---
license: other
tags:
- vision
- image-segmentation
- generated_from_trainer
base_model: nvidia/mit-b0
model-index:
- name: segformer-b0-finetuned-sudoku
  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-sudoku

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the mrkprc1/SudokuBoundaries2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6963
- Mean Iou: 0.2715
- Mean Accuracy: 0.4994
- Overall Accuracy: 0.4914
- Accuracy Unlabelled: 0.9207
- Accuracy Sudoku-boundary: 0.0782
- Iou Unlabelled: 0.4703
- Iou Sudoku-boundary: 0.0726

## 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: 6e-07
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabelled | Accuracy Sudoku-boundary | Iou Unlabelled | Iou Sudoku-boundary |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:------------------------:|:--------------:|:-------------------:|
| 0.5345        | 3.33  | 20   | 0.6911          | 0.3154   | 0.5281        | 0.5355           | 0.1414              | 0.9147                   | 0.1299         | 0.5008              |
| 1.1081        | 6.67  | 40   | 0.6904          | 0.3388   | 0.5351        | 0.5411           | 0.2242              | 0.8460                   | 0.1933         | 0.4844              |
| 0.3015        | 10.0  | 60   | 0.6963          | 0.2715   | 0.4994        | 0.4914           | 0.9207              | 0.0782                   | 0.4703         | 0.0726              |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.1