_exhaustive dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0749
  • Mean Iou: 0.1968
  • Mean Accuracy: 0.3939
  • Overall Accuracy: 0.3939
  • Accuracy Background: nan
  • Accuracy Crack: 0.3939
  • Iou Background: 0.0
  • Iou Crack: 0.3936

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: 10000

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Accuracy Background Accuracy Crack Iou Background Iou Crack
0.0534 1.0 548 0.0614 0.1368 0.2750 0.2750 nan 0.2750 0.0 0.2736
0.058 2.0 1096 0.1018 0.2093 0.4238 0.4238 nan 0.4238 0.0 0.4186
0.0482 3.0 1644 0.0508 0.1791 0.4315 0.4315 nan 0.4315 0.0 0.3582
0.0338 4.0 2192 0.0569 0.1849 0.3716 0.3716 nan 0.3716 0.0 0.3698
0.0395 5.0 2740 0.0597 0.1745 0.3506 0.3506 nan 0.3506 0.0 0.3490
0.0372 6.0 3288 0.0509 0.2298 0.4635 0.4635 nan 0.4635 0.0 0.4597
0.0402 7.0 3836 0.0620 0.1751 0.3507 0.3507 nan 0.3507 0.0 0.3503
0.038 8.0 4384 0.0681 0.1905 0.3815 0.3815 nan 0.3815 0.0 0.3810
0.0393 9.0 4932 0.0685 0.2213 0.4433 0.4433 nan 0.4433 0.0 0.4425
0.0376 10.0 5480 0.0590 0.1962 0.3929 0.3929 nan 0.3929 0.0 0.3924
0.0381 11.0 6028 0.0626 0.1891 0.3801 0.3801 nan 0.3801 0.0 0.3783
0.034 12.0 6576 0.0623 0.2061 0.4162 0.4162 nan 0.4162 0.0 0.4122
0.0301 13.0 7124 0.0831 0.1832 0.3669 0.3669 nan 0.3669 0.0 0.3664
0.034 14.0 7672 0.0636 0.2059 0.4119 0.4119 nan 0.4119 0.0 0.4118
0.0303 15.0 8220 0.0705 0.1931 0.3864 0.3864 nan 0.3864 0.0 0.3862
0.0338 16.0 8768 0.0685 0.2101 0.4206 0.4206 nan 0.4206 0.0 0.4202
0.0229 17.0 9316 0.0706 0.2099 0.4204 0.4204 nan 0.4204 0.0 0.4197
0.0337 18.0 9864 0.0742 0.1982 0.3968 0.3968 nan 0.3968 0.0 0.3965
0.0257 18.25 10000 0.0749 0.1968 0.3939 0.3939 nan 0.3939 0.0 0.3936

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cpu
  • Datasets 2.14.6
  • Tokenizers 0.14.1