---
license: other
base_model: nvidia/mit-b0
tags:
- image-segmentation
- vision
- generated_from_trainer
model-index:
- name: segformer-finetuned-sidewalk-10k-steps
  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-finetuned-sidewalk-10k-steps

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the Manduzamzam/practice2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6829
- Mean Iou: 0.0140
- Mean Accuracy: 0.0279
- Overall Accuracy: 0.0279
- Accuracy Background: nan
- Accuracy Object: 0.0279
- Iou Background: 0.0
- Iou Object: 0.0279

## 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: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- training_steps: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Object | Iou Background | Iou Object |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:---------------:|:--------------:|:----------:|
| No log        | 0.71  | 10   | 0.6829          | 0.0140   | 0.0279        | 0.0279           | nan                 | 0.0279          | 0.0            | 0.0279     |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.14.5
- Tokenizers 0.14.0