---
library_name: transformers
license: other
base_model: nvidia/segformer-b0-finetuned-ade-512-512
tags:
- generated_from_trainer
model-index:
- name: segformer-b0-segments-lungs-xray
  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. -->

# segformer-b0-segments-lungs-xray

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0589
- Mean Iou: 0.9509
- Mean Accuracy: 0.9747
- Overall Accuracy: 0.9814
- Accuracy Background: 0.9877
- Accuracy Target: 0.9617
- Iou Background: 0.9758
- Iou Target: 0.9260

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Target | Iou Background | Iou Target |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:---------------:|:--------------:|:----------:|
| 0.1417        | 1.0   | 123  | 0.1330          | 0.9172   | 0.9657        | 0.9673           | 0.9688              | 0.9626          | 0.9574         | 0.8770     |
| 0.0957        | 2.0   | 246  | 0.0860          | 0.9425   | 0.9680        | 0.9782           | 0.9878              | 0.9481          | 0.9717         | 0.9133     |
| 0.0889        | 3.0   | 369  | 0.0743          | 0.9418   | 0.9734        | 0.9777           | 0.9817              | 0.9650          | 0.9709         | 0.9128     |
| 0.076         | 4.0   | 492  | 0.0635          | 0.9494   | 0.9724        | 0.9809           | 0.9889              | 0.9559          | 0.9751         | 0.9237     |
| 0.0621        | 5.0   | 615  | 0.0603          | 0.9508   | 0.9734        | 0.9814           | 0.9890              | 0.9578          | 0.9758         | 0.9259     |
| 0.0653        | 6.0   | 738  | 0.0589          | 0.9509   | 0.9747        | 0.9814           | 0.9877              | 0.9617          | 0.9758         | 0.9260     |
| 0.0593        | 7.0   | 861  | 0.0587          | 0.9507   | 0.9748        | 0.9813           | 0.9875              | 0.9622          | 0.9757         | 0.9258     |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3