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---
library_name: transformers
license: other
base_model: nvidia/segformer-b4-finetuned-ade-512-512
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b4-finetuned-ade-512-512_corm
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. -->
# segformer-b4-finetuned-ade-512-512_corm
This model is a fine-tuned version of [nvidia/segformer-b4-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b4-finetuned-ade-512-512) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0391
- Mean Iou: 0.9261
- Mean Accuracy: 0.9594
- Overall Accuracy: 0.9863
- Accuracy Background: 0.9977
- Accuracy Corm: 0.9268
- Accuracy Damage: 0.9537
- Iou Background: 0.9944
- Iou Corm: 0.8758
- Iou Damage: 0.9082
## 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
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Corm | Accuracy Damage | Iou Background | Iou Corm | Iou Damage |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:---------------:|:--------------:|:--------:|:----------:|
| 1.0242 | 0.6061 | 20 | 1.0187 | 0.3316 | 0.6012 | 0.5573 | 0.5345 | 0.5453 | 0.7237 | 0.5341 | 0.1224 | 0.3383 |
| 0.7686 | 1.2121 | 40 | 0.6913 | 0.7059 | 0.8624 | 0.9170 | 0.9369 | 0.7070 | 0.9434 | 0.9369 | 0.4718 | 0.7090 |
| 0.5281 | 1.8182 | 60 | 0.4782 | 0.8060 | 0.9165 | 0.9537 | 0.9697 | 0.8764 | 0.9032 | 0.9696 | 0.6651 | 0.7833 |
| 0.3931 | 2.4242 | 80 | 0.3279 | 0.8530 | 0.9308 | 0.9690 | 0.9843 | 0.8578 | 0.9503 | 0.9837 | 0.7547 | 0.8206 |
| 0.2574 | 3.0303 | 100 | 0.2112 | 0.8733 | 0.9335 | 0.9753 | 0.9915 | 0.8406 | 0.9685 | 0.9899 | 0.7898 | 0.8402 |
| 0.2112 | 3.6364 | 120 | 0.1588 | 0.8990 | 0.9450 | 0.9807 | 0.9952 | 0.8824 | 0.9576 | 0.9918 | 0.8337 | 0.8716 |
| 0.1545 | 4.2424 | 140 | 0.1198 | 0.8960 | 0.9398 | 0.9805 | 0.9965 | 0.8539 | 0.9690 | 0.9924 | 0.8245 | 0.8711 |
| 0.1127 | 4.8485 | 160 | 0.1152 | 0.8851 | 0.9395 | 0.9782 | 0.9973 | 0.9609 | 0.8604 | 0.9923 | 0.8191 | 0.8440 |
| 0.1147 | 5.4545 | 180 | 0.0862 | 0.9130 | 0.9546 | 0.9834 | 0.9956 | 0.9170 | 0.9513 | 0.9930 | 0.8579 | 0.8881 |
| 0.0945 | 6.0606 | 200 | 0.0793 | 0.9083 | 0.9457 | 0.9829 | 0.9977 | 0.8728 | 0.9667 | 0.9929 | 0.8437 | 0.8881 |
| 0.0942 | 6.6667 | 220 | 0.0730 | 0.9170 | 0.9519 | 0.9842 | 0.9985 | 0.9263 | 0.9309 | 0.9926 | 0.8624 | 0.8960 |
| 0.0766 | 7.2727 | 240 | 0.0675 | 0.9185 | 0.9565 | 0.9847 | 0.9972 | 0.9365 | 0.9358 | 0.9936 | 0.8656 | 0.8963 |
| 0.0674 | 7.8788 | 260 | 0.0635 | 0.9160 | 0.9523 | 0.9844 | 0.9972 | 0.8897 | 0.9700 | 0.9937 | 0.8585 | 0.8957 |
| 0.0662 | 8.4848 | 280 | 0.0593 | 0.9199 | 0.9520 | 0.9849 | 0.9985 | 0.8984 | 0.9590 | 0.9931 | 0.8637 | 0.9030 |
| 0.0683 | 9.0909 | 300 | 0.0582 | 0.9176 | 0.9516 | 0.9847 | 0.9981 | 0.8914 | 0.9652 | 0.9937 | 0.8598 | 0.8994 |
| 0.0591 | 9.6970 | 320 | 0.0548 | 0.9222 | 0.9565 | 0.9855 | 0.9974 | 0.9076 | 0.9644 | 0.9941 | 0.8693 | 0.9031 |
| 0.0649 | 10.3030 | 340 | 0.0541 | 0.9201 | 0.9553 | 0.9849 | 0.9984 | 0.9407 | 0.9269 | 0.9935 | 0.8685 | 0.8982 |
| 0.0622 | 10.9091 | 360 | 0.0525 | 0.9155 | 0.9497 | 0.9844 | 0.9982 | 0.8803 | 0.9707 | 0.9938 | 0.8551 | 0.8976 |
| 0.0637 | 11.5152 | 380 | 0.0542 | 0.9124 | 0.9466 | 0.9838 | 0.9986 | 0.8720 | 0.9692 | 0.9933 | 0.8491 | 0.8948 |
| 0.0647 | 12.1212 | 400 | 0.0486 | 0.9244 | 0.9562 | 0.9857 | 0.9988 | 0.9340 | 0.9358 | 0.9933 | 0.8738 | 0.9060 |
| 0.0418 | 12.7273 | 420 | 0.0466 | 0.9267 | 0.9589 | 0.9862 | 0.9980 | 0.9288 | 0.9500 | 0.9939 | 0.8773 | 0.9088 |
| 0.0459 | 13.3333 | 440 | 0.0460 | 0.9260 | 0.9601 | 0.9862 | 0.9977 | 0.9378 | 0.9448 | 0.9942 | 0.8770 | 0.9069 |
| 0.048 | 13.9394 | 460 | 0.0453 | 0.9253 | 0.9586 | 0.9861 | 0.9981 | 0.9335 | 0.9443 | 0.9941 | 0.8751 | 0.9067 |
| 0.0397 | 14.5455 | 480 | 0.0446 | 0.9263 | 0.9589 | 0.9863 | 0.9978 | 0.9219 | 0.9569 | 0.9943 | 0.8759 | 0.9088 |
| 0.0546 | 15.1515 | 500 | 0.0457 | 0.9219 | 0.9572 | 0.9854 | 0.9983 | 0.9447 | 0.9285 | 0.9940 | 0.8707 | 0.9010 |
| 0.0427 | 15.7576 | 520 | 0.0432 | 0.9267 | 0.9611 | 0.9863 | 0.9973 | 0.9374 | 0.9485 | 0.9943 | 0.8774 | 0.9084 |
| 0.0463 | 16.3636 | 540 | 0.0424 | 0.9263 | 0.9576 | 0.9863 | 0.9982 | 0.9148 | 0.9598 | 0.9941 | 0.8750 | 0.9098 |
| 0.048 | 16.9697 | 560 | 0.0421 | 0.9272 | 0.9588 | 0.9865 | 0.9981 | 0.9229 | 0.9555 | 0.9942 | 0.8776 | 0.9099 |
| 0.0534 | 17.5758 | 580 | 0.0420 | 0.9269 | 0.9610 | 0.9863 | 0.9975 | 0.9393 | 0.9460 | 0.9943 | 0.8777 | 0.9085 |
| 0.0411 | 18.1818 | 600 | 0.0420 | 0.9249 | 0.9581 | 0.9861 | 0.9976 | 0.9133 | 0.9634 | 0.9944 | 0.8734 | 0.9068 |
| 0.0417 | 18.7879 | 620 | 0.0425 | 0.9231 | 0.9573 | 0.9858 | 0.9973 | 0.9042 | 0.9705 | 0.9945 | 0.8699 | 0.9048 |
| 0.0368 | 19.3939 | 640 | 0.0405 | 0.9283 | 0.9603 | 0.9867 | 0.9979 | 0.9281 | 0.9548 | 0.9944 | 0.8795 | 0.9111 |
| 0.048 | 20.0 | 660 | 0.0399 | 0.9279 | 0.9608 | 0.9866 | 0.9977 | 0.9325 | 0.9522 | 0.9944 | 0.8793 | 0.9100 |
| 0.0363 | 20.6061 | 680 | 0.0415 | 0.9255 | 0.9593 | 0.9861 | 0.9981 | 0.9421 | 0.9378 | 0.9943 | 0.8761 | 0.9061 |
| 0.0459 | 21.2121 | 700 | 0.0421 | 0.9243 | 0.9583 | 0.9858 | 0.9984 | 0.9471 | 0.9294 | 0.9940 | 0.8748 | 0.9042 |
| 0.0436 | 21.8182 | 720 | 0.0403 | 0.9269 | 0.9610 | 0.9863 | 0.9976 | 0.9426 | 0.9429 | 0.9943 | 0.8782 | 0.9080 |
| 0.0461 | 22.4242 | 740 | 0.0406 | 0.9260 | 0.9615 | 0.9862 | 0.9974 | 0.9476 | 0.9396 | 0.9945 | 0.8771 | 0.9065 |
| 0.0319 | 23.0303 | 760 | 0.0395 | 0.9269 | 0.9614 | 0.9864 | 0.9970 | 0.9306 | 0.9567 | 0.9944 | 0.8780 | 0.9082 |
| 0.0366 | 23.6364 | 780 | 0.0392 | 0.9277 | 0.9607 | 0.9866 | 0.9978 | 0.9352 | 0.9492 | 0.9944 | 0.8793 | 0.9095 |
| 0.0351 | 24.2424 | 800 | 0.0390 | 0.9282 | 0.9605 | 0.9866 | 0.9979 | 0.9338 | 0.9497 | 0.9943 | 0.8796 | 0.9106 |
| 0.0322 | 24.8485 | 820 | 0.0388 | 0.9280 | 0.9600 | 0.9866 | 0.9980 | 0.9289 | 0.9531 | 0.9944 | 0.8790 | 0.9108 |
| 0.0346 | 25.4545 | 840 | 0.0392 | 0.9266 | 0.9595 | 0.9864 | 0.9976 | 0.9173 | 0.9635 | 0.9944 | 0.8760 | 0.9095 |
| 0.0342 | 26.0606 | 860 | 0.0398 | 0.9243 | 0.9575 | 0.9861 | 0.9976 | 0.9059 | 0.9691 | 0.9945 | 0.8715 | 0.9070 |
| 0.0389 | 26.6667 | 880 | 0.0387 | 0.9275 | 0.9617 | 0.9865 | 0.9970 | 0.9272 | 0.9609 | 0.9945 | 0.8793 | 0.9087 |
| 0.033 | 27.2727 | 900 | 0.0392 | 0.9272 | 0.9596 | 0.9865 | 0.9976 | 0.9168 | 0.9645 | 0.9944 | 0.8772 | 0.9099 |
| 0.0316 | 27.8788 | 920 | 0.0388 | 0.9269 | 0.9602 | 0.9865 | 0.9973 | 0.9196 | 0.9636 | 0.9945 | 0.8768 | 0.9095 |
| 0.0391 | 28.4848 | 940 | 0.0396 | 0.9262 | 0.9604 | 0.9863 | 0.9970 | 0.9200 | 0.9642 | 0.9945 | 0.8760 | 0.9082 |
| 0.0305 | 29.0909 | 960 | 0.0386 | 0.9275 | 0.9600 | 0.9865 | 0.9978 | 0.9241 | 0.9580 | 0.9945 | 0.8780 | 0.9101 |
| 0.034 | 29.6970 | 980 | 0.0392 | 0.9267 | 0.9600 | 0.9863 | 0.9980 | 0.9399 | 0.9421 | 0.9943 | 0.8777 | 0.9081 |
| 0.0322 | 30.3030 | 1000 | 0.0383 | 0.9275 | 0.9607 | 0.9865 | 0.9976 | 0.9321 | 0.9524 | 0.9945 | 0.8786 | 0.9094 |
| 0.0288 | 30.9091 | 1020 | 0.0389 | 0.9271 | 0.9606 | 0.9864 | 0.9976 | 0.9339 | 0.9504 | 0.9944 | 0.8782 | 0.9087 |
| 0.0324 | 31.5152 | 1040 | 0.0394 | 0.9265 | 0.9601 | 0.9863 | 0.9978 | 0.9362 | 0.9462 | 0.9944 | 0.8770 | 0.9080 |
| 0.0329 | 32.1212 | 1060 | 0.0399 | 0.9259 | 0.9599 | 0.9862 | 0.9980 | 0.9421 | 0.9396 | 0.9943 | 0.8767 | 0.9068 |
| 0.0211 | 32.7273 | 1080 | 0.0390 | 0.9268 | 0.9593 | 0.9864 | 0.9981 | 0.9310 | 0.9490 | 0.9943 | 0.8773 | 0.9087 |
| 0.0227 | 33.3333 | 1100 | 0.0389 | 0.9269 | 0.9581 | 0.9864 | 0.9983 | 0.9194 | 0.9565 | 0.9941 | 0.8764 | 0.9101 |
| 0.0328 | 33.9394 | 1120 | 0.0391 | 0.9270 | 0.9587 | 0.9864 | 0.9983 | 0.9284 | 0.9494 | 0.9941 | 0.8773 | 0.9096 |
| 0.0297 | 34.5455 | 1140 | 0.0389 | 0.9267 | 0.9597 | 0.9864 | 0.9979 | 0.9304 | 0.9509 | 0.9944 | 0.8771 | 0.9087 |
| 0.0346 | 35.1515 | 1160 | 0.0390 | 0.9267 | 0.9595 | 0.9864 | 0.9979 | 0.9292 | 0.9516 | 0.9943 | 0.8769 | 0.9088 |
| 0.0231 | 35.7576 | 1180 | 0.0391 | 0.9266 | 0.9587 | 0.9863 | 0.9981 | 0.9232 | 0.9547 | 0.9942 | 0.8764 | 0.9093 |
| 0.0301 | 36.3636 | 1200 | 0.0387 | 0.9267 | 0.9594 | 0.9864 | 0.9978 | 0.9232 | 0.9572 | 0.9944 | 0.8764 | 0.9093 |
| 0.0331 | 36.9697 | 1220 | 0.0388 | 0.9269 | 0.9597 | 0.9864 | 0.9979 | 0.9290 | 0.9522 | 0.9943 | 0.8772 | 0.9091 |
| 0.0281 | 37.5758 | 1240 | 0.0389 | 0.9268 | 0.9589 | 0.9864 | 0.9981 | 0.9266 | 0.9520 | 0.9943 | 0.8769 | 0.9093 |
| 0.0208 | 38.1818 | 1260 | 0.0390 | 0.9266 | 0.9605 | 0.9863 | 0.9975 | 0.9318 | 0.9523 | 0.9944 | 0.8768 | 0.9086 |
| 0.0348 | 38.7879 | 1280 | 0.0397 | 0.9257 | 0.9598 | 0.9862 | 0.9978 | 0.9387 | 0.9429 | 0.9943 | 0.8760 | 0.9068 |
| 0.0276 | 39.3939 | 1300 | 0.0388 | 0.9269 | 0.9590 | 0.9864 | 0.9981 | 0.9267 | 0.9522 | 0.9942 | 0.8772 | 0.9093 |
| 0.0286 | 40.0 | 1320 | 0.0395 | 0.9248 | 0.9572 | 0.9861 | 0.9979 | 0.9082 | 0.9655 | 0.9944 | 0.8723 | 0.9076 |
| 0.0298 | 40.6061 | 1340 | 0.0391 | 0.9263 | 0.9592 | 0.9863 | 0.9977 | 0.9212 | 0.9587 | 0.9944 | 0.8759 | 0.9087 |
| 0.0235 | 41.2121 | 1360 | 0.0389 | 0.9262 | 0.9590 | 0.9863 | 0.9978 | 0.9220 | 0.9574 | 0.9944 | 0.8757 | 0.9085 |
| 0.0223 | 41.8182 | 1380 | 0.0392 | 0.9265 | 0.9593 | 0.9863 | 0.9979 | 0.9273 | 0.9528 | 0.9943 | 0.8765 | 0.9088 |
| 0.0216 | 42.4242 | 1400 | 0.0390 | 0.9264 | 0.9592 | 0.9863 | 0.9979 | 0.9265 | 0.9531 | 0.9943 | 0.8761 | 0.9086 |
| 0.027 | 43.0303 | 1420 | 0.0395 | 0.9264 | 0.9601 | 0.9863 | 0.9976 | 0.9315 | 0.9511 | 0.9944 | 0.8764 | 0.9083 |
| 0.0261 | 43.6364 | 1440 | 0.0392 | 0.9265 | 0.9593 | 0.9863 | 0.9980 | 0.9309 | 0.9491 | 0.9943 | 0.8768 | 0.9083 |
| 0.0213 | 44.2424 | 1460 | 0.0390 | 0.9262 | 0.9592 | 0.9863 | 0.9977 | 0.9213 | 0.9584 | 0.9944 | 0.8756 | 0.9087 |
| 0.0228 | 44.8485 | 1480 | 0.0390 | 0.9260 | 0.9596 | 0.9863 | 0.9976 | 0.9240 | 0.9571 | 0.9944 | 0.8756 | 0.9081 |
| 0.0317 | 45.4545 | 1500 | 0.0391 | 0.9259 | 0.9584 | 0.9862 | 0.9980 | 0.9227 | 0.9544 | 0.9942 | 0.8751 | 0.9082 |
| 0.0244 | 46.0606 | 1520 | 0.0392 | 0.9261 | 0.9591 | 0.9863 | 0.9979 | 0.9274 | 0.9521 | 0.9943 | 0.8759 | 0.9081 |
| 0.0282 | 46.6667 | 1540 | 0.0391 | 0.9259 | 0.9589 | 0.9862 | 0.9978 | 0.9224 | 0.9564 | 0.9944 | 0.8750 | 0.9082 |
| 0.0244 | 47.2727 | 1560 | 0.0397 | 0.9262 | 0.9592 | 0.9863 | 0.9979 | 0.9280 | 0.9519 | 0.9944 | 0.8760 | 0.9081 |
| 0.0265 | 47.8788 | 1580 | 0.0393 | 0.9258 | 0.9592 | 0.9862 | 0.9977 | 0.9226 | 0.9572 | 0.9944 | 0.8751 | 0.9080 |
| 0.0282 | 48.4848 | 1600 | 0.0394 | 0.9260 | 0.9585 | 0.9863 | 0.9980 | 0.9209 | 0.9567 | 0.9943 | 0.8752 | 0.9084 |
| 0.0229 | 49.0909 | 1620 | 0.0390 | 0.9262 | 0.9592 | 0.9863 | 0.9979 | 0.9281 | 0.9517 | 0.9943 | 0.8760 | 0.9083 |
| 0.0236 | 49.6970 | 1640 | 0.0391 | 0.9261 | 0.9594 | 0.9863 | 0.9977 | 0.9268 | 0.9537 | 0.9944 | 0.8758 | 0.9082 |
### Framework versions
- Transformers 4.44.1
- Pytorch 2.6.0+cpu
- Datasets 2.21.0
- Tokenizers 0.19.1
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