transformers tensorboard safetensors segformer vision image-segmentation generated_from_trainer base_model:peldrak/segformer-b5-cityscapes-finetuned-coastTrain license:other endpoints_compatible region:us
---
license: other
base_model: peldrak/segformer-b5-cityscapes-finetuned-coastTrain
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b5-cityscapes-finetuned-coastTrain-grCoastline
  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-b5-cityscapes-finetuned-coastTrain-grCoastline

This model is a fine-tuned version of [peldrak/segformer-b5-cityscapes-finetuned-coastTrain](https://huggingface.co/peldrak/segformer-b5-cityscapes-finetuned-coastTrain) on the peldrak/grCoastline_512 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2369
- Mean Iou: 0.7581
- Mean Accuracy: 0.8319
- Overall Accuracy: 0.9386
- Accuracy Water: 0.9821
- Accuracy Whitewater: 0.4902
- Accuracy Sediment: 0.9136
- Accuracy Other Natural Terrain: 0.8026
- Accuracy Vegetation: 0.9297
- Accuracy Development: 0.7063
- Accuracy Unknown: 0.9989
- Iou Water: 0.9520
- Iou Whitewater: 0.3507
- Iou Sediment: 0.8649
- Iou Other Natural Terrain: 0.6679
- Iou Vegetation: 0.8298
- Iou Development: 0.6457
- Iou Unknown: 0.9956
- F1 Score: 0.9379

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------:|:-------------------:|:-----------------:|:------------------------------:|:-------------------:|:--------------------:|:----------------:|:---------:|:--------------:|:------------:|:-------------------------:|:--------------:|:---------------:|:-----------:|:--------:|
| 0.4436        | 0.24  | 20   | 0.3559          | 0.6026   | 0.6838        | 0.8880           | 0.9773         | 0.0337              | 0.9374            | 0.5772                         | 0.8436              | 0.4204               | 0.9972           | 0.8777    | 0.0293         | 0.7012       | 0.4913                    | 0.7446         | 0.3805          | 0.9937      | 0.8816   |
| 0.3897        | 0.49  | 40   | 0.2428          | 0.6524   | 0.7222        | 0.9165           | 0.9825         | 0.0                 | 0.9378            | 0.7357                         | 0.8910              | 0.5144               | 0.9944           | 0.9418    | 0.0            | 0.7760       | 0.5956                    | 0.8037         | 0.4564          | 0.9931      | 0.9134   |
| 0.5041        | 0.73  | 60   | 0.2645          | 0.6562   | 0.7196        | 0.9172           | 0.9864         | 0.0587              | 0.9317            | 0.6634                         | 0.9456              | 0.4577               | 0.9934           | 0.9407    | 0.0581         | 0.7808       | 0.5880                    | 0.8037         | 0.4299          | 0.9922      | 0.9118   |
| 0.1355        | 0.98  | 80   | 0.1992          | 0.7084   | 0.7729        | 0.9324           | 0.9855         | 0.1154              | 0.9117            | 0.8215                         | 0.8980              | 0.6808               | 0.9974           | 0.9470    | 0.1086         | 0.8482       | 0.6539                    | 0.8245         | 0.5821          | 0.9943      | 0.9316   |
| 0.1142        | 1.22  | 100  | 0.2597          | 0.6630   | 0.7299        | 0.9220           | 0.9852         | 0.0279              | 0.9498            | 0.8028                         | 0.8860              | 0.4611               | 0.9965           | 0.9489    | 0.0278         | 0.7668       | 0.6533                    | 0.8202         | 0.4298          | 0.9943      | 0.9184   |
| 0.2346        | 1.46  | 120  | 0.2670          | 0.6708   | 0.7331        | 0.9239           | 0.9823         | 0.0530              | 0.9331            | 0.7716                         | 0.9238              | 0.4729               | 0.9953           | 0.9497    | 0.0524         | 0.8044       | 0.6352                    | 0.8128         | 0.4478          | 0.9936      | 0.9201   |
| 0.4209        | 1.71  | 140  | 0.1952          | 0.7291   | 0.7955        | 0.9336           | 0.9688         | 0.2746              | 0.9536            | 0.8644                         | 0.8830              | 0.6252               | 0.9989           | 0.9485    | 0.2476         | 0.8375       | 0.6754                    | 0.8291         | 0.5719          | 0.9939      | 0.9328   |
| 0.0803        | 1.95  | 160  | 0.2460          | 0.6772   | 0.7440        | 0.9228           | 0.9824         | 0.0952              | 0.9514            | 0.7835                         | 0.8898              | 0.5101               | 0.9958           | 0.9458    | 0.0937         | 0.7832       | 0.6355                    | 0.8190         | 0.4692          | 0.9943      | 0.9200   |
| 0.3305        | 2.2   | 180  | 0.2127          | 0.7372   | 0.7992        | 0.9381           | 0.9869         | 0.1967              | 0.9330            | 0.7088                         | 0.9337              | 0.8417               | 0.9935           | 0.9463    | 0.1844         | 0.8578       | 0.6514                    | 0.8284         | 0.6996          | 0.9928      | 0.9366   |
| 0.1355        | 2.44  | 200  | 0.1968          | 0.7219   | 0.7768        | 0.9387           | 0.9877         | 0.0983              | 0.9309            | 0.7413                         | 0.9411              | 0.7414               | 0.9971           | 0.9480    | 0.0963         | 0.8611       | 0.6629                    | 0.8333         | 0.6575          | 0.9941      | 0.9370   |
| 0.0807        | 2.68  | 220  | 0.2531          | 0.6939   | 0.7569        | 0.9273           | 0.9826         | 0.1709              | 0.9534            | 0.7590                         | 0.9194              | 0.5160               | 0.9969           | 0.9520    | 0.1628         | 0.8076       | 0.6326                    | 0.8290         | 0.4785          | 0.9950      | 0.9242   |
| 0.1226        | 2.93  | 240  | 0.2434          | 0.7382   | 0.8081        | 0.9315           | 0.9832         | 0.3932              | 0.9090            | 0.7441                         | 0.9272              | 0.7026               | 0.9976           | 0.9340    | 0.3119         | 0.8604       | 0.6199                    | 0.8192         | 0.6276          | 0.9947      | 0.9303   |
| 0.0681        | 3.17  | 260  | 0.2265          | 0.7529   | 0.8220        | 0.9387           | 0.9802         | 0.3786              | 0.9371            | 0.7742                         | 0.9194              | 0.7668               | 0.9974           | 0.9506    | 0.3042         | 0.8661       | 0.6614                    | 0.8315         | 0.6617          | 0.9950      | 0.9380   |
| 0.1304        | 3.41  | 280  | 0.2342          | 0.7360   | 0.8009        | 0.9348           | 0.9772         | 0.3403              | 0.9507            | 0.7835                         | 0.9220              | 0.6358               | 0.9971           | 0.9486    | 0.2864         | 0.8471       | 0.6572                    | 0.8302         | 0.5880          | 0.9947      | 0.9333   |
| 0.1353        | 3.66  | 300  | 0.1970          | 0.7426   | 0.8071        | 0.9400           | 0.9803         | 0.2770              | 0.9285            | 0.8866                         | 0.8962              | 0.6822               | 0.9987           | 0.9508    | 0.2259         | 0.8732       | 0.6883                    | 0.8370         | 0.6278          | 0.9954      | 0.9397   |
| 0.3968        | 3.9   | 320  | 0.2181          | 0.7551   | 0.8214        | 0.9389           | 0.9868         | 0.3918              | 0.9280            | 0.7945                         | 0.9160              | 0.7343               | 0.9982           | 0.9512    | 0.3204         | 0.8645       | 0.6646                    | 0.8297         | 0.6594          | 0.9962      | 0.9381   |
| 0.0548        | 4.15  | 340  | 0.2025          | 0.7645   | 0.8313        | 0.9411           | 0.9804         | 0.4091              | 0.9287            | 0.7892                         | 0.9208              | 0.7920               | 0.9987           | 0.9525    | 0.3393         | 0.8686       | 0.6729                    | 0.8347         | 0.6878          | 0.9956      | 0.9406   |
| 0.0653        | 4.39  | 360  | 0.2549          | 0.7399   | 0.8105        | 0.9327           | 0.9851         | 0.4396              | 0.9222            | 0.8119                         | 0.9144              | 0.6029               | 0.9976           | 0.9528    | 0.3534         | 0.8455       | 0.6479                    | 0.8239         | 0.5602          | 0.9957      | 0.9314   |
| 0.1244        | 4.63  | 380  | 0.2580          | 0.7216   | 0.7821        | 0.9336           | 0.9925         | 0.2673              | 0.9136            | 0.7674                         | 0.9405              | 0.5951               | 0.9984           | 0.9465    | 0.2327         | 0.8327       | 0.6598                    | 0.8338         | 0.5501          | 0.9957      | 0.9312   |
| 0.2298        | 4.88  | 400  | 0.2345          | 0.7441   | 0.8112        | 0.9368           | 0.9760         | 0.2900              | 0.9511            | 0.8680                         | 0.8716              | 0.7250               | 0.9965           | 0.9520    | 0.2585         | 0.8639       | 0.6659                    | 0.8229         | 0.6497          | 0.9956      | 0.9369   |
| 0.0469        | 5.12  | 420  | 0.2614          | 0.7131   | 0.7813        | 0.9279           | 0.9854         | 0.3576              | 0.9420            | 0.8114                         | 0.9099              | 0.4639               | 0.9986           | 0.9534    | 0.3075         | 0.8081       | 0.6597                    | 0.8237         | 0.4432          | 0.9957      | 0.9244   |
| 0.1398        | 5.37  | 440  | 0.2542          | 0.7344   | 0.8077        | 0.9318           | 0.9851         | 0.4151              | 0.9388            | 0.8538                         | 0.8842              | 0.5789               | 0.9979           | 0.9561    | 0.3381         | 0.8258       | 0.6665                    | 0.8241         | 0.5345          | 0.9957      | 0.9305   |
| 0.0683        | 5.61  | 460  | 0.2496          | 0.7472   | 0.8213        | 0.9365           | 0.9856         | 0.5096              | 0.9419            | 0.8014                         | 0.9301              | 0.5823               | 0.9980           | 0.9569    | 0.3788         | 0.8228       | 0.6847                    | 0.8445         | 0.5467          | 0.9961      | 0.9346   |
| 0.141         | 5.85  | 480  | 0.2251          | 0.7514   | 0.8174        | 0.9393           | 0.9873         | 0.3664              | 0.9389            | 0.8465                         | 0.8977              | 0.6867               | 0.9982           | 0.9559    | 0.3151         | 0.8544       | 0.6856                    | 0.8387         | 0.6140          | 0.9962      | 0.9387   |
| 0.2161        | 6.1   | 500  | 0.2369          | 0.7581   | 0.8319        | 0.9386           | 0.9821         | 0.4902              | 0.9136            | 0.8026                         | 0.9297              | 0.7063               | 0.9989           | 0.9520    | 0.3507         | 0.8649       | 0.6679                    | 0.8298         | 0.6457          | 0.9956      | 0.9379   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
