transformers tensorboard safetensors segformer vision image-segmentation generated_from_trainer base_model:peldrak/segformer-b4-cityscapes-finetuned-coastTrain license:other endpoints_compatible region:us
---
license: other
base_model: peldrak/segformer-b4-cityscapes-finetuned-coastTrain
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b4-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-b4-cityscapes-finetuned-coastTrain-grCoastline

This model is a fine-tuned version of [peldrak/segformer-b4-cityscapes-finetuned-coastTrain](https://huggingface.co/peldrak/segformer-b4-cityscapes-finetuned-coastTrain) on the peldrak/grCoastline_512 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2751
- Mean Iou: 0.7477
- Mean Accuracy: 0.8306
- Overall Accuracy: 0.9274
- Accuracy Water: 0.9618
- Accuracy Whitewater: 0.5458
- Accuracy Sediment: 0.9189
- Accuracy Other Natural Terrain: 0.6111
- Accuracy Vegetation: 0.9584
- Accuracy Development: 0.8193
- Accuracy Unknown: 0.9989
- Iou Water: 0.9317
- Iou Whitewater: 0.4264
- Iou Sediment: 0.7904
- Iou Other Natural Terrain: 0.5618
- Iou Vegetation: 0.8457
- Iou Development: 0.6820
- Iou Unknown: 0.9958
- F1 Score: 0.9247

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------:|:-------------------:|:-----------------:|:------------------------------:|:-------------------:|:--------------------:|:----------------:|:---------:|:--------------:|:------------:|:-------------------------:|:--------------:|:---------------:|:-----------:|:--------:|
| 0.2133        | 0.24  | 20   | 0.5121          | 0.5418   | 0.6551        | 0.8537           | 0.9585         | 0.0                 | 0.8618            | 0.0673                         | 0.9007              | 0.7998               | 0.9976           | 0.9023    | 0.0            | 0.6459       | 0.0662                    | 0.7036         | 0.4840          | 0.9902      | 0.8244   |
| 0.414         | 0.49  | 40   | 0.3762          | 0.6200   | 0.7083        | 0.8876           | 0.9715         | 0.0                 | 0.8827            | 0.6187                         | 0.8259              | 0.6633               | 0.9959           | 0.9246    | 0.0            | 0.7128       | 0.4398                    | 0.7463         | 0.5240          | 0.9926      | 0.8868   |
| 0.1269        | 0.73  | 60   | 0.4382          | 0.5881   | 0.6925        | 0.8750           | 0.9318         | 0.0009              | 0.8038            | 0.2996                         | 0.9384              | 0.8817               | 0.9916           | 0.8967    | 0.0009         | 0.6716       | 0.2920                    | 0.7370         | 0.5281          | 0.9905      | 0.8642   |
| 0.1997        | 0.98  | 80   | 0.3072          | 0.6505   | 0.7324        | 0.9091           | 0.9761         | 0.0012              | 0.8633            | 0.5977                         | 0.9144              | 0.7777               | 0.9963           | 0.9201    | 0.0012         | 0.7241       | 0.5213                    | 0.8180         | 0.5755          | 0.9932      | 0.9063   |
| 0.1083        | 1.22  | 100  | 0.3962          | 0.6172   | 0.6949        | 0.8968           | 0.9637         | 0.0008              | 0.9391            | 0.4493                         | 0.9514              | 0.5660               | 0.9938           | 0.9245    | 0.0008         | 0.6964       | 0.4157                    | 0.7968         | 0.4937          | 0.9928      | 0.8887   |
| 0.3105        | 1.46  | 120  | 0.2904          | 0.6512   | 0.7371        | 0.8982           | 0.9807         | 0.0948              | 0.9006            | 0.7090                         | 0.8154              | 0.6621               | 0.9971           | 0.9235    | 0.0936         | 0.7400       | 0.4954                    | 0.7695         | 0.5415          | 0.9947      | 0.8983   |
| 0.2026        | 1.71  | 140  | 0.3171          | 0.6590   | 0.7377        | 0.9117           | 0.9627         | 0.0314              | 0.9322            | 0.5886                         | 0.9180              | 0.7359               | 0.9952           | 0.9374    | 0.0308         | 0.7378       | 0.5309                    | 0.8117         | 0.5706          | 0.9935      | 0.9089   |
| 0.1502        | 1.95  | 160  | 0.2682          | 0.6830   | 0.7555        | 0.9097           | 0.9747         | 0.2278              | 0.8771            | 0.5280                         | 0.9490              | 0.7334               | 0.9984           | 0.9210    | 0.2170         | 0.7785       | 0.4686                    | 0.7951         | 0.6075          | 0.9934      | 0.9048   |
| 0.0935        | 2.2   | 180  | 0.3351          | 0.6378   | 0.7209        | 0.9009           | 0.9776         | 0.0421              | 0.9416            | 0.7188                         | 0.8390              | 0.5301               | 0.9967           | 0.9143    | 0.0421         | 0.6865       | 0.5566                    | 0.8033         | 0.4677          | 0.9940      | 0.8991   |
| 0.2849        | 2.44  | 200  | 0.2994          | 0.6750   | 0.7469        | 0.9177           | 0.9675         | 0.0987              | 0.9478            | 0.5966                         | 0.9442              | 0.6781               | 0.9954           | 0.9286    | 0.0931         | 0.7319       | 0.5570                    | 0.8430         | 0.5768          | 0.9943      | 0.9142   |
| 0.4015        | 2.68  | 220  | 0.3270          | 0.6682   | 0.7424        | 0.9058           | 0.9778         | 0.1729              | 0.8825            | 0.4336                         | 0.9693              | 0.7683               | 0.9924           | 0.9117    | 0.1667         | 0.7556       | 0.4112                    | 0.7914         | 0.6490          | 0.9917      | 0.8978   |
| 0.236         | 2.93  | 240  | 0.3329          | 0.6715   | 0.7520        | 0.9093           | 0.9707         | 0.1421              | 0.9684            | 0.6999                         | 0.8499              | 0.6351               | 0.9981           | 0.9231    | 0.1363         | 0.7081       | 0.5718                    | 0.8119         | 0.5550          | 0.9941      | 0.9083   |
| 0.0648        | 3.17  | 260  | 0.2652          | 0.6981   | 0.7843        | 0.9186           | 0.9715         | 0.1933              | 0.8879            | 0.7052                         | 0.8762              | 0.8578               | 0.9983           | 0.9202    | 0.1728         | 0.7617       | 0.5836                    | 0.8319         | 0.6221          | 0.9942      | 0.9184   |
| 0.1835        | 3.41  | 280  | 0.2945          | 0.6778   | 0.7568        | 0.9165           | 0.9734         | 0.0494              | 0.9337            | 0.6959                         | 0.8648              | 0.7820               | 0.9986           | 0.9185    | 0.0483         | 0.7555       | 0.5665                    | 0.8205         | 0.6412          | 0.9942      | 0.9154   |
| 0.0845        | 3.66  | 300  | 0.3184          | 0.6904   | 0.7687        | 0.9124           | 0.9741         | 0.2469              | 0.9595            | 0.6890                         | 0.8701              | 0.6442               | 0.9969           | 0.9117    | 0.2429         | 0.7297       | 0.5577                    | 0.8332         | 0.5628          | 0.9949      | 0.9112   |
| 0.1369        | 3.9   | 320  | 0.2729          | 0.7262   | 0.8066        | 0.9229           | 0.9706         | 0.3939              | 0.9080            | 0.5670                         | 0.9483              | 0.8607               | 0.9976           | 0.9268    | 0.3526         | 0.7736       | 0.5358                    | 0.8440         | 0.6550          | 0.9954      | 0.9195   |
| 0.2455        | 4.15  | 340  | 0.2923          | 0.7087   | 0.7941        | 0.9148           | 0.9687         | 0.3314              | 0.9364            | 0.7874                         | 0.8373              | 0.6999               | 0.9978           | 0.9457    | 0.2815         | 0.7742       | 0.5592                    | 0.8056         | 0.5992          | 0.9954      | 0.9160   |
| 0.1555        | 4.39  | 360  | 0.2976          | 0.6953   | 0.7665        | 0.9227           | 0.9694         | 0.1557              | 0.9383            | 0.6031                         | 0.9438              | 0.7572               | 0.9977           | 0.9260    | 0.1480         | 0.7761       | 0.5530                    | 0.8467         | 0.6235          | 0.9939      | 0.9194   |
| 0.1789        | 4.63  | 380  | 0.2856          | 0.7085   | 0.7802        | 0.9229           | 0.9717         | 0.2405              | 0.9347            | 0.6306                         | 0.9315              | 0.7538               | 0.9983           | 0.9227    | 0.2238         | 0.7697       | 0.5606                    | 0.8466         | 0.6410          | 0.9948      | 0.9202   |
| 0.1023        | 4.88  | 400  | 0.2929          | 0.7024   | 0.7723        | 0.9217           | 0.9639         | 0.2536              | 0.9496            | 0.6680                         | 0.9365              | 0.6356               | 0.9988           | 0.9294    | 0.2279         | 0.7536       | 0.5796                    | 0.8489         | 0.5825          | 0.9951      | 0.9191   |
| 0.1112        | 5.12  | 420  | 0.3065          | 0.7011   | 0.7720        | 0.9210           | 0.9812         | 0.1859              | 0.9282            | 0.6461                         | 0.9172              | 0.7497               | 0.9955           | 0.9220    | 0.1800         | 0.7803       | 0.5507                    | 0.8348         | 0.6454          | 0.9944      | 0.9187   |
| 0.1932        | 5.37  | 440  | 0.3091          | 0.7137   | 0.7938        | 0.9183           | 0.9588         | 0.3565              | 0.9580            | 0.6726                         | 0.8990              | 0.7139               | 0.9980           | 0.9241    | 0.3106         | 0.7708       | 0.5589                    | 0.8277         | 0.6077          | 0.9960      | 0.9170   |
| 0.092         | 5.61  | 460  | 0.3078          | 0.7082   | 0.7831        | 0.9188           | 0.9659         | 0.2639              | 0.9494            | 0.6480                         | 0.9015              | 0.7550               | 0.9979           | 0.9312    | 0.2488         | 0.7690       | 0.5543                    | 0.8162         | 0.6422          | 0.9957      | 0.9170   |
| 0.0515        | 5.85  | 480  | 0.3024          | 0.7363   | 0.8322        | 0.9208           | 0.9660         | 0.5072              | 0.9229            | 0.7492                         | 0.8596              | 0.8222               | 0.9980           | 0.9318    | 0.3939         | 0.7716       | 0.5899                    | 0.8228         | 0.6482          | 0.9959      | 0.9213   |
| 0.1004        | 6.1   | 500  | 0.3174          | 0.7201   | 0.7917        | 0.9265           | 0.9707         | 0.2714              | 0.9527            | 0.5768                         | 0.9471              | 0.8254               | 0.9976           | 0.9234    | 0.2468         | 0.7821       | 0.5443                    | 0.8508         | 0.6974          | 0.9958      | 0.9228   |
| 0.0747        | 6.34  | 520  | 0.3035          | 0.7158   | 0.7896        | 0.9233           | 0.9645         | 0.3336              | 0.9640            | 0.6184                         | 0.9394              | 0.7088               | 0.9987           | 0.9279    | 0.2958         | 0.7659       | 0.5631                    | 0.8517         | 0.6106          | 0.9958      | 0.9204   |
| 0.205         | 6.59  | 540  | 0.2899          | 0.7245   | 0.8015        | 0.9234           | 0.9788         | 0.3345              | 0.9541            | 0.7218                         | 0.8790              | 0.7447               | 0.9977           | 0.9340    | 0.3038         | 0.7685       | 0.5897                    | 0.8380         | 0.6410          | 0.9961      | 0.9228   |
| 0.0729        | 6.83  | 560  | 0.2751          | 0.7477   | 0.8306        | 0.9274           | 0.9618         | 0.5458              | 0.9189            | 0.6111                         | 0.9584              | 0.8193               | 0.9989           | 0.9317    | 0.4264         | 0.7904       | 0.5618                    | 0.8457         | 0.6820          | 0.9958      | 0.9247   |


### Framework versions

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