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---
license: other
base_model: JCAI2000/segformer-b5-finetuned-100by100PNG-50epochs-attempt2-100epochs-backgroundclass-2
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformerb5-finetuned-largerImages
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# segformerb5-finetuned-largerImages
This model is a fine-tuned version of [JCAI2000/segformer-b5-finetuned-100by100PNG-50epochs-attempt2-100epochs-backgroundclass-2](https://huggingface.co/JCAI2000/segformer-b5-finetuned-100by100PNG-50epochs-attempt2-100epochs-backgroundclass-2) on the JCAI2000/LargerImagesLabelled dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0724
- Mean Iou: 0.7754
- Mean Accuracy: 0.8589
- Overall Accuracy: 0.9828
- Accuracy Background: 0.9910
- Accuracy Branch: 0.7269
- Iou Background: 0.9824
- Iou Branch: 0.5684
## 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: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Branch | Iou Background | Iou Branch |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:---------------:|:--------------:|:----------:|
| 0.0872 | 1.18 | 20 | 0.0678 | 0.6870 | 0.7241 | 0.9784 | 0.9954 | 0.4528 | 0.9781 | 0.3958 |
| 0.0848 | 2.35 | 40 | 0.0577 | 0.7333 | 0.7908 | 0.9806 | 0.9932 | 0.5884 | 0.9802 | 0.4864 |
| 0.0549 | 3.53 | 60 | 0.0634 | 0.7485 | 0.8857 | 0.9773 | 0.9834 | 0.7879 | 0.9767 | 0.5203 |
| 0.0653 | 4.71 | 80 | 0.0493 | 0.7662 | 0.8346 | 0.9827 | 0.9926 | 0.6767 | 0.9823 | 0.5500 |
| 0.0596 | 5.88 | 100 | 0.0476 | 0.7497 | 0.7920 | 0.9828 | 0.9955 | 0.5885 | 0.9825 | 0.5168 |
| 0.0458 | 7.06 | 120 | 0.0478 | 0.7636 | 0.8357 | 0.9823 | 0.9921 | 0.6793 | 0.9819 | 0.5452 |
| 0.0285 | 8.24 | 140 | 0.0458 | 0.7758 | 0.8574 | 0.9829 | 0.9913 | 0.7235 | 0.9825 | 0.5691 |
| 0.0341 | 9.41 | 160 | 0.0466 | 0.7670 | 0.8376 | 0.9827 | 0.9923 | 0.6829 | 0.9823 | 0.5517 |
| 0.0369 | 10.59 | 180 | 0.0491 | 0.7699 | 0.8731 | 0.9813 | 0.9885 | 0.7576 | 0.9809 | 0.5589 |
| 0.0352 | 11.76 | 200 | 0.0465 | 0.7731 | 0.8551 | 0.9826 | 0.9911 | 0.7191 | 0.9822 | 0.5640 |
| 0.0477 | 12.94 | 220 | 0.0462 | 0.7721 | 0.8415 | 0.9832 | 0.9926 | 0.6905 | 0.9828 | 0.5615 |
| 0.0404 | 14.12 | 240 | 0.0493 | 0.7704 | 0.8734 | 0.9814 | 0.9886 | 0.7583 | 0.9809 | 0.5599 |
| 0.0221 | 15.29 | 260 | 0.0458 | 0.7798 | 0.8719 | 0.9828 | 0.9901 | 0.7536 | 0.9823 | 0.5772 |
| 0.0263 | 16.47 | 280 | 0.0450 | 0.7778 | 0.8509 | 0.9835 | 0.9923 | 0.7096 | 0.9831 | 0.5726 |
| 0.0364 | 17.65 | 300 | 0.0489 | 0.7756 | 0.8537 | 0.9830 | 0.9917 | 0.7158 | 0.9827 | 0.5686 |
| 0.02 | 18.82 | 320 | 0.0493 | 0.7713 | 0.8474 | 0.9828 | 0.9918 | 0.7031 | 0.9824 | 0.5602 |
| 0.0193 | 20.0 | 340 | 0.0481 | 0.7786 | 0.8694 | 0.9827 | 0.9903 | 0.7484 | 0.9823 | 0.5749 |
| 0.0133 | 21.18 | 360 | 0.0486 | 0.7756 | 0.8552 | 0.9830 | 0.9915 | 0.7189 | 0.9826 | 0.5686 |
| 0.0163 | 22.35 | 380 | 0.0492 | 0.7768 | 0.8632 | 0.9828 | 0.9907 | 0.7357 | 0.9824 | 0.5713 |
| 0.0252 | 23.53 | 400 | 0.0510 | 0.7725 | 0.8605 | 0.9823 | 0.9904 | 0.7306 | 0.9819 | 0.5632 |
| 0.0178 | 24.71 | 420 | 0.0509 | 0.7770 | 0.8665 | 0.9826 | 0.9904 | 0.7427 | 0.9822 | 0.5719 |
| 0.0167 | 25.88 | 440 | 0.0516 | 0.7748 | 0.8615 | 0.9826 | 0.9906 | 0.7323 | 0.9822 | 0.5675 |
| 0.0332 | 27.06 | 460 | 0.0507 | 0.7702 | 0.8422 | 0.9829 | 0.9922 | 0.6921 | 0.9825 | 0.5578 |
| 0.021 | 28.24 | 480 | 0.0522 | 0.7710 | 0.8482 | 0.9827 | 0.9916 | 0.7048 | 0.9823 | 0.5597 |
| 0.0284 | 29.41 | 500 | 0.0536 | 0.7762 | 0.8643 | 0.9826 | 0.9905 | 0.7380 | 0.9822 | 0.5702 |
| 0.0174 | 30.59 | 520 | 0.0535 | 0.7739 | 0.8591 | 0.9826 | 0.9908 | 0.7274 | 0.9822 | 0.5657 |
| 0.0228 | 31.76 | 540 | 0.0527 | 0.7765 | 0.8578 | 0.9830 | 0.9913 | 0.7243 | 0.9826 | 0.5703 |
| 0.0347 | 32.94 | 560 | 0.0530 | 0.7754 | 0.8534 | 0.9830 | 0.9917 | 0.7151 | 0.9826 | 0.5681 |
| 0.0182 | 34.12 | 580 | 0.0554 | 0.7764 | 0.8670 | 0.9825 | 0.9902 | 0.7437 | 0.9821 | 0.5706 |
| 0.0139 | 35.29 | 600 | 0.0521 | 0.7786 | 0.8540 | 0.9834 | 0.9920 | 0.7159 | 0.9830 | 0.5742 |
| 0.0121 | 36.47 | 620 | 0.0549 | 0.7787 | 0.8728 | 0.9826 | 0.9899 | 0.7557 | 0.9822 | 0.5752 |
| 0.0191 | 37.65 | 640 | 0.0560 | 0.7766 | 0.8678 | 0.9825 | 0.9902 | 0.7454 | 0.9821 | 0.5711 |
| 0.0216 | 38.82 | 660 | 0.0553 | 0.7745 | 0.8543 | 0.9829 | 0.9914 | 0.7172 | 0.9825 | 0.5665 |
| 0.0135 | 40.0 | 680 | 0.0569 | 0.7738 | 0.8640 | 0.9823 | 0.9902 | 0.7379 | 0.9819 | 0.5658 |
| 0.0167 | 41.18 | 700 | 0.0566 | 0.7765 | 0.8619 | 0.9828 | 0.9908 | 0.7330 | 0.9824 | 0.5707 |
| 0.0224 | 42.35 | 720 | 0.0570 | 0.7768 | 0.8680 | 0.9825 | 0.9902 | 0.7458 | 0.9821 | 0.5714 |
| 0.0188 | 43.53 | 740 | 0.0575 | 0.7768 | 0.8630 | 0.9828 | 0.9907 | 0.7353 | 0.9824 | 0.5713 |
| 0.0338 | 44.71 | 760 | 0.0565 | 0.7783 | 0.8634 | 0.9830 | 0.9909 | 0.7359 | 0.9826 | 0.5741 |
| 0.0122 | 45.88 | 780 | 0.0585 | 0.7788 | 0.8656 | 0.9829 | 0.9907 | 0.7404 | 0.9825 | 0.5750 |
| 0.0119 | 47.06 | 800 | 0.0587 | 0.7774 | 0.8639 | 0.9828 | 0.9907 | 0.7371 | 0.9824 | 0.5725 |
| 0.0086 | 48.24 | 820 | 0.0594 | 0.7777 | 0.8567 | 0.9832 | 0.9916 | 0.7218 | 0.9828 | 0.5726 |
| 0.0094 | 49.41 | 840 | 0.0597 | 0.7766 | 0.8627 | 0.9828 | 0.9907 | 0.7347 | 0.9823 | 0.5708 |
| 0.0107 | 50.59 | 860 | 0.0619 | 0.7773 | 0.8624 | 0.9829 | 0.9909 | 0.7338 | 0.9825 | 0.5722 |
| 0.0175 | 51.76 | 880 | 0.0605 | 0.7752 | 0.8588 | 0.9828 | 0.9910 | 0.7266 | 0.9824 | 0.5681 |
| 0.0139 | 52.94 | 900 | 0.0620 | 0.7786 | 0.8675 | 0.9828 | 0.9905 | 0.7446 | 0.9824 | 0.5748 |
| 0.02 | 54.12 | 920 | 0.0633 | 0.7764 | 0.8628 | 0.9827 | 0.9907 | 0.7348 | 0.9823 | 0.5704 |
| 0.0294 | 55.29 | 940 | 0.0637 | 0.7762 | 0.8584 | 0.9829 | 0.9912 | 0.7256 | 0.9825 | 0.5699 |
| 0.0175 | 56.47 | 960 | 0.0639 | 0.7789 | 0.8717 | 0.9827 | 0.9900 | 0.7534 | 0.9822 | 0.5755 |
| 0.008 | 57.65 | 980 | 0.0640 | 0.7797 | 0.8667 | 0.9830 | 0.9907 | 0.7428 | 0.9826 | 0.5768 |
| 0.0132 | 58.82 | 1000 | 0.0652 | 0.7754 | 0.8657 | 0.9825 | 0.9902 | 0.7412 | 0.9820 | 0.5687 |
| 0.0339 | 60.0 | 1020 | 0.0640 | 0.7785 | 0.8664 | 0.9828 | 0.9906 | 0.7421 | 0.9824 | 0.5746 |
| 0.0144 | 61.18 | 1040 | 0.0618 | 0.7804 | 0.8577 | 0.9835 | 0.9919 | 0.7236 | 0.9831 | 0.5778 |
| 0.0206 | 62.35 | 1060 | 0.0653 | 0.7767 | 0.8636 | 0.9827 | 0.9907 | 0.7366 | 0.9823 | 0.5710 |
| 0.0165 | 63.53 | 1080 | 0.0651 | 0.7774 | 0.8602 | 0.9830 | 0.9912 | 0.7293 | 0.9826 | 0.5722 |
| 0.0175 | 64.71 | 1100 | 0.0648 | 0.7758 | 0.8568 | 0.9829 | 0.9913 | 0.7222 | 0.9825 | 0.5690 |
| 0.0104 | 65.88 | 1120 | 0.0669 | 0.7771 | 0.8618 | 0.9829 | 0.9909 | 0.7327 | 0.9825 | 0.5717 |
| 0.0191 | 67.06 | 1140 | 0.0662 | 0.7779 | 0.8696 | 0.9826 | 0.9901 | 0.7490 | 0.9822 | 0.5737 |
| 0.0123 | 68.24 | 1160 | 0.0668 | 0.7775 | 0.8591 | 0.9830 | 0.9913 | 0.7270 | 0.9826 | 0.5723 |
| 0.0127 | 69.41 | 1180 | 0.0676 | 0.7772 | 0.8637 | 0.9828 | 0.9907 | 0.7366 | 0.9824 | 0.5720 |
| 0.0092 | 70.59 | 1200 | 0.0673 | 0.7778 | 0.8699 | 0.9826 | 0.9901 | 0.7496 | 0.9822 | 0.5735 |
| 0.0101 | 71.76 | 1220 | 0.0680 | 0.7761 | 0.8694 | 0.9824 | 0.9899 | 0.7489 | 0.9820 | 0.5703 |
| 0.0204 | 72.94 | 1240 | 0.0676 | 0.7772 | 0.8640 | 0.9828 | 0.9907 | 0.7373 | 0.9824 | 0.5721 |
| 0.008 | 74.12 | 1260 | 0.0685 | 0.7768 | 0.8661 | 0.9826 | 0.9904 | 0.7417 | 0.9822 | 0.5714 |
| 0.0124 | 75.29 | 1280 | 0.0676 | 0.7776 | 0.8648 | 0.9828 | 0.9907 | 0.7390 | 0.9824 | 0.5729 |
| 0.0134 | 76.47 | 1300 | 0.0689 | 0.7770 | 0.8672 | 0.9826 | 0.9903 | 0.7441 | 0.9822 | 0.5718 |
| 0.0082 | 77.65 | 1320 | 0.0688 | 0.7755 | 0.8621 | 0.9826 | 0.9907 | 0.7336 | 0.9822 | 0.5687 |
| 0.0125 | 78.82 | 1340 | 0.0698 | 0.7761 | 0.8655 | 0.9826 | 0.9904 | 0.7407 | 0.9822 | 0.5701 |
| 0.0064 | 80.0 | 1360 | 0.0707 | 0.7760 | 0.8611 | 0.9827 | 0.9908 | 0.7314 | 0.9823 | 0.5696 |
| 0.0131 | 81.18 | 1380 | 0.0709 | 0.7765 | 0.8645 | 0.9827 | 0.9905 | 0.7384 | 0.9822 | 0.5707 |
| 0.0099 | 82.35 | 1400 | 0.0696 | 0.7769 | 0.8665 | 0.9826 | 0.9904 | 0.7427 | 0.9822 | 0.5717 |
| 0.0174 | 83.53 | 1420 | 0.0704 | 0.7757 | 0.8612 | 0.9827 | 0.9908 | 0.7317 | 0.9823 | 0.5692 |
| 0.0122 | 84.71 | 1440 | 0.0710 | 0.7754 | 0.8595 | 0.9827 | 0.9910 | 0.7281 | 0.9823 | 0.5685 |
| 0.0136 | 85.88 | 1460 | 0.0705 | 0.7765 | 0.8632 | 0.9827 | 0.9907 | 0.7356 | 0.9823 | 0.5706 |
| 0.0115 | 87.06 | 1480 | 0.0711 | 0.7763 | 0.8638 | 0.9827 | 0.9906 | 0.7370 | 0.9823 | 0.5703 |
| 0.0074 | 88.24 | 1500 | 0.0709 | 0.7763 | 0.8606 | 0.9828 | 0.9910 | 0.7302 | 0.9824 | 0.5702 |
| 0.0073 | 89.41 | 1520 | 0.0707 | 0.7767 | 0.8595 | 0.9829 | 0.9911 | 0.7278 | 0.9825 | 0.5708 |
| 0.0073 | 90.59 | 1540 | 0.0713 | 0.7756 | 0.8556 | 0.9830 | 0.9914 | 0.7197 | 0.9826 | 0.5687 |
| 0.0123 | 91.76 | 1560 | 0.0716 | 0.7763 | 0.8623 | 0.9827 | 0.9907 | 0.7339 | 0.9823 | 0.5702 |
| 0.0161 | 92.94 | 1580 | 0.0712 | 0.7762 | 0.8601 | 0.9828 | 0.9910 | 0.7293 | 0.9824 | 0.5700 |
| 0.0061 | 94.12 | 1600 | 0.0718 | 0.7754 | 0.8597 | 0.9827 | 0.9909 | 0.7284 | 0.9823 | 0.5685 |
| 0.0063 | 95.29 | 1620 | 0.0725 | 0.7751 | 0.8598 | 0.9827 | 0.9909 | 0.7288 | 0.9823 | 0.5679 |
| 0.0124 | 96.47 | 1640 | 0.0722 | 0.7750 | 0.8633 | 0.9825 | 0.9905 | 0.7361 | 0.9821 | 0.5680 |
| 0.0123 | 97.65 | 1660 | 0.0722 | 0.7751 | 0.8598 | 0.9827 | 0.9909 | 0.7287 | 0.9823 | 0.5680 |
| 0.0185 | 98.82 | 1680 | 0.0717 | 0.7753 | 0.8593 | 0.9827 | 0.9910 | 0.7277 | 0.9823 | 0.5683 |
| 0.0152 | 100.0 | 1700 | 0.0724 | 0.7754 | 0.8589 | 0.9828 | 0.9910 | 0.7269 | 0.9824 | 0.5684 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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