---
license: other
base_model: nvidia/segformer-b2-finetuned-ade-512-512
tags:
- vision
- image-segmentation
- generated_from_trainer
metrics:
- precision
model-index:
- name: segformer_b2_finetuned_segment_pv_p100_4batch
  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/segformer-pv-4batches/runs/a86baba8)
# segformer_b2_finetuned_segment_pv_p100_4batch

This model is a fine-tuned version of [nvidia/segformer-b2-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b2-finetuned-ade-512-512) on the mouadenna/satellite_PV_dataset_train_test_v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0090
- Mean Iou: 0.8765
- Precision: 0.9192

## 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: 4e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Mean Iou | Precision |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|
| 0.5015        | 1.0   | 917   | 0.1494          | 0.5660   | 0.6026    |
| 0.0714        | 2.0   | 1834  | 0.0237          | 0.7528   | 0.7988    |
| 0.0171        | 3.0   | 2751  | 0.0101          | 0.7978   | 0.8930    |
| 0.0087        | 4.0   | 3668  | 0.0072          | 0.8260   | 0.8534    |
| 0.0058        | 5.0   | 4585  | 0.0067          | 0.8418   | 0.8981    |
| 0.0046        | 6.0   | 5502  | 0.0056          | 0.8457   | 0.8971    |
| 0.0038        | 7.0   | 6419  | 0.0056          | 0.8530   | 0.8770    |
| 0.0034        | 8.0   | 7336  | 0.0056          | 0.8525   | 0.8978    |
| 0.003         | 9.0   | 8253  | 0.0052          | 0.8643   | 0.9063    |
| 0.0028        | 10.0  | 9170  | 0.0054          | 0.8641   | 0.9010    |
| 0.0027        | 11.0  | 10087 | 0.0065          | 0.8489   | 0.9236    |
| 0.0025        | 12.0  | 11004 | 0.0066          | 0.8432   | 0.9006    |
| 0.0024        | 13.0  | 11921 | 0.0055          | 0.8637   | 0.9242    |
| 0.0022        | 14.0  | 12838 | 0.0054          | 0.8679   | 0.9104    |
| 0.0024        | 15.0  | 13755 | 0.0055          | 0.8719   | 0.9171    |
| 0.0019        | 16.0  | 14672 | 0.0055          | 0.8746   | 0.9219    |
| 0.0019        | 17.0  | 15589 | 0.0056          | 0.8668   | 0.9062    |
| 0.0018        | 18.0  | 16506 | 0.0063          | 0.8703   | 0.9121    |
| 0.0017        | 19.0  | 17423 | 0.0062          | 0.8694   | 0.9084    |
| 0.0016        | 20.0  | 18340 | 0.0063          | 0.8719   | 0.9133    |
| 0.0015        | 21.0  | 19257 | 0.0065          | 0.8734   | 0.9159    |
| 0.0014        | 22.0  | 20174 | 0.0068          | 0.8730   | 0.9155    |
| 0.0015        | 23.0  | 21091 | 0.0069          | 0.8719   | 0.9228    |
| 0.0013        | 24.0  | 22008 | 0.0069          | 0.8745   | 0.9162    |
| 0.0013        | 25.0  | 22925 | 0.0069          | 0.8757   | 0.9196    |
| 0.0012        | 26.0  | 23842 | 0.0075          | 0.8747   | 0.9138    |
| 0.0012        | 27.0  | 24759 | 0.0074          | 0.8750   | 0.9159    |
| 0.0012        | 28.0  | 25676 | 0.0074          | 0.8755   | 0.9213    |
| 0.0011        | 29.0  | 26593 | 0.0081          | 0.8762   | 0.9154    |
| 0.0011        | 30.0  | 27510 | 0.0083          | 0.8754   | 0.9162    |
| 0.0011        | 31.0  | 28427 | 0.0084          | 0.8753   | 0.9168    |
| 0.001         | 32.0  | 29344 | 0.0083          | 0.8754   | 0.9202    |
| 0.001         | 33.0  | 30261 | 0.0085          | 0.8758   | 0.9174    |
| 0.001         | 34.0  | 31178 | 0.0085          | 0.8758   | 0.9208    |
| 0.0009        | 35.0  | 32095 | 0.0088          | 0.8763   | 0.9191    |
| 0.0009        | 36.0  | 33012 | 0.0090          | 0.8756   | 0.9172    |
| 0.0009        | 37.0  | 33929 | 0.0090          | 0.8760   | 0.9181    |
| 0.0009        | 38.0  | 34846 | 0.0087          | 0.8764   | 0.9195    |
| 0.0009        | 39.0  | 35763 | 0.0090          | 0.8763   | 0.9184    |
| 0.0009        | 40.0  | 36680 | 0.0090          | 0.8765   | 0.9192    |


### Framework versions

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