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---
license: openrail
tags:
- generated_from_trainer
- document-image-binarization
- image-segmentation
model-index:
- name: binarization-segformer-b3
results: []
---
# binarization-segformer-b3
This model is a fine-tuned version of [nvidia/segformer-b3-1024-1024](https://huggingface.co/nvidia/segformer-b3-finetuned-cityscapes-1024-1024)
on the same ensemble of 13 datasets as the [SauvolaNet](https://arxiv.org/pdf/2105.05521.pdf) work publicly available
in their GitHub [repository](https://github.com/Leedeng/SauvolaNet#datasets).
It achieves the following results on the evaluation set on DIBCO metrics:
- loss: 0.0743
- DRD: 5.9548
- F-measure: 0.9840
- pseudo F-measure: 0.9740
- PSNR: 16.0119
with PSNR the peak signal-to-noise ratio and DRD the distance reciprocal distortion.
For more information on the above DIBCO metrics, see the 2017 introductory [paper](https://ieeexplore.ieee.org/document/8270159).
## Model description
This model is part of on-going research on pure semantic segmentation models as a formulation of document image binarization (DIBCO).
This is in contrast to the late trend of adapting classical binarization algorithms with neural networks,
such as [DeepOtsu](https://arxiv.org/abs/1901.06081) or [SauvolaNet](https://arxiv.org/pdf/2105.05521.pdf)
as extensions of Otsu's method and Sauvola thresholding algorithm, respectively.
## Intended uses & limitations
TBC
## Training and evaluation data
TBC
## Training procedure
### Training hyperparameters
TBC
### Training results
| training loss | epoch | step | validation loss | DRD | F-measure | pseudo F-measure | PSNR |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:----------------:|:-------:|
| 0.6983 | 0.26 | 10 | 0.7079 | 199.5096 | 0.5945 | 0.5801 | 3.4552 |
| 0.6657 | 0.52 | 20 | 0.6755 | 149.2346 | 0.7006 | 0.6165 | 4.6752 |
| 0.6145 | 0.77 | 30 | 0.6433 | 109.7298 | 0.7831 | 0.6520 | 5.5489 |
| 0.5553 | 1.03 | 40 | 0.5443 | 53.7149 | 0.8952 | 0.8000 | 8.1736 |
| 0.4627 | 1.29 | 50 | 0.4896 | 32.7649 | 0.9321 | 0.8603 | 9.8706 |
| 0.3969 | 1.55 | 60 | 0.4327 | 21.5508 | 0.9526 | 0.8985 | 11.3400 |
| 0.3414 | 1.81 | 70 | 0.3002 | 11.0094 | 0.9732 | 0.9462 | 13.5901 |
| 0.2898 | 2.06 | 80 | 0.2839 | 10.1064 | 0.9748 | 0.9563 | 13.9796 |
| 0.2292 | 2.32 | 90 | 0.2427 | 9.4437 | 0.9761 | 0.9584 | 14.2161 |
| 0.2153 | 2.58 | 100 | 0.2095 | 8.8696 | 0.9771 | 0.9621 | 14.4319 |
| 0.1767 | 2.84 | 110 | 0.1916 | 8.6152 | 0.9776 | 0.9646 | 14.5528 |
| 0.1509 | 3.1 | 120 | 0.1704 | 8.0761 | 0.9791 | 0.9632 | 14.7961 |
| 0.1265 | 3.35 | 130 | 0.1561 | 8.5627 | 0.9784 | 0.9655 | 14.7400 |
| 0.132 | 3.61 | 140 | 0.1318 | 8.1849 | 0.9788 | 0.9670 | 14.8469 |
| 0.1115 | 3.87 | 150 | 0.1317 | 7.8438 | 0.9790 | 0.9657 | 14.9072 |
| 0.0983 | 4.13 | 160 | 0.1273 | 7.9405 | 0.9791 | 0.9673 | 14.9701 |
| 0.1001 | 4.39 | 170 | 0.1234 | 8.4132 | 0.9788 | 0.9691 | 14.8573 |
| 0.0862 | 4.65 | 180 | 0.1147 | 8.0838 | 0.9797 | 0.9678 | 15.0433 |
| 0.0713 | 4.9 | 190 | 0.1134 | 7.6027 | 0.9806 | 0.9687 | 15.2235 |
| 0.0905 | 5.16 | 200 | 0.1061 | 7.2973 | 0.9803 | 0.9699 | 15.1646 |
| 0.0902 | 5.42 | 210 | 0.1061 | 8.4049 | 0.9787 | 0.9699 | 14.8460 |
| 0.0759 | 5.68 | 220 | 0.1062 | 7.7147 | 0.9809 | 0.9695 | 15.2426 |
| 0.0638 | 5.94 | 230 | 0.1019 | 7.7449 | 0.9806 | 0.9695 | 15.2195 |
| 0.0852 | 6.19 | 240 | 0.0962 | 7.0221 | 0.9817 | 0.9693 | 15.4730 |
| 0.0677 | 6.45 | 250 | 0.0961 | 7.2520 | 0.9814 | 0.9710 | 15.3878 |
| 0.0668 | 6.71 | 260 | 0.0972 | 6.6658 | 0.9823 | 0.9689 | 15.6106 |
| 0.0701 | 6.97 | 270 | 0.0909 | 6.9454 | 0.9820 | 0.9713 | 15.5458 |
| 0.0567 | 7.23 | 280 | 0.0925 | 6.5498 | 0.9824 | 0.9718 | 15.5965 |
| 0.0624 | 7.48 | 290 | 0.0899 | 7.3125 | 0.9813 | 0.9717 | 15.3255 |
| 0.0649 | 7.74 | 300 | 0.0932 | 7.4915 | 0.9816 | 0.9684 | 15.5666 |
| 0.0524 | 8.0 | 310 | 0.0905 | 7.1666 | 0.9815 | 0.9711 | 15.4526 |
| 0.0693 | 8.26 | 320 | 0.0901 | 6.5627 | 0.9827 | 0.9704 | 15.7335 |
| 0.0528 | 8.52 | 330 | 0.0845 | 6.6690 | 0.9826 | 0.9734 | 15.5950 |
| 0.0632 | 8.77 | 340 | 0.0822 | 6.2661 | 0.9833 | 0.9723 | 15.8631 |
| 0.0522 | 9.03 | 350 | 0.0844 | 6.0073 | 0.9836 | 0.9715 | 15.9393 |
| 0.0568 | 9.29 | 360 | 0.0817 | 5.9460 | 0.9837 | 0.9721 | 15.9523 |
| 0.057 | 9.55 | 370 | 0.0900 | 7.9726 | 0.9812 | 0.9730 | 15.1229 |
| 0.052 | 9.81 | 380 | 0.0836 | 6.5444 | 0.9822 | 0.9712 | 15.6388 |
| 0.0568 | 10.06 | 390 | 0.0810 | 6.0359 | 0.9836 | 0.9714 | 15.9796 |
| 0.0481 | 10.32 | 400 | 0.0784 | 6.2110 | 0.9835 | 0.9724 | 15.9235 |
| 0.0513 | 10.58 | 410 | 0.0803 | 6.0990 | 0.9835 | 0.9715 | 15.9502 |
| 0.0595 | 10.84 | 420 | 0.0798 | 6.0829 | 0.9835 | 0.9720 | 15.9052 |
| 0.047 | 11.1 | 430 | 0.0779 | 5.8847 | 0.9838 | 0.9725 | 16.0043 |
| 0.0406 | 11.35 | 440 | 0.0802 | 5.7944 | 0.9838 | 0.9713 | 16.0620 |
| 0.0493 | 11.61 | 450 | 0.0781 | 6.0947 | 0.9836 | 0.9731 | 15.9033 |
| 0.064 | 11.87 | 460 | 0.0769 | 6.1257 | 0.9837 | 0.9736 | 15.9080 |
| 0.0622 | 12.13 | 470 | 0.0765 | 6.2964 | 0.9835 | 0.9739 | 15.8188 |
| 0.0457 | 12.39 | 480 | 0.0773 | 5.9826 | 0.9838 | 0.9728 | 16.0119 |
| 0.0447 | 12.65 | 490 | 0.0761 | 5.7977 | 0.9841 | 0.9728 | 16.0900 |
| 0.0515 | 12.9 | 500 | 0.0750 | 5.8569 | 0.9840 | 0.9729 | 16.0633 |
| 0.0357 | 13.16 | 510 | 0.0796 | 5.7990 | 0.9837 | 0.9713 | 16.0818 |
| 0.0503 | 13.42 | 520 | 0.0749 | 5.8323 | 0.9841 | 0.9736 | 16.0510 |
| 0.0508 | 13.68 | 530 | 0.0746 | 6.0361 | 0.9839 | 0.9735 | 15.9709 |
| 0.0533 | 13.94 | 540 | 0.0768 | 6.1596 | 0.9836 | 0.9740 | 15.9193 |
| 0.0503 | 14.19 | 550 | 0.0739 | 5.5900 | 0.9843 | 0.9723 | 16.1883 |
| 0.0515 | 14.45 | 560 | 0.0740 | 5.4660 | 0.9845 | 0.9727 | 16.2745 |
| 0.0502 | 14.71 | 570 | 0.0740 | 5.5895 | 0.9844 | 0.9736 | 16.2054 |
| 0.0401 | 14.97 | 580 | 0.0741 | 5.9694 | 0.9840 | 0.9747 | 15.9603 |
| 0.0495 | 15.23 | 590 | 0.0745 | 5.9136 | 0.9841 | 0.9740 | 16.0458 |
| 0.0413 | 15.48 | 600 | 0.0743 | 5.9548 | 0.9840 | 0.9740 | 16.0119 |
### Framework versions
- transformers 4.31.0
- torch 2.0.0
- datasets 2.13.1
- tokenizers 0.13.3
|