---
library_name: transformers
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b0-finetuned-georeferencing
  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-georeferencing

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the zhaoqiao0120/georeferencing_2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1456
- Mean Iou: 0.0
- Mean Accuracy: 0.0
- Overall Accuracy: 0.0
- Accuracy Unlabeled: nan
- Accuracy Object: 0.0
- Iou Unlabeled: 0.0
- Iou Object: 0.0

## 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 Object | Iou Unlabeled | Iou Object |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:---------------:|:-------------:|:----------:|
| 0.4873        | 5.0   | 20   | 0.5349          | 0.0      | 0.0           | 0.0              | nan                | 0.0             | 0.0           | 0.0        |
| 0.3815        | 10.0  | 40   | 0.3688          | 0.0      | 0.0           | 0.0              | nan                | 0.0             | 0.0           | 0.0        |
| 0.3355        | 15.0  | 60   | 0.2834          | 0.0      | 0.0           | 0.0              | nan                | 0.0             | 0.0           | 0.0        |
| 0.2632        | 20.0  | 80   | 0.2497          | 0.0      | 0.0           | 0.0              | nan                | 0.0             | 0.0           | 0.0        |
| 0.187         | 25.0  | 100  | 0.2110          | 0.0      | 0.0           | 0.0              | nan                | 0.0             | 0.0           | 0.0        |
| 0.2059        | 30.0  | 120  | 0.1814          | 0.0      | 0.0           | 0.0              | nan                | 0.0             | 0.0           | 0.0        |
| 0.1468        | 35.0  | 140  | 0.1703          | 0.0      | 0.0           | 0.0              | nan                | 0.0             | 0.0           | 0.0        |
| 0.1357        | 40.0  | 160  | 0.1479          | 0.0      | 0.0           | 0.0              | nan                | 0.0             | 0.0           | 0.0        |
| 0.1443        | 45.0  | 180  | 0.1445          | 0.0      | 0.0           | 0.0              | nan                | 0.0             | 0.0           | 0.0        |
| 0.1344        | 50.0  | 200  | 0.1456          | 0.0      | 0.0           | 0.0              | nan                | 0.0             | 0.0           | 0.0        |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cpu
- Datasets 2.21.0
- Tokenizers 0.19.1