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README.md
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---
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license: other
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tags:
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- vision
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- image-segmentation
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- generated_from_trainer
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model-index:
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- name: segformer-b0-finetuned-segments-stamp-verification
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# segformer-b0-finetuned-segments-stamp-verification
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This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the bilal01/stamp-verification dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0372
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- Mean Iou: 0.1908
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- Mean Accuracy: 0.3817
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- Overall Accuracy: 0.3817
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- Accuracy Unlabeled: nan
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- Accuracy Stamp: 0.3817
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- Iou Unlabeled: 0.0
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- Iou Stamp: 0.3817
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 6e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Stamp | Iou Unlabeled | Iou Stamp |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:---------:|
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| 0.3384 | 0.83 | 20 | 0.2769 | 0.0335 | 0.0670 | 0.0670 | nan | 0.0670 | 0.0 | 0.0670 |
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| 0.2626 | 1.67 | 40 | 0.2201 | 0.1256 | 0.2512 | 0.2512 | nan | 0.2512 | 0.0 | 0.2512 |
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| 0.1944 | 2.5 | 60 | 0.1918 | 0.2030 | 0.4060 | 0.4060 | nan | 0.4060 | 0.0 | 0.4060 |
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| 0.2665 | 3.33 | 80 | 0.1564 | 0.1574 | 0.3148 | 0.3148 | nan | 0.3148 | 0.0 | 0.3148 |
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| 0.1351 | 4.17 | 100 | 0.1194 | 0.1817 | 0.3634 | 0.3634 | nan | 0.3634 | 0.0 | 0.3634 |
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| 0.1156 | 5.0 | 120 | 0.1035 | 0.1334 | 0.2668 | 0.2668 | nan | 0.2668 | 0.0 | 0.2668 |
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| 0.1103 | 5.83 | 140 | 0.0895 | 0.1819 | 0.3638 | 0.3638 | nan | 0.3638 | 0.0 | 0.3638 |
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| 0.0882 | 6.67 | 160 | 0.0746 | 0.0833 | 0.1665 | 0.1665 | nan | 0.1665 | 0.0 | 0.1665 |
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| 0.0778 | 7.5 | 180 | 0.0655 | 0.1927 | 0.3854 | 0.3854 | nan | 0.3854 | 0.0 | 0.3854 |
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| 0.0672 | 8.33 | 200 | 0.0585 | 0.1327 | 0.2654 | 0.2654 | nan | 0.2654 | 0.0 | 0.2654 |
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| 0.0612 | 9.17 | 220 | 0.0615 | 0.1640 | 0.3279 | 0.3279 | nan | 0.3279 | 0.0 | 0.3279 |
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| 0.0611 | 10.0 | 240 | 0.0546 | 0.2466 | 0.4933 | 0.4933 | nan | 0.4933 | 0.0 | 0.4933 |
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| 0.0537 | 10.83 | 260 | 0.0499 | 0.1129 | 0.2258 | 0.2258 | nan | 0.2258 | 0.0 | 0.2258 |
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| 0.0504 | 11.67 | 280 | 0.0502 | 0.1857 | 0.3713 | 0.3713 | nan | 0.3713 | 0.0 | 0.3713 |
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| 0.0707 | 12.5 | 300 | 0.0442 | 0.1710 | 0.3419 | 0.3419 | nan | 0.3419 | 0.0 | 0.3419 |
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| 0.0508 | 13.33 | 320 | 0.0434 | 0.2003 | 0.4006 | 0.4006 | nan | 0.4006 | 0.0 | 0.4006 |
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| 0.0396 | 14.17 | 340 | 0.0420 | 0.1409 | 0.2818 | 0.2818 | nan | 0.2818 | 0.0 | 0.2818 |
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| 0.0395 | 15.0 | 360 | 0.0417 | 0.1640 | 0.3280 | 0.3280 | nan | 0.3280 | 0.0 | 0.3280 |
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| 0.0387 | 15.83 | 380 | 0.0397 | 0.1827 | 0.3655 | 0.3655 | nan | 0.3655 | 0.0 | 0.3655 |
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| 0.0458 | 16.67 | 400 | 0.0387 | 0.1582 | 0.3165 | 0.3165 | nan | 0.3165 | 0.0 | 0.3165 |
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| 0.0363 | 17.5 | 420 | 0.0390 | 0.1724 | 0.3449 | 0.3449 | nan | 0.3449 | 0.0 | 0.3449 |
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| 0.0401 | 18.33 | 440 | 0.0382 | 0.2018 | 0.4036 | 0.4036 | nan | 0.4036 | 0.0 | 0.4036 |
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| 0.0355 | 19.17 | 460 | 0.0382 | 0.2032 | 0.4064 | 0.4064 | nan | 0.4064 | 0.0 | 0.4064 |
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| 0.0447 | 20.0 | 480 | 0.0372 | 0.1908 | 0.3817 | 0.3817 | nan | 0.3817 | 0.0 | 0.3817 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.0+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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