---
license: other
base_model: nvidia/segformer-b1-finetuned-ade-512-512
tags:
- vision
- image-segmentation
- generated_from_trainer
metrics:
- precision
model-index:
- name: segformer-b1-finetuned-segments-pv
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mouadn773/huggingface/runs/lyupah0l)
# segformer-b1-finetuned-segments-pv

This model is a fine-tuned version of [nvidia/segformer-b1-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b1-finetuned-ade-512-512) on the mouadenna/satellite_PV_dataset_train_test dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0192
- Mean Iou: 0.8631
- Precision: 0.9304

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Mean Iou | Precision |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|
| 0.0051        | 1.0   | 3666   | 0.0084          | 0.8064   | 0.8864    |
| 0.0038        | 2.0   | 7332   | 0.0115          | 0.7607   | 0.9338    |
| 0.0001        | 3.0   | 10998  | 0.0089          | 0.8145   | 0.9115    |
| 0.0           | 4.0   | 14664  | 0.0078          | 0.8317   | 0.9063    |
| 0.0           | 5.0   | 18330  | 0.0093          | 0.8078   | 0.9244    |
| 0.0017        | 6.0   | 21996  | 0.0080          | 0.8370   | 0.9203    |
| 0.0019        | 7.0   | 25662  | 0.0085          | 0.8395   | 0.9163    |
| 0.0001        | 8.0   | 29328  | 0.0099          | 0.8379   | 0.8931    |
| 0.0019        | 9.0   | 32994  | 0.0100          | 0.8388   | 0.9225    |
| 0.0048        | 10.0  | 36660  | 0.0103          | 0.8422   | 0.9035    |
| 0.0238        | 11.0  | 40326  | 0.0132          | 0.8378   | 0.9169    |
| 0.0           | 12.0  | 43992  | 0.0093          | 0.8509   | 0.9254    |
| 0.0017        | 13.0  | 47658  | 0.0116          | 0.8417   | 0.9243    |
| 0.0014        | 14.0  | 51324  | 0.0127          | 0.8348   | 0.9017    |
| 0.0031        | 15.0  | 54990  | 0.0123          | 0.8463   | 0.9299    |
| 0.0016        | 16.0  | 58656  | 0.0109          | 0.8439   | 0.9062    |
| 0.0091        | 17.0  | 62322  | 0.0199          | 0.8143   | 0.9344    |
| 0.0017        | 18.0  | 65988  | 0.0155          | 0.8326   | 0.9184    |
| 0.0           | 19.0  | 69654  | 0.0128          | 0.8351   | 0.8971    |
| 0.0013        | 20.0  | 73320  | 0.0135          | 0.8360   | 0.8970    |
| 0.0015        | 21.0  | 76986  | 0.0151          | 0.8466   | 0.9055    |
| 0.0011        | 22.0  | 80652  | 0.0136          | 0.8525   | 0.9117    |
| 0.0016        | 23.0  | 84318  | 0.0129          | 0.8478   | 0.9052    |
| 0.0007        | 24.0  | 87984  | 0.0189          | 0.8422   | 0.9422    |
| 0.0012        | 25.0  | 91650  | 0.0134          | 0.8435   | 0.9070    |
| 0.0012        | 26.0  | 95316  | 0.0152          | 0.8532   | 0.9243    |
| 0.0028        | 27.0  | 98982  | 0.0145          | 0.8521   | 0.9273    |
| 0.0023        | 28.0  | 102648 | 0.0156          | 0.8566   | 0.9288    |
| 0.0           | 29.0  | 106314 | 0.0176          | 0.8494   | 0.9222    |
| 0.0           | 30.0  | 109980 | 0.0156          | 0.8542   | 0.9282    |
| 0.0           | 31.0  | 113646 | 0.0158          | 0.8578   | 0.9273    |
| 0.0012        | 32.0  | 117312 | 0.0171          | 0.8560   | 0.9258    |
| 0.0005        | 33.0  | 120978 | 0.0146          | 0.8534   | 0.9149    |
| 0.0016        | 34.0  | 124644 | 0.0199          | 0.8519   | 0.9250    |
| 0.0015        | 35.0  | 128310 | 0.0164          | 0.8559   | 0.9181    |
| 0.0005        | 36.0  | 131976 | 0.0164          | 0.8551   | 0.9176    |
| 0.0014        | 37.0  | 135642 | 0.0172          | 0.8594   | 0.9263    |
| 0.0008        | 38.0  | 139308 | 0.0178          | 0.8601   | 0.9273    |
| 0.0           | 39.0  | 142974 | 0.0153          | 0.8601   | 0.9281    |
| 0.0           | 40.0  | 146640 | 0.0165          | 0.8632   | 0.9324    |
| 0.0           | 41.0  | 150306 | 0.0172          | 0.8624   | 0.9328    |
| 0.0002        | 42.0  | 153972 | 0.0201          | 0.8590   | 0.9303    |
| 0.0033        | 43.0  | 157638 | 0.0180          | 0.8611   | 0.9347    |
| 0.0           | 44.0  | 161304 | 0.0155          | 0.8620   | 0.9283    |
| 0.0011        | 45.0  | 164970 | 0.0174          | 0.8624   | 0.9277    |
| 0.0004        | 46.0  | 168636 | 0.0192          | 0.8612   | 0.9316    |
| 0.0           | 47.0  | 172302 | 0.0185          | 0.8612   | 0.9232    |
| 0.0007        | 48.0  | 175968 | 0.0173          | 0.8623   | 0.9247    |
| 0.0007        | 49.0  | 179634 | 0.0196          | 0.8628   | 0.9295    |
| 0.0003        | 50.0  | 183300 | 0.0192          | 0.8631   | 0.9304    |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1