---
license: other
base_model: nvidia/segformer-b0-finetuned-ade-512-512
tags:
- vision
- image-segmentation
- generated_from_trainer
metrics:
- precision
model-index:
- name: segformer_b0_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/tes0yime)
# segformer_b0_finetuned_segment_pv_p100_4batch

This model is a fine-tuned version of [nvidia/segformer-b0-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512) on the mouadenna/satellite_PV_dataset_train_test_v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0065
- Mean Iou: 0.8630
- Precision: 0.9115

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|
| 0.5732        | 1.0   | 917   | 0.2901          | 0.4717   | 0.5866    |
| 0.1327        | 2.0   | 1834  | 0.0327          | 0.6919   | 0.7689    |
| 0.0272        | 3.0   | 2751  | 0.0138          | 0.7618   | 0.8768    |
| 0.0128        | 4.0   | 3668  | 0.0098          | 0.7875   | 0.8206    |
| 0.0081        | 5.0   | 4585  | 0.0077          | 0.8165   | 0.8512    |
| 0.0061        | 6.0   | 5502  | 0.0071          | 0.8177   | 0.8795    |
| 0.005         | 7.0   | 6419  | 0.0060          | 0.8303   | 0.8747    |
| 0.0045        | 8.0   | 7336  | 0.0056          | 0.8459   | 0.8897    |
| 0.004         | 9.0   | 8253  | 0.0057          | 0.8470   | 0.8851    |
| 0.0038        | 10.0  | 9170  | 0.0058          | 0.8384   | 0.8761    |
| 0.0034        | 11.0  | 10087 | 0.0056          | 0.8495   | 0.8966    |
| 0.0033        | 12.0  | 11004 | 0.0053          | 0.8464   | 0.8956    |
| 0.0031        | 13.0  | 11921 | 0.0060          | 0.8354   | 0.8843    |
| 0.003         | 14.0  | 12838 | 0.0063          | 0.8414   | 0.8897    |
| 0.0028        | 15.0  | 13755 | 0.0062          | 0.8466   | 0.9129    |
| 0.0029        | 16.0  | 14672 | 0.0060          | 0.8480   | 0.9057    |
| 0.0026        | 17.0  | 15589 | 0.0056          | 0.8559   | 0.9005    |
| 0.0027        | 18.0  | 16506 | 0.0055          | 0.8571   | 0.9042    |
| 0.0025        | 19.0  | 17423 | 0.0056          | 0.8571   | 0.9096    |
| 0.0025        | 20.0  | 18340 | 0.0080          | 0.8329   | 0.9194    |
| 0.0025        | 21.0  | 19257 | 0.0058          | 0.8567   | 0.8981    |
| 0.0023        | 22.0  | 20174 | 0.0058          | 0.8624   | 0.9061    |
| 0.0023        | 23.0  | 21091 | 0.0059          | 0.8599   | 0.9055    |
| 0.0022        | 24.0  | 22008 | 0.0061          | 0.8601   | 0.9132    |
| 0.0023        | 25.0  | 22925 | 0.0059          | 0.8603   | 0.9007    |
| 0.0021        | 26.0  | 23842 | 0.0065          | 0.8594   | 0.9160    |
| 0.0021        | 27.0  | 24759 | 0.0059          | 0.8636   | 0.9071    |
| 0.0021        | 28.0  | 25676 | 0.0060          | 0.8650   | 0.9093    |
| 0.002         | 29.0  | 26593 | 0.0061          | 0.8639   | 0.9158    |
| 0.002         | 30.0  | 27510 | 0.0063          | 0.8621   | 0.9074    |
| 0.002         | 31.0  | 28427 | 0.0064          | 0.8598   | 0.9081    |
| 0.0021        | 32.0  | 29344 | 0.0064          | 0.8570   | 0.9129    |
| 0.0019        | 33.0  | 30261 | 0.0064          | 0.8601   | 0.9086    |
| 0.0019        | 34.0  | 31178 | 0.0062          | 0.8626   | 0.9146    |
| 0.0019        | 35.0  | 32095 | 0.0066          | 0.8607   | 0.9060    |
| 0.0018        | 36.0  | 33012 | 0.0064          | 0.8610   | 0.9056    |
| 0.0018        | 37.0  | 33929 | 0.0065          | 0.8618   | 0.9072    |
| 0.0018        | 38.0  | 34846 | 0.0063          | 0.8631   | 0.9094    |
| 0.0018        | 39.0  | 35763 | 0.0064          | 0.8628   | 0.9126    |
| 0.0018        | 40.0  | 36680 | 0.0065          | 0.8630   | 0.9115    |


### Framework versions

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