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# segformer-b0-finetuned-segments-sidewalk-2

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the jhaberbe/lipid-droplets dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1190
- Mean Iou: 0.0003
- Mean Accuracy: 0.0005
- Overall Accuracy: 0.0005
- Accuracy Unlabeled: nan
- Accuracy Lipid: 0.0005
- Iou Unlabeled: 0.0
- Iou Lipid: 0.0005

## 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 Lipid | Iou Unlabeled | Iou Lipid |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:---------:|
| 0.4655        | 2.5   | 20   | 0.5773          | 0.0      | 0.0           | 0.0              | nan                | 0.0            | 0.0           | 0.0       |
| 0.3833        | 5.0   | 40   | 0.3752          | 0.0      | 0.0           | 0.0              | nan                | 0.0            | 0.0           | 0.0       |
| 0.2614        | 7.5   | 60   | 0.3287          | 0.0030   | 0.0061        | 0.0061           | nan                | 0.0061         | 0.0           | 0.0061    |
| 0.2051        | 10.0  | 80   | 0.2866          | 0.0056   | 0.0112        | 0.0112           | nan                | 0.0112         | 0.0           | 0.0112    |
| 0.2325        | 12.5  | 100  | 0.2576          | 0.0038   | 0.0075        | 0.0075           | nan                | 0.0075         | 0.0           | 0.0075    |
| 0.1321        | 15.0  | 120  | 0.3566          | 0.0075   | 0.0150        | 0.0150           | nan                | 0.0150         | 0.0           | 0.0150    |
| 0.1154        | 17.5  | 140  | 0.0788          | 0.0      | 0.0           | 0.0              | nan                | 0.0            | 0.0           | 0.0       |
| 0.1673        | 20.0  | 160  | 0.1221          | 0.0004   | 0.0007        | 0.0007           | nan                | 0.0007         | 0.0           | 0.0007    |
| 0.0926        | 22.5  | 180  | 0.2054          | 0.0050   | 0.0100        | 0.0100           | nan                | 0.0100         | 0.0           | 0.0100    |
| 0.0772        | 25.0  | 200  | 0.2137          | 0.0047   | 0.0094        | 0.0094           | nan                | 0.0094         | 0.0           | 0.0094    |
| 0.0728        | 27.5  | 220  | 0.2009          | 0.0028   | 0.0056        | 0.0056           | nan                | 0.0056         | 0.0           | 0.0056    |
| 0.0822        | 30.0  | 240  | 0.0919          | 0.0000   | 0.0001        | 0.0001           | nan                | 0.0001         | 0.0           | 0.0001    |
| 0.0566        | 32.5  | 260  | 0.2123          | 0.0141   | 0.0283        | 0.0283           | nan                | 0.0283         | 0.0           | 0.0283    |
| 0.0568        | 35.0  | 280  | 0.2434          | 0.0078   | 0.0157        | 0.0157           | nan                | 0.0157         | 0.0           | 0.0157    |
| 0.1524        | 37.5  | 300  | 0.1944          | 0.0277   | 0.0553        | 0.0553           | nan                | 0.0553         | 0.0           | 0.0553    |
| 0.0714        | 40.0  | 320  | 0.1203          | 0.0150   | 0.0300        | 0.0300           | nan                | 0.0300         | 0.0           | 0.0300    |
| 0.0484        | 42.5  | 340  | 0.1303          | 0.0025   | 0.0050        | 0.0050           | nan                | 0.0050         | 0.0           | 0.0050    |
| 0.051         | 45.0  | 360  | 0.1411          | 0.0064   | 0.0128        | 0.0128           | nan                | 0.0128         | 0.0           | 0.0128    |
| 0.063         | 47.5  | 380  | 0.0970          | 0.0008   | 0.0017        | 0.0017           | nan                | 0.0017         | 0.0           | 0.0017    |
| 0.0465        | 50.0  | 400  | 0.1190          | 0.0003   | 0.0005        | 0.0005           | nan                | 0.0005         | 0.0           | 0.0005    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2

{"license": "other", "tags": ["vision", "image-segmentation", "generated_from_trainer"], "base_model": "nvidia/mit-b0", "model-index": [{"name": "segformer-b0-finetuned-segments-sidewalk-2", "results": []}]}
transformers safetensors segformer vision image-segmentation generated_from_trainer base_model:nvidia/mit-b0 license:other endpoints_compatible region:us