--- license: other base_model: nvidia/segformer-b0-finetuned-ade-512-512 tags: - vision - image-segmentation - generated_from_trainer model-index: - name: segformer-finetuned-coastal results: [] --- # segformer-finetuned-coastal This model is a fine-tuned version of [nvidia/segformer-b0-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512) on the peldrak/coastal3 dataset. It achieves the following results on the evaluation set: - Loss: 1.7456 - Mean Iou: 0.0841 - Mean Accuracy: 0.1629 - Overall Accuracy: 0.3309 - Accuracy Water: 0.2728 - Accuracy Whitewater: 0.0 - Accuracy Sediment: 0.0194 - Accuracy Other Natural Terrain: 0.0 - Accuracy Vegetation: 0.7325 - Accuracy Development: 0.0055 - Accuracy Unknown: 0.1102 - Iou Water: 0.1767 - Iou Whitewater: 0.0 - Iou Sediment: 0.0157 - Iou Other Natural Terrain: 0.0 - Iou Vegetation: 0.3002 - Iou Development: 0.0052 - Iou Unknown: 0.0908 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Water | Accuracy Whitewater | Accuracy Sediment | Accuracy Other Natural Terrain | Accuracy Vegetation | Accuracy Development | Accuracy Unknown | Iou Water | Iou Whitewater | Iou Sediment | Iou Other Natural Terrain | Iou Vegetation | Iou Development | Iou Unknown | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------:|:-------------------:|:-----------------:|:------------------------------:|:-------------------:|:--------------------:|:----------------:|:---------:|:--------------:|:------------:|:-------------------------:|:--------------:|:---------------:|:-----------:| | 1.8429 | 0.12 | 20 | 1.8742 | 0.0623 | 0.1432 | 0.2198 | 0.5172 | 0.0044 | 0.3137 | 0.0050 | 0.1165 | 0.0019 | 0.0435 | 0.2514 | 0.0037 | 0.0521 | 0.0034 | 0.0889 | 0.0019 | 0.0348 | | 1.6623 | 0.25 | 40 | 1.8297 | 0.0731 | 0.1572 | 0.2536 | 0.4349 | 0.0007 | 0.3336 | 0.0010 | 0.3158 | 0.0011 | 0.0135 | 0.2462 | 0.0006 | 0.0569 | 0.0009 | 0.1940 | 0.0011 | 0.0120 | | 1.6173 | 0.37 | 60 | 1.7856 | 0.0812 | 0.1585 | 0.3080 | 0.3151 | 0.0007 | 0.1179 | 0.0005 | 0.6339 | 0.0012 | 0.0405 | 0.2056 | 0.0007 | 0.0357 | 0.0005 | 0.2859 | 0.0012 | 0.0388 | | 1.5078 | 0.49 | 80 | 1.7805 | 0.0764 | 0.1537 | 0.3038 | 0.2792 | 0.0 | 0.1036 | 0.0000 | 0.6639 | 0.0003 | 0.0290 | 0.1839 | 0.0 | 0.0338 | 0.0000 | 0.2895 | 0.0003 | 0.0274 | | 1.3927 | 0.62 | 100 | 1.7549 | 0.0725 | 0.1521 | 0.3227 | 0.2589 | 0.0 | 0.0222 | 0.0001 | 0.7643 | 0.0005 | 0.0187 | 0.1703 | 0.0 | 0.0133 | 0.0001 | 0.3055 | 0.0005 | 0.0179 | | 1.6024 | 0.74 | 120 | 1.7348 | 0.0835 | 0.1598 | 0.3271 | 0.3514 | 0.0 | 0.0204 | 0.0001 | 0.6538 | 0.0005 | 0.0926 | 0.2021 | 0.0 | 0.0147 | 0.0001 | 0.2873 | 0.0005 | 0.0796 | | 1.3287 | 0.86 | 140 | 1.7352 | 0.0776 | 0.1556 | 0.3267 | 0.3309 | 0.0 | 0.0083 | 0.0 | 0.6910 | 0.0000 | 0.0591 | 0.1935 | 0.0 | 0.0076 | 0.0 | 0.2849 | 0.0000 | 0.0573 | | 1.4153 | 0.99 | 160 | 1.7024 | 0.0746 | 0.1567 | 0.3356 | 0.2947 | 0.0 | 0.0011 | 0.0 | 0.7683 | 0.0006 | 0.0320 | 0.1879 | 0.0 | 0.0011 | 0.0 | 0.3021 | 0.0006 | 0.0309 | | 1.3334 | 1.11 | 180 | 1.7262 | 0.0744 | 0.1567 | 0.3374 | 0.3130 | 0.0 | 0.0018 | 0.0 | 0.7620 | 0.0001 | 0.0203 | 0.1988 | 0.0 | 0.0017 | 0.0 | 0.3004 | 0.0001 | 0.0198 | | 1.3956 | 1.23 | 200 | 1.7304 | 0.0858 | 0.1622 | 0.3326 | 0.4838 | 0.0 | 0.0127 | 0.0 | 0.5432 | 0.0015 | 0.0944 | 0.2373 | 0.0 | 0.0112 | 0.0 | 0.2731 | 0.0015 | 0.0777 | | 1.5776 | 1.36 | 220 | 1.7300 | 0.0791 | 0.1622 | 0.3411 | 0.2581 | 0.0 | 0.0010 | 0.0 | 0.8012 | 0.0003 | 0.0748 | 0.1734 | 0.0 | 0.0010 | 0.0 | 0.3144 | 0.0003 | 0.0647 | | 1.1656 | 1.48 | 240 | 1.7248 | 0.0831 | 0.1657 | 0.3440 | 0.2687 | 0.0 | 0.0026 | 0.0 | 0.7879 | 0.0014 | 0.0995 | 0.1775 | 0.0 | 0.0025 | 0.0 | 0.3183 | 0.0014 | 0.0822 | | 1.4429 | 1.6 | 260 | 1.7308 | 0.0764 | 0.1616 | 0.3408 | 0.2091 | 0.0 | 0.0029 | 0.0 | 0.8518 | 0.0037 | 0.0637 | 0.1507 | 0.0 | 0.0028 | 0.0 | 0.3200 | 0.0036 | 0.0578 | | 1.6649 | 1.73 | 280 | 1.7282 | 0.0743 | 0.1564 | 0.3372 | 0.3261 | 0.0 | 0.0033 | 0.0 | 0.7514 | 0.0015 | 0.0128 | 0.1994 | 0.0 | 0.0031 | 0.0 | 0.3037 | 0.0015 | 0.0125 | | 1.3634 | 1.85 | 300 | 1.7216 | 0.0847 | 0.1653 | 0.3413 | 0.3196 | 0.0 | 0.0273 | 0.0 | 0.7402 | 0.0036 | 0.0665 | 0.2012 | 0.0 | 0.0204 | 0.0 | 0.3101 | 0.0035 | 0.0579 | | 1.5224 | 1.98 | 320 | 1.7343 | 0.0822 | 0.1626 | 0.3410 | 0.3793 | 0.0 | 0.0277 | 0.0 | 0.6985 | 0.0017 | 0.0311 | 0.2236 | 0.0 | 0.0210 | 0.0 | 0.3000 | 0.0016 | 0.0293 | | 1.2527 | 2.1 | 340 | 1.7149 | 0.0759 | 0.1559 | 0.3344 | 0.4108 | 0.0 | 0.0119 | 0.0 | 0.6629 | 0.0021 | 0.0034 | 0.2244 | 0.0 | 0.0105 | 0.0 | 0.2913 | 0.0021 | 0.0033 | | 1.5931 | 2.22 | 360 | 1.7170 | 0.0838 | 0.1619 | 0.3365 | 0.4061 | 0.0 | 0.0098 | 0.0 | 0.6414 | 0.0028 | 0.0730 | 0.2228 | 0.0 | 0.0090 | 0.0 | 0.2882 | 0.0027 | 0.0641 | | 1.2434 | 2.35 | 380 | 1.7437 | 0.0844 | 0.1619 | 0.3364 | 0.4734 | 0.0 | 0.0118 | 0.0 | 0.5785 | 0.0028 | 0.0667 | 0.2391 | 0.0 | 0.0105 | 0.0 | 0.2777 | 0.0027 | 0.0607 | | 1.4071 | 2.47 | 400 | 1.7316 | 0.0823 | 0.1639 | 0.3433 | 0.3054 | 0.0 | 0.0053 | 0.0 | 0.7633 | 0.0057 | 0.0674 | 0.1933 | 0.0 | 0.0051 | 0.0 | 0.3125 | 0.0054 | 0.0596 | | 1.2177 | 2.59 | 420 | 1.7195 | 0.0848 | 0.1657 | 0.3459 | 0.3442 | 0.0 | 0.0030 | 0.0 | 0.7315 | 0.0110 | 0.0705 | 0.2084 | 0.0 | 0.0029 | 0.0 | 0.3111 | 0.0102 | 0.0613 | | 1.3724 | 2.72 | 440 | 1.7359 | 0.0843 | 0.1660 | 0.3455 | 0.3091 | 0.0 | 0.0089 | 0.0 | 0.7620 | 0.0057 | 0.0761 | 0.1946 | 0.0 | 0.0084 | 0.0 | 0.3147 | 0.0054 | 0.0669 | | 1.3973 | 2.84 | 460 | 1.7469 | 0.0827 | 0.1617 | 0.3352 | 0.3153 | 0.0 | 0.0101 | 0.0 | 0.7231 | 0.0109 | 0.0724 | 0.1922 | 0.0 | 0.0088 | 0.0 | 0.3045 | 0.0099 | 0.0638 | | 1.3098 | 2.96 | 480 | 1.7193 | 0.0852 | 0.1658 | 0.3447 | 0.3412 | 0.0 | 0.0032 | 0.0 | 0.7240 | 0.0038 | 0.0887 | 0.2039 | 0.0 | 0.0031 | 0.0 | 0.3076 | 0.0037 | 0.0779 | | 0.9545 | 3.09 | 500 | 1.7256 | 0.0840 | 0.1627 | 0.3359 | 0.3366 | 0.0 | 0.0026 | 0.0 | 0.6959 | 0.0077 | 0.0960 | 0.2007 | 0.0 | 0.0025 | 0.0 | 0.2969 | 0.0072 | 0.0808 | | 1.176 | 3.21 | 520 | 1.7334 | 0.0827 | 0.1616 | 0.3357 | 0.3396 | 0.0 | 0.0024 | 0.0 | 0.6963 | 0.0016 | 0.0915 | 0.1999 | 0.0 | 0.0024 | 0.0 | 0.2966 | 0.0015 | 0.0785 | | 1.5622 | 3.33 | 540 | 1.7790 | 0.0689 | 0.1528 | 0.3311 | 0.2393 | 0.0 | 0.0015 | 0.0 | 0.8186 | 0.0009 | 0.0091 | 0.1638 | 0.0 | 0.0015 | 0.0 | 0.3073 | 0.0009 | 0.0089 | | 1.2673 | 3.46 | 560 | 1.7339 | 0.0803 | 0.1585 | 0.3302 | 0.3228 | 0.0 | 0.0113 | 0.0 | 0.7035 | 0.0036 | 0.0686 | 0.1930 | 0.0 | 0.0104 | 0.0 | 0.2942 | 0.0034 | 0.0613 | | 1.418 | 3.58 | 580 | 1.7648 | 0.0760 | 0.1563 | 0.3325 | 0.3074 | 0.0 | 0.0022 | 0.0 | 0.7416 | 0.0041 | 0.0386 | 0.1902 | 0.0 | 0.0022 | 0.0 | 0.2994 | 0.0038 | 0.0363 | | 1.3578 | 3.7 | 600 | 1.7338 | 0.0845 | 0.1619 | 0.3327 | 0.3548 | 0.0 | 0.0119 | 0.0 | 0.6693 | 0.0076 | 0.0898 | 0.2039 | 0.0 | 0.0108 | 0.0 | 0.2940 | 0.0070 | 0.0758 | | 1.1991 | 3.83 | 620 | 1.7711 | 0.0761 | 0.1546 | 0.3285 | 0.3473 | 0.0 | 0.0049 | 0.0 | 0.6906 | 0.0018 | 0.0379 | 0.1995 | 0.0 | 0.0046 | 0.0 | 0.2912 | 0.0017 | 0.0356 | | 1.3699 | 3.95 | 640 | 1.7421 | 0.0829 | 0.1595 | 0.3312 | 0.4290 | 0.0 | 0.0048 | 0.0 | 0.5994 | 0.0032 | 0.0804 | 0.2223 | 0.0 | 0.0045 | 0.0 | 0.2819 | 0.0031 | 0.0687 | | 1.308 | 4.07 | 660 | 1.7769 | 0.0709 | 0.1518 | 0.3250 | 0.2512 | 0.0 | 0.0035 | 0.0 | 0.7784 | 0.0034 | 0.0260 | 0.1656 | 0.0 | 0.0033 | 0.0 | 0.2996 | 0.0033 | 0.0245 | | 1.3746 | 4.2 | 680 | 1.7811 | 0.0749 | 0.1538 | 0.3283 | 0.3497 | 0.0 | 0.0077 | 0.0 | 0.6953 | 0.0037 | 0.0200 | 0.2022 | 0.0 | 0.0070 | 0.0 | 0.2928 | 0.0035 | 0.0191 | | 1.2085 | 4.32 | 700 | 1.7401 | 0.0825 | 0.1600 | 0.3319 | 0.3632 | 0.0 | 0.0106 | 0.0 | 0.6663 | 0.0042 | 0.0759 | 0.2064 | 0.0 | 0.0096 | 0.0 | 0.2912 | 0.0040 | 0.0664 | | 0.8119 | 4.44 | 720 | 1.7638 | 0.0755 | 0.1539 | 0.3284 | 0.3660 | 0.0 | 0.0060 | 0.0 | 0.6784 | 0.0034 | 0.0237 | 0.2073 | 0.0 | 0.0053 | 0.0 | 0.2902 | 0.0033 | 0.0226 | | 1.1547 | 4.57 | 740 | 1.7581 | 0.0795 | 0.1573 | 0.3289 | 0.3410 | 0.0 | 0.0140 | 0.0 | 0.6879 | 0.0030 | 0.0550 | 0.1996 | 0.0 | 0.0116 | 0.0 | 0.2929 | 0.0029 | 0.0497 | | 1.2229 | 4.69 | 760 | 1.7817 | 0.0730 | 0.1550 | 0.3243 | 0.1861 | 0.0 | 0.0124 | 0.0 | 0.8198 | 0.0036 | 0.0631 | 0.1365 | 0.0 | 0.0103 | 0.0 | 0.3050 | 0.0034 | 0.0557 | | 1.3332 | 4.81 | 780 | 1.7580 | 0.0769 | 0.1563 | 0.3276 | 0.2656 | 0.0 | 0.0044 | 0.0 | 0.7524 | 0.0042 | 0.0677 | 0.1721 | 0.0 | 0.0041 | 0.0 | 0.2998 | 0.0040 | 0.0581 | | 1.1668 | 4.94 | 800 | 1.7456 | 0.0841 | 0.1629 | 0.3309 | 0.2728 | 0.0 | 0.0194 | 0.0 | 0.7325 | 0.0055 | 0.1102 | 0.1767 | 0.0 | 0.0157 | 0.0 | 0.3002 | 0.0052 | 0.0908 | ### Framework versions - Transformers 4.33.0 - Pytorch 2.0.0 - Datasets 2.1.0 - Tokenizers 0.13.3