---
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b0-finetuned-segments-sidewalk-oct-22
  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-segments-sidewalk-oct-22

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the mrkprc1/SudokuSegmentation2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3909
- Mean Iou: 0.3084
- Mean Accuracy: 0.9142
- Overall Accuracy: 0.9142
- Accuracy Empty-cell: nan
- Accuracy Complete-cell: 0.9142
- Iou Empty-cell: 0.0
- Iou Complete-cell: 0.6169

## 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-05
- 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Empty-cell | Accuracy Complete-cell | Iou Empty-cell | Iou Complete-cell |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:----------------------:|:--------------:|:-----------------:|
| 0.3784        | 10.0  | 20   | 0.4056          | 0.3166   | 0.9695        | 0.9695           | nan                 | 0.9695                 | 0.0            | 0.6333            |
| 0.3037        | 20.0  | 40   | 0.4253          | 0.2816   | 0.7997        | 0.7997           | nan                 | 0.7997                 | 0.0            | 0.5631            |
| 0.3326        | 30.0  | 60   | 0.4163          | 0.2894   | 0.8280        | 0.8280           | nan                 | 0.8280                 | 0.0            | 0.5789            |
| 0.276         | 40.0  | 80   | 0.4037          | 0.2990   | 0.8758        | 0.8758           | nan                 | 0.8758                 | 0.0            | 0.5979            |
| 0.2616        | 50.0  | 100  | 0.3909          | 0.3084   | 0.9142        | 0.9142           | nan                 | 0.9142                 | 0.0            | 0.6169            |


### Framework versions

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