Edit model card

segformer-b4-ade-finetuned-grCoastline

This model is a fine-tuned version of nvidia/segformer-b4-finetuned-ade-512-512 on the peldrak/grCoastline_512 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2116
  • Mean Iou: 0.7207
  • Mean Accuracy: 0.7864
  • Overall Accuracy: 0.9441
  • Accuracy Water: 0.9915
  • Accuracy Whitewater: 0.0
  • Accuracy Sediment: 0.9083
  • Accuracy Other Natural Terrain: 0.8596
  • Accuracy Vegetation: 0.8771
  • Accuracy Development: 0.8701
  • Accuracy Unknown: 0.9983
  • Iou Water: 0.9580
  • Iou Whitewater: 0.0
  • Iou Sediment: 0.8691
  • Iou Other Natural Terrain: 0.7108
  • Iou Vegetation: 0.8236
  • Iou Development: 0.6878
  • Iou Unknown: 0.9957
  • F1 Score: 0.9437

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

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 F1 Score
1.4532 0.24 20 1.3435 0.4211 0.5264 0.7441 0.7775 0.0 0.2537 0.5410 0.7502 0.3664 0.9961 0.6995 0.0 0.2230 0.3135 0.4349 0.3008 0.9758 0.7366
1.0467 0.49 40 0.8901 0.4799 0.5609 0.8306 0.9261 0.0 0.6581 0.3109 0.9513 0.0809 0.9992 0.8704 0.0 0.5553 0.3049 0.5627 0.0804 0.9860 0.8109
0.9494 0.73 60 0.6358 0.5209 0.5972 0.8680 0.9788 0.0 0.8070 0.4142 0.9622 0.0220 0.9964 0.9044 0.0 0.6693 0.4008 0.6578 0.0220 0.9921 0.8452
0.6118 0.98 80 0.5235 0.5454 0.6191 0.8834 0.9836 0.0 0.8558 0.5071 0.9635 0.0283 0.9951 0.9172 0.0 0.6969 0.4748 0.7090 0.0282 0.9914 0.8625
0.5458 1.22 100 0.4739 0.5846 0.6514 0.8875 0.9514 0.0 0.8431 0.5217 0.9639 0.2829 0.9967 0.9258 0.0 0.7593 0.4726 0.6684 0.2728 0.9930 0.8793
0.5935 1.46 120 0.3786 0.6090 0.6793 0.9055 0.9774 0.0 0.9195 0.7271 0.8854 0.2475 0.9980 0.9221 0.0 0.7820 0.5782 0.7474 0.2415 0.9921 0.8969
0.616 1.71 140 0.3630 0.6382 0.7043 0.9141 0.9845 0.0 0.9106 0.7205 0.8929 0.4243 0.9975 0.9132 0.0 0.7515 0.6445 0.7799 0.3859 0.9920 0.9090
0.6891 1.95 160 0.3563 0.6249 0.6897 0.9049 0.9912 0.0 0.8575 0.5156 0.9541 0.5139 0.9955 0.9010 0.0 0.7908 0.4895 0.7447 0.4577 0.9906 0.8978
0.3915 2.2 180 0.3039 0.6420 0.7094 0.9122 0.9690 0.0 0.8829 0.7779 0.8809 0.4559 0.9990 0.9296 0.0 0.8211 0.5859 0.7445 0.4225 0.9901 0.9093
0.478 2.44 200 0.2957 0.6661 0.7380 0.9201 0.9884 0.0 0.8179 0.8009 0.8854 0.6765 0.9973 0.9150 0.0 0.7697 0.6348 0.7986 0.5532 0.9916 0.9186
0.2891 2.68 220 0.2687 0.6781 0.7439 0.9258 0.9890 0.0 0.9161 0.7389 0.8977 0.6776 0.9881 0.9253 0.0 0.8384 0.6330 0.7898 0.5726 0.9874 0.9238
0.3432 2.93 240 0.2629 0.6725 0.7379 0.9246 0.9752 0.0 0.9444 0.7407 0.8825 0.6246 0.9976 0.9308 0.0 0.8389 0.6136 0.7804 0.5506 0.9935 0.9224
0.4379 3.17 260 0.2528 0.6787 0.7360 0.9283 0.9837 0.0 0.9170 0.7116 0.9280 0.6139 0.9974 0.9422 0.0 0.8382 0.6218 0.7870 0.5687 0.9931 0.9255
0.2129 3.41 280 0.2250 0.6775 0.7401 0.9264 0.9911 0.0 0.9001 0.6653 0.9301 0.7006 0.9936 0.9330 0.0 0.8456 0.6021 0.7849 0.5853 0.9918 0.9237
0.1941 3.66 300 0.2191 0.6943 0.7621 0.9336 0.9770 0.0 0.9426 0.8365 0.8619 0.7193 0.9974 0.9377 0.0 0.8296 0.6934 0.8076 0.5981 0.9938 0.9325
0.3357 3.9 320 0.2315 0.6841 0.7582 0.9267 0.9782 0.0 0.8671 0.7910 0.8801 0.7948 0.9961 0.9322 0.0 0.8089 0.6298 0.8011 0.6240 0.9926 0.9261
0.2456 4.15 340 0.2462 0.6904 0.7586 0.9303 0.9895 0.0 0.9229 0.6965 0.8897 0.8146 0.9970 0.9339 0.0 0.8563 0.6091 0.7915 0.6476 0.9947 0.9284
0.3712 4.39 360 0.2366 0.6918 0.7696 0.9307 0.9848 0.0 0.8491 0.8504 0.8689 0.8389 0.9951 0.9514 0.0 0.8085 0.6517 0.8102 0.6272 0.9935 0.9311
0.4034 4.63 380 0.2442 0.6854 0.7691 0.9254 0.9799 0.0 0.9505 0.8457 0.7848 0.8289 0.9940 0.9361 0.0 0.8287 0.6650 0.7533 0.6215 0.9930 0.9248
0.1794 4.88 400 0.2162 0.6951 0.7555 0.9338 0.9831 0.0 0.8868 0.7703 0.9249 0.7271 0.9967 0.9449 0.0 0.8392 0.6450 0.8101 0.6320 0.9945 0.9324
0.3036 5.12 420 0.2356 0.6869 0.7514 0.9303 0.9889 0.0 0.9184 0.6697 0.9145 0.7701 0.9983 0.9289 0.0 0.8442 0.6064 0.8075 0.6280 0.9932 0.9277
0.1948 5.37 440 0.2138 0.6963 0.7661 0.9333 0.9801 0.0 0.8889 0.8187 0.8823 0.7944 0.9982 0.9443 0.0 0.8363 0.6453 0.8165 0.6381 0.9939 0.9330
0.5839 5.61 460 0.2248 0.6998 0.7699 0.9350 0.9913 0.0 0.9310 0.7673 0.8695 0.8340 0.9966 0.9330 0.0 0.8511 0.6645 0.8143 0.6420 0.9936 0.9338
0.2039 5.85 480 0.2311 0.6949 0.7695 0.9300 0.9801 0.0 0.8510 0.8609 0.8619 0.8362 0.9967 0.9417 0.0 0.8106 0.6365 0.8076 0.6740 0.9942 0.9304
0.1818 6.1 500 0.2297 0.7037 0.7794 0.9338 0.9788 0.0 0.9420 0.8915 0.8103 0.8374 0.9955 0.9417 0.0 0.8651 0.6649 0.7871 0.6730 0.9942 0.9338
0.1637 6.34 520 0.1984 0.7105 0.7757 0.9389 0.9817 0.0 0.9503 0.8314 0.8634 0.8062 0.9969 0.9409 0.0 0.8601 0.6899 0.8123 0.6756 0.9946 0.9380
0.2034 6.59 540 0.1970 0.7170 0.7771 0.9426 0.9875 0.0 0.8953 0.8225 0.9205 0.8200 0.9939 0.9478 0.0 0.8602 0.7085 0.8317 0.6781 0.9926 0.9418
0.2673 6.83 560 0.2055 0.7111 0.7800 0.9400 0.9907 0.0 0.9323 0.8022 0.8739 0.8651 0.9957 0.9366 0.0 0.8675 0.6941 0.8262 0.6591 0.9939 0.9392
0.2446 7.07 580 0.2391 0.6769 0.7454 0.9286 0.9829 0.0 0.9409 0.9085 0.8298 0.5581 0.9979 0.9531 0.0 0.8470 0.6501 0.7880 0.5054 0.9944 0.9274
0.1747 7.32 600 0.2450 0.6993 0.7642 0.9351 0.9872 0.0 0.9200 0.7115 0.9121 0.8223 0.9967 0.9458 0.0 0.8690 0.6249 0.8060 0.6552 0.9939 0.9335
0.1262 7.56 620 0.2595 0.6955 0.7652 0.9315 0.9878 0.0 0.9453 0.7199 0.8657 0.8406 0.9970 0.9399 0.0 0.8588 0.6152 0.7856 0.6745 0.9946 0.9298
0.1223 7.8 640 0.2334 0.7028 0.7704 0.9339 0.9861 0.0 0.9214 0.8069 0.8572 0.8234 0.9977 0.9527 0.0 0.8672 0.6354 0.7841 0.6854 0.9948 0.9334
0.0915 8.05 660 0.2561 0.6879 0.7660 0.9258 0.9905 0.0 0.8363 0.8988 0.8221 0.8176 0.9967 0.9483 0.0 0.8053 0.6239 0.7819 0.6615 0.9946 0.9266
0.1095 8.29 680 0.2018 0.7179 0.7813 0.9431 0.9851 0.0 0.9306 0.7844 0.9086 0.8650 0.9950 0.9425 0.0 0.8742 0.6973 0.8350 0.6831 0.9933 0.9421
0.196 8.54 700 0.2125 0.7115 0.7834 0.9392 0.9800 0.0 0.9376 0.8437 0.8523 0.8722 0.9979 0.9515 0.0 0.8737 0.6855 0.8046 0.6707 0.9947 0.9389
0.1548 8.78 720 0.1893 0.7261 0.7833 0.9467 0.9830 0.0 0.9370 0.8452 0.9035 0.8170 0.9973 0.9545 0.0 0.8776 0.7329 0.8299 0.6936 0.9944 0.9458
0.1376 9.02 740 0.2467 0.7101 0.7706 0.9394 0.9868 0.0 0.9268 0.7615 0.9067 0.8150 0.9977 0.9536 0.0 0.8685 0.6624 0.8077 0.6831 0.9952 0.9381
0.1569 9.27 760 0.2038 0.7184 0.7823 0.9432 0.9904 0.0 0.9064 0.8209 0.8961 0.8651 0.9976 0.9505 0.0 0.8672 0.7048 0.8265 0.6845 0.9952 0.9425
0.1633 9.51 780 0.1953 0.7213 0.7820 0.9443 0.9882 0.0 0.9093 0.8436 0.8986 0.8371 0.9975 0.9499 0.0 0.8690 0.7129 0.8304 0.6919 0.9950 0.9436
0.1501 9.76 800 0.2605 0.7013 0.7688 0.9352 0.9799 0.0 0.8636 0.8899 0.8816 0.7689 0.9975 0.9573 0.0 0.8129 0.6623 0.8220 0.6595 0.9950 0.9353
0.2376 10.0 820 0.2071 0.7186 0.7850 0.9438 0.9922 0.0 0.9306 0.8279 0.8795 0.8683 0.9962 0.9505 0.0 0.8731 0.7145 0.8282 0.6695 0.9947 0.9431
0.0856 10.24 840 0.2190 0.7113 0.7689 0.9410 0.9878 0.0 0.9119 0.8175 0.9127 0.7559 0.9964 0.9583 0.0 0.8737 0.6801 0.8152 0.6568 0.9948 0.9401
0.2257 10.49 860 0.2133 0.7124 0.7847 0.9402 0.9871 0.0 0.9328 0.8304 0.8554 0.8895 0.9980 0.9565 0.0 0.8557 0.7005 0.8108 0.6686 0.9948 0.9398
0.2022 10.73 880 0.2517 0.7030 0.7746 0.9355 0.9845 0.0 0.8451 0.8379 0.8945 0.8631 0.9973 0.9514 0.0 0.8109 0.6656 0.8229 0.6754 0.9949 0.9353
0.0923 10.98 900 0.2118 0.7122 0.7717 0.9416 0.9863 0.0 0.8904 0.8660 0.9057 0.7555 0.9979 0.9563 0.0 0.8418 0.7016 0.8320 0.6582 0.9952 0.9409
0.1639 11.22 920 0.1961 0.7244 0.7817 0.9471 0.9835 0.0 0.9354 0.8432 0.9118 0.8013 0.9967 0.9584 0.0 0.8649 0.7337 0.8397 0.6790 0.9951 0.9462
0.0676 11.46 940 0.2238 0.7135 0.7829 0.9421 0.9885 0.0 0.9482 0.7915 0.8765 0.8784 0.9973 0.9503 0.0 0.8653 0.7000 0.8282 0.6555 0.9952 0.9413
0.056 11.71 960 0.1908 0.7284 0.7848 0.9478 0.9862 0.0 0.9206 0.8434 0.9143 0.8319 0.9973 0.9583 0.0 0.8724 0.7308 0.8375 0.7048 0.9948 0.9470
0.1205 11.95 980 0.2000 0.7248 0.7914 0.9457 0.9844 0.0 0.9377 0.8256 0.8807 0.9132 0.9986 0.9581 0.0 0.8681 0.7249 0.8265 0.7016 0.9947 0.9450
0.0429 12.2 1000 0.1937 0.7285 0.7865 0.9476 0.9856 0.0 0.9298 0.8327 0.9064 0.8529 0.9982 0.9590 0.0 0.8687 0.7326 0.8335 0.7108 0.9952 0.9468
0.0992 12.44 1020 0.2081 0.7225 0.7858 0.9448 0.9863 0.0 0.9394 0.8478 0.8780 0.8522 0.9972 0.9576 0.0 0.8668 0.7191 0.8230 0.6955 0.9953 0.9441
0.089 12.68 1040 0.2044 0.7243 0.7812 0.9466 0.9832 0.0 0.9240 0.8403 0.9128 0.8095 0.9987 0.9561 0.0 0.8724 0.7274 0.8351 0.6844 0.9949 0.9457
0.1252 12.93 1060 0.2146 0.7138 0.7750 0.9417 0.9824 0.0 0.9125 0.8768 0.8895 0.7662 0.9973 0.9573 0.0 0.8521 0.6993 0.8267 0.6659 0.9950 0.9412
0.3201 13.17 1080 0.2169 0.7197 0.7849 0.9439 0.9796 0.0 0.9489 0.8613 0.8713 0.8352 0.9977 0.9580 0.0 0.8636 0.7225 0.8209 0.6774 0.9955 0.9434
0.101 13.41 1100 0.2023 0.7268 0.7848 0.9482 0.9871 0.0 0.9314 0.8350 0.9111 0.8315 0.9978 0.9587 0.0 0.8702 0.7416 0.8412 0.6806 0.9952 0.9473
0.0522 13.66 1120 0.2116 0.7207 0.7864 0.9441 0.9915 0.0 0.9083 0.8596 0.8771 0.8701 0.9983 0.9580 0.0 0.8691 0.7108 0.8236 0.6878 0.9957 0.9437

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2
Downloads last month
0
Safetensors
Model size
64M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for peldrak/segformer-b4-ade-finetuned-grCoastline

Finetuned
(4)
this model