---
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 bricklerex/lane-detect dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0646
- Mean Iou: 0.4681
- Mean Accuracy: 0.9362
- Overall Accuracy: 0.9362
- Accuracy Unlabelled: nan
- Accuracy Lane: 0.9362
- Iou Unlabelled: 0.0
- Iou Lane: 0.9362

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabelled | Accuracy Lane | Iou Unlabelled | Iou Lane |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:--------------:|:--------:|
| 0.0823        | 0.35  | 20   | 0.0933          | 0.4675   | 0.9349        | 0.9349           | nan                 | 0.9349        | 0.0            | 0.9349   |
| 0.0676        | 0.7   | 40   | 0.0737          | 0.4547   | 0.9093        | 0.9093           | nan                 | 0.9093        | 0.0            | 0.9093   |
| 0.0639        | 1.05  | 60   | 0.0659          | 0.4583   | 0.9166        | 0.9166           | nan                 | 0.9166        | 0.0            | 0.9166   |
| 0.0584        | 1.4   | 80   | 0.0831          | 0.4715   | 0.9429        | 0.9429           | nan                 | 0.9429        | 0.0            | 0.9429   |
| 0.0541        | 1.75  | 100  | 0.0646          | 0.4681   | 0.9362        | 0.9362           | nan                 | 0.9362        | 0.0            | 0.9362   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2