---
license: other
base_model: nvidia/mit-b0
tags:
- image-segmentation
- vision
- generated_from_trainer
model-index:
- name: segformer-finetuned-obb-1k-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-obb-1k-steps

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the Spatiallysaying/obb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0511
- Mean Iou: 0.2238
- Mean Accuracy: 0.4477
- Overall Accuracy: 0.4477
- Accuracy  Backgound : nan
- Accuracy Rwy Obb: 0.4477
- Iou  Backgound : 0.0
- Iou Rwy Obb: 0.4477

## 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: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- training_steps: 1000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy  Backgound  | Accuracy Rwy Obb | Iou  Backgound  | Iou Rwy Obb |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------------:|:----------------:|:---------------:|:-----------:|
| 0.3927        | 1.0    | 173  | 0.1096          | 0.1590   | 0.3180        | 0.3180           | nan                  | 0.3180           | 0.0             | 0.3180      |
| 0.0969        | 2.0    | 346  | 0.0704          | 0.2112   | 0.4224        | 0.4224           | nan                  | 0.4224           | 0.0             | 0.4224      |
| 0.0651        | 3.0    | 519  | 0.0598          | 0.2186   | 0.4371        | 0.4371           | nan                  | 0.4371           | 0.0             | 0.4371      |
| 0.0576        | 4.0    | 692  | 0.0530          | 0.2250   | 0.4500        | 0.4500           | nan                  | 0.4500           | 0.0             | 0.4500      |
| 0.0531        | 5.0    | 865  | 0.0529          | 0.2212   | 0.4424        | 0.4424           | nan                  | 0.4424           | 0.0             | 0.4424      |
| 0.0467        | 5.7803 | 1000 | 0.0511          | 0.2238   | 0.4477        | 0.4477           | nan                  | 0.4477           | 0.0             | 0.4477      |


### Framework versions

- Transformers 4.43.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1