---
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_v1_normalized_p100_4batch_try
  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/b36iwo31)
# segformer-b1-finetuned-segments-pv_v1_normalized_p100_4batch_try

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: 0.0012
- Mean Iou: 0.9586
- Precision: 0.9787

## 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: 0.0004
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:---------:|
| 0.2001        | 0.9989  | 229  | 0.0557          | 0.7433   | 0.8099    |
| 0.0234        | 1.9978  | 458  | 0.0111          | 0.8026   | 0.8735    |
| 0.0109        | 2.9967  | 687  | 0.0069          | 0.8264   | 0.9062    |
| 0.0077        | 4.0     | 917  | 0.0052          | 0.8659   | 0.9087    |
| 0.0053        | 4.9989  | 1146 | 0.0142          | 0.6652   | 0.6845    |
| 0.0055        | 5.9978  | 1375 | 0.0041          | 0.8885   | 0.9319    |
| 0.0041        | 6.9967  | 1604 | 0.0038          | 0.8855   | 0.9516    |
| 0.0046        | 8.0     | 1834 | 0.0041          | 0.8787   | 0.9430    |
| 0.0041        | 8.9989  | 2063 | 0.0035          | 0.8902   | 0.9105    |
| 0.0035        | 9.9978  | 2292 | 0.0028          | 0.9107   | 0.9475    |
| 0.0034        | 10.9967 | 2521 | 0.0027          | 0.9116   | 0.9390    |
| 0.0038        | 12.0    | 2751 | 0.0031          | 0.9001   | 0.9306    |
| 0.0033        | 12.9989 | 2980 | 0.0025          | 0.9160   | 0.9563    |
| 0.0029        | 13.9978 | 3209 | 0.0026          | 0.9153   | 0.9444    |
| 0.0026        | 14.9967 | 3438 | 0.0023          | 0.9218   | 0.9499    |
| 0.0027        | 16.0    | 3668 | 0.0027          | 0.9086   | 0.9525    |
| 0.0032        | 16.9989 | 3897 | 0.0029          | 0.9076   | 0.9439    |
| 0.0033        | 17.9978 | 4126 | 0.0024          | 0.9192   | 0.9459    |
| 0.0025        | 18.9967 | 4355 | 0.0027          | 0.9108   | 0.9538    |
| 0.0024        | 20.0    | 4585 | 0.0021          | 0.9276   | 0.9559    |
| 0.0022        | 20.9989 | 4814 | 0.0020          | 0.9316   | 0.9649    |
| 0.0021        | 21.9978 | 5043 | 0.0021          | 0.9287   | 0.9571    |
| 0.0025        | 22.9967 | 5272 | 0.0023          | 0.9217   | 0.9511    |
| 0.0022        | 24.0    | 5502 | 0.0020          | 0.9309   | 0.9676    |
| 0.002         | 24.9989 | 5731 | 0.0018          | 0.9360   | 0.9613    |
| 0.002         | 25.9978 | 5960 | 0.0017          | 0.9394   | 0.9621    |
| 0.0019        | 26.9967 | 6189 | 0.0017          | 0.9403   | 0.9664    |
| 0.0018        | 28.0    | 6419 | 0.0017          | 0.9405   | 0.9566    |
| 0.0017        | 28.9989 | 6648 | 0.0016          | 0.9438   | 0.9695    |
| 0.0017        | 29.9978 | 6877 | 0.0015          | 0.9469   | 0.9755    |
| 0.002         | 30.9967 | 7106 | 0.0016          | 0.9448   | 0.9672    |
| 0.0018        | 32.0    | 7336 | 0.0015          | 0.9459   | 0.9693    |
| 0.0016        | 32.9989 | 7565 | 0.0014          | 0.9486   | 0.9674    |
| 0.0015        | 33.9978 | 7794 | 0.0013          | 0.9528   | 0.9761    |
| 0.0015        | 34.9967 | 8023 | 0.0013          | 0.9520   | 0.9732    |
| 0.0014        | 36.0    | 8253 | 0.0013          | 0.9541   | 0.9705    |
| 0.0014        | 36.9989 | 8482 | 0.0012          | 0.9563   | 0.9739    |
| 0.0014        | 37.9978 | 8711 | 0.0012          | 0.9575   | 0.9764    |
| 0.0014        | 38.9967 | 8940 | 0.0012          | 0.9581   | 0.9766    |
| 0.0014        | 39.9564 | 9160 | 0.0012          | 0.9586   | 0.9787    |


### Framework versions

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