---
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_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/0aseuh20)
# segformer_b1_finetuned_segment_pv_p100_4batch

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_v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0072
- Mean Iou: 0.8692
- Precision: 0.9162

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|
| 0.4877        | 1.0   | 917   | 0.2178          | 0.5326   | 0.6037    |
| 0.0992        | 2.0   | 1834  | 0.0258          | 0.7353   | 0.7913    |
| 0.022         | 3.0   | 2751  | 0.0119          | 0.7764   | 0.9267    |
| 0.0106        | 4.0   | 3668  | 0.0084          | 0.8093   | 0.8316    |
| 0.0069        | 5.0   | 4585  | 0.0070          | 0.8327   | 0.8698    |
| 0.0054        | 6.0   | 5502  | 0.0057          | 0.8431   | 0.8829    |
| 0.0044        | 7.0   | 6419  | 0.0055          | 0.8494   | 0.8877    |
| 0.0039        | 8.0   | 7336  | 0.0059          | 0.8474   | 0.9002    |
| 0.0036        | 9.0   | 8253  | 0.0056          | 0.8505   | 0.8894    |
| 0.0031        | 10.0  | 9170  | 0.0054          | 0.8575   | 0.8994    |
| 0.0031        | 11.0  | 10087 | 0.0051          | 0.8620   | 0.9190    |
| 0.0027        | 12.0  | 11004 | 0.0053          | 0.8646   | 0.9043    |
| 0.0026        | 13.0  | 11921 | 0.0059          | 0.8643   | 0.9275    |
| 0.0028        | 14.0  | 12838 | 0.0055          | 0.8641   | 0.9131    |
| 0.0025        | 15.0  | 13755 | 0.0053          | 0.8661   | 0.9120    |
| 0.0023        | 16.0  | 14672 | 0.0056          | 0.8644   | 0.9107    |
| 0.0022        | 17.0  | 15589 | 0.0052          | 0.8668   | 0.9125    |
| 0.0022        | 18.0  | 16506 | 0.0054          | 0.8700   | 0.9143    |
| 0.0022        | 19.0  | 17423 | 0.0059          | 0.8685   | 0.9180    |
| 0.002         | 20.0  | 18340 | 0.0057          | 0.8696   | 0.9157    |
| 0.0019        | 21.0  | 19257 | 0.0061          | 0.8682   | 0.9136    |
| 0.0019        | 22.0  | 20174 | 0.0069          | 0.8606   | 0.9262    |
| 0.0019        | 23.0  | 21091 | 0.0062          | 0.8700   | 0.9172    |
| 0.0018        | 24.0  | 22008 | 0.0061          | 0.8682   | 0.9258    |
| 0.0019        | 25.0  | 22925 | 0.0062          | 0.8669   | 0.9124    |
| 0.002         | 26.0  | 23842 | 0.0065          | 0.8672   | 0.9206    |
| 0.0017        | 27.0  | 24759 | 0.0062          | 0.8688   | 0.9108    |
| 0.0016        | 28.0  | 25676 | 0.0066          | 0.8686   | 0.9154    |
| 0.0016        | 29.0  | 26593 | 0.0066          | 0.8704   | 0.9175    |
| 0.0016        | 30.0  | 27510 | 0.0068          | 0.8664   | 0.9127    |
| 0.0015        | 31.0  | 28427 | 0.0069          | 0.8679   | 0.9150    |
| 0.0015        | 32.0  | 29344 | 0.0065          | 0.8691   | 0.9196    |
| 0.0015        | 33.0  | 30261 | 0.0069          | 0.8676   | 0.9130    |
| 0.0014        | 34.0  | 31178 | 0.0067          | 0.8691   | 0.9164    |
| 0.0014        | 35.0  | 32095 | 0.0071          | 0.8679   | 0.9153    |
| 0.0014        | 36.0  | 33012 | 0.0072          | 0.8687   | 0.9127    |
| 0.0014        | 37.0  | 33929 | 0.0073          | 0.8689   | 0.9151    |
| 0.0014        | 38.0  | 34846 | 0.0069          | 0.8696   | 0.9183    |
| 0.0014        | 39.0  | 35763 | 0.0070          | 0.8694   | 0.9163    |
| 0.0013        | 40.0  | 36680 | 0.0072          | 0.8692   | 0.9162    |


### Framework versions

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