---
license: other
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b0-finetuned-busigt2
  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-finetuned-busigt2

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the kasumi222/busigt5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9345
- Mean Iou: 0.2296
- Mean Accuracy: 0.3908
- Overall Accuracy: 0.3978
- Per Category Iou: [0.0, 0.3674785422564665, 0.32138792265751265]
- Per Category Accuracy: [nan, 0.43273323064546193, 0.34877217945992856]

## 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: 0.00013
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou                               | Per Category Accuracy                           |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------------------------------------:|:-----------------------------------------------:|
| 0.813         | 0.61  | 20   | 0.9345          | 0.2296   | 0.3908        | 0.3978           | [0.0, 0.3674785422564665, 0.32138792265751265] | [nan, 0.43273323064546193, 0.34877217945992856] |


### Framework versions

- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1