---
license: other
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b0-scene-parse-150
  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-scene-parse-150

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the Grizzlygg/CrownTest dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7268
- Mean Iou: 0.3888
- Mean Accuracy: 0.7776
- Overall Accuracy: 0.7776
- Accuracy Unlabeled: nan
- Accuracy Crown: 0.7776
- Iou Unlabeled: 0.0
- Iou Crown: 0.7776

## 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 Unlabeled | Accuracy Crown | Iou Unlabeled | Iou Crown |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:---------:|
| 0.3303        | 10.0  | 20   | 0.6046          | 0.3722   | 0.7444        | 0.7444           | nan                | 0.7444         | 0.0           | 0.7444    |
| 0.2269        | 20.0  | 40   | 0.6817          | 0.3613   | 0.7226        | 0.7226           | nan                | 0.7226         | 0.0           | 0.7226    |
| 0.1893        | 30.0  | 60   | 0.7231          | 0.3717   | 0.7435        | 0.7435           | nan                | 0.7435         | 0.0           | 0.7435    |
| 0.185         | 40.0  | 80   | 0.7688          | 0.3880   | 0.7760        | 0.7760           | nan                | 0.7760         | 0.0           | 0.7760    |
| 0.1704        | 50.0  | 100  | 0.7268          | 0.3888   | 0.7776        | 0.7776           | nan                | 0.7776         | 0.0           | 0.7776    |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.13.3