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

This model is a fine-tuned version of [peldrak/segformer-b5-ade-finetuned-coastTrain](https://huggingface.co/peldrak/segformer-b5-ade-finetuned-coastTrain) on the peldrak/grCoastline_512 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1862
- Mean Iou: 0.7261
- Mean Accuracy: 0.7941
- Overall Accuracy: 0.9457
- Accuracy Water: 0.9892
- Accuracy Whitewater: 0.1212
- Accuracy Sediment: 0.8832
- Accuracy Other Natural Terrain: 0.9089
- Accuracy Vegetation: 0.8620
- Accuracy Development: 0.7955
- Accuracy Unknown: 0.9987
- Iou Water: 0.9551
- Iou Whitewater: 0.1179
- Iou Sediment: 0.8407
- Iou Other Natural Terrain: 0.7579
- Iou Vegetation: 0.8186
- Iou Development: 0.5970
- Iou Unknown: 0.9957
- F1 Score: 0.9457

## 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: 20

### 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------:|:-------------------:|:-----------------:|:------------------------------:|:-------------------:|:--------------------:|:----------------:|:---------:|:--------------:|:------------:|:-------------------------:|:--------------:|:---------------:|:-----------:|:--------:|
| 0.3949        | 0.24  | 20   | 0.4674          | 0.5533   | 0.6548        | 0.8647           | 0.9629         | 0.0                 | 0.8258            | 0.3380                         | 0.8635              | 0.5954               | 0.9980           | 0.8563    | 0.0            | 0.5989       | 0.2978                    | 0.6772         | 0.4600          | 0.9826      | 0.8527   |
| 0.3836        | 0.49  | 40   | 0.3509          | 0.6135   | 0.6996        | 0.8983           | 0.9860         | 0.0                 | 0.9063            | 0.4811                         | 0.8910              | 0.6351               | 0.9974           | 0.9202    | 0.0            | 0.7089       | 0.4491                    | 0.6990         | 0.5252          | 0.9922      | 0.8914   |
| 0.4461        | 0.73  | 60   | 0.2453          | 0.6595   | 0.7407        | 0.9222           | 0.9948         | 0.0                 | 0.8439            | 0.8332                         | 0.8203              | 0.6988               | 0.9937           | 0.9202    | 0.0            | 0.7836       | 0.6604                    | 0.7620         | 0.4984          | 0.9916      | 0.9219   |
| 0.7886        | 0.98  | 80   | 0.2794          | 0.6594   | 0.7302        | 0.9222           | 0.9841         | 0.0004              | 0.8601            | 0.6668                         | 0.9358              | 0.6682               | 0.9962           | 0.9314    | 0.0004         | 0.8039       | 0.6086                    | 0.7510         | 0.5271          | 0.9931      | 0.9198   |
| 0.2695        | 1.22  | 100  | 0.2217          | 0.6871   | 0.7557        | 0.9326           | 0.9879         | 0.0                 | 0.9150            | 0.7878                         | 0.8622              | 0.7392               | 0.9978           | 0.9159    | 0.0            | 0.8153       | 0.7031                    | 0.7691         | 0.6121          | 0.9946      | 0.9311   |
| 0.2343        | 1.46  | 120  | 0.2122          | 0.6772   | 0.7477        | 0.9312           | 0.9894         | 0.0001              | 0.9146            | 0.8691                         | 0.8144              | 0.6484               | 0.9975           | 0.9315    | 0.0001         | 0.7897       | 0.7006                    | 0.7760         | 0.5482          | 0.9943      | 0.9300   |
| 0.1973        | 1.71  | 140  | 0.1803          | 0.6962   | 0.7646        | 0.9392           | 0.9769         | 0.0052              | 0.9011            | 0.8906                         | 0.8519              | 0.7277               | 0.9988           | 0.9530    | 0.0052         | 0.8240       | 0.7305                    | 0.7956         | 0.5717          | 0.9932      | 0.9387   |
| 0.2983        | 1.95  | 160  | 0.1978          | 0.6927   | 0.7630        | 0.9372           | 0.9918         | 0.0                 | 0.9197            | 0.8532                         | 0.8443              | 0.7362               | 0.9955           | 0.9476    | 0.0            | 0.8177       | 0.7287                    | 0.7781         | 0.5832          | 0.9936      | 0.9363   |
| 0.1164        | 2.2   | 180  | 0.2010          | 0.6933   | 0.7540        | 0.9368           | 0.9880         | 0.0150              | 0.8760            | 0.8708                         | 0.8652              | 0.6641               | 0.9990           | 0.9438    | 0.0150         | 0.8319       | 0.7074                    | 0.7900         | 0.5732          | 0.9916      | 0.9357   |
| 0.1998        | 2.44  | 200  | 0.1988          | 0.6920   | 0.7694        | 0.9365           | 0.9824         | 0.0186              | 0.8837            | 0.9011                         | 0.8253              | 0.7768               | 0.9977           | 0.9502    | 0.0186         | 0.8128       | 0.7331                    | 0.7836         | 0.5517          | 0.9941      | 0.9365   |
| 0.5358        | 2.68  | 220  | 0.1884          | 0.6989   | 0.7633        | 0.9392           | 0.9887         | 0.0322              | 0.8630            | 0.8721                         | 0.8830              | 0.7074               | 0.9969           | 0.9521    | 0.0322         | 0.8189       | 0.7330                    | 0.7929         | 0.5683          | 0.9948      | 0.9386   |
| 0.184         | 2.93  | 240  | 0.2723          | 0.6598   | 0.7425        | 0.9222           | 0.9888         | 0.0024              | 0.8640            | 0.6604                         | 0.9037              | 0.7791               | 0.9990           | 0.9246    | 0.0024         | 0.7290       | 0.6206                    | 0.7797         | 0.5689          | 0.9936      | 0.9198   |
| 0.1789        | 3.17  | 260  | 0.3020          | 0.6541   | 0.7355        | 0.9089           | 0.9738         | 0.0623              | 0.8362            | 0.9736                         | 0.6716              | 0.6330               | 0.9981           | 0.9485    | 0.0620         | 0.7995       | 0.6046                    | 0.6513         | 0.5177          | 0.9953      | 0.9099   |
| 0.1925        | 3.41  | 280  | 0.1866          | 0.7052   | 0.7741        | 0.9420           | 0.9869         | 0.0404              | 0.8583            | 0.8487                         | 0.9004              | 0.7852               | 0.9990           | 0.9463    | 0.0404         | 0.8083       | 0.7554                    | 0.8171         | 0.5749          | 0.9943      | 0.9416   |
| 0.1533        | 3.66  | 300  | 0.1827          | 0.7119   | 0.7673        | 0.9460           | 0.9870         | 0.0374              | 0.8885            | 0.8771                         | 0.9152              | 0.6690               | 0.9968           | 0.9497    | 0.0374         | 0.8259       | 0.7684                    | 0.8228         | 0.5836          | 0.9951      | 0.9448   |
| 0.3405        | 3.9   | 320  | 0.1840          | 0.7068   | 0.7791        | 0.9420           | 0.9918         | 0.0417              | 0.8530            | 0.9050                         | 0.8582              | 0.8061               | 0.9978           | 0.9467    | 0.0416         | 0.8163       | 0.7590                    | 0.8089         | 0.5793          | 0.9955      | 0.9419   |
| 0.1095        | 4.15  | 340  | 0.1938          | 0.7142   | 0.7842        | 0.9419           | 0.9842         | 0.1098              | 0.8741            | 0.9043                         | 0.8602              | 0.7577               | 0.9989           | 0.9536    | 0.1080         | 0.8306       | 0.7499                    | 0.8076         | 0.5549          | 0.9949      | 0.9420   |
| 0.0942        | 4.39  | 360  | 0.2193          | 0.7139   | 0.7905        | 0.9384           | 0.9785         | 0.1433              | 0.8578            | 0.8932                         | 0.8522              | 0.8094               | 0.9987           | 0.9456    | 0.1394         | 0.8182       | 0.7408                    | 0.7945         | 0.5640          | 0.9947      | 0.9388   |
| 0.151         | 4.63  | 380  | 0.1964          | 0.7189   | 0.7915        | 0.9388           | 0.9826         | 0.1692              | 0.8619            | 0.8826                         | 0.8601              | 0.7854               | 0.9983           | 0.9491    | 0.1609         | 0.8171       | 0.7329                    | 0.7912         | 0.5858          | 0.9950      | 0.9388   |
| 0.1181        | 4.88  | 400  | 0.2256          | 0.7023   | 0.7752        | 0.9370           | 0.9880         | 0.1247              | 0.8074            | 0.8731                         | 0.8893              | 0.7453               | 0.9988           | 0.9505    | 0.1227         | 0.7869       | 0.7375                    | 0.8042         | 0.5191          | 0.9953      | 0.9370   |
| 0.0898        | 5.12  | 420  | 0.2061          | 0.7193   | 0.7950        | 0.9429           | 0.9908         | 0.1206              | 0.8387            | 0.8846                         | 0.8758              | 0.8559               | 0.9983           | 0.9504    | 0.1163         | 0.8109       | 0.7627                    | 0.8149         | 0.5839          | 0.9961      | 0.9432   |
| 0.1225        | 5.37  | 440  | 0.1905          | 0.7361   | 0.8013        | 0.9460           | 0.9887         | 0.1963              | 0.8653            | 0.9102                         | 0.8772              | 0.7726               | 0.9991           | 0.9502    | 0.1790         | 0.8365       | 0.7638                    | 0.8197         | 0.6085          | 0.9953      | 0.9458   |
| 0.1501        | 5.61  | 460  | 0.1883          | 0.7325   | 0.7938        | 0.9453           | 0.9921         | 0.1697              | 0.8818            | 0.9120                         | 0.8677              | 0.7350               | 0.9983           | 0.9480    | 0.1599         | 0.8421       | 0.7570                    | 0.8113         | 0.6134          | 0.9960      | 0.9448   |
| 0.0686        | 5.85  | 480  | 0.2161          | 0.7313   | 0.8038        | 0.9429           | 0.9870         | 0.2042              | 0.8679            | 0.8909                         | 0.8651              | 0.8126               | 0.9987           | 0.9538    | 0.1884         | 0.8378       | 0.7427                    | 0.8065         | 0.5939          | 0.9960      | 0.9432   |
| 0.166         | 6.1   | 500  | 0.2229          | 0.7250   | 0.7891        | 0.9438           | 0.9887         | 0.1570              | 0.8673            | 0.8510                         | 0.9086              | 0.7524               | 0.9985           | 0.9540    | 0.1485         | 0.8359       | 0.7417                    | 0.8132         | 0.5857          | 0.9959      | 0.9434   |
| 0.1168        | 6.34  | 520  | 0.2215          | 0.7207   | 0.7956        | 0.9412           | 0.9911         | 0.1826              | 0.8410            | 0.9082                         | 0.8622              | 0.7868               | 0.9976           | 0.9508    | 0.1697         | 0.8113       | 0.7493                    | 0.8156         | 0.5523          | 0.9959      | 0.9416   |
| 0.1935        | 6.59  | 540  | 0.1862          | 0.7261   | 0.7941        | 0.9457           | 0.9892         | 0.1212              | 0.8832            | 0.9089                         | 0.8620              | 0.7955               | 0.9987           | 0.9551    | 0.1179         | 0.8407       | 0.7579                    | 0.8186         | 0.5970          | 0.9957      | 0.9457   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.1
