transformers pytorch tensorboard segformer vision image-segmentation generated_from_trainer license:other endpoints_compatible region:us
---
license: other
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: parking-utcustom-train-SF-RGB-b0_1
  results: []
---

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# parking-utcustom-train-SF-RGB-b0_1

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the sam1120/parking-utcustom-train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7736
- Mean Iou: 0.3038
- Mean Accuracy: 0.9115
- Overall Accuracy: 0.9115
- Accuracy Unlabeled: nan
- Accuracy Parking: nan
- Accuracy Unparking: 0.9115
- Iou Unlabeled: 0.0
- Iou Parking: 0.0
- Iou Unparking: 0.9115

## 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: 2.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 120

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Parking | Accuracy Unparking | Iou Unlabeled | Iou Parking | Iou Unparking |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:----------------:|:------------------:|:-------------:|:-----------:|:-------------:|
| 1.0406        | 20.0  | 20   | 1.0478          | 0.2219   | 0.6657        | 0.6657           | nan                | nan              | 0.6657             | 0.0           | 0.0         | 0.6657        |
| 0.9316        | 40.0  | 40   | 0.9617          | 0.2595   | 0.7786        | 0.7786           | nan                | nan              | 0.7786             | 0.0           | 0.0         | 0.7786        |
| 0.8588        | 60.0  | 60   | 0.8796          | 0.2921   | 0.8762        | 0.8762           | nan                | nan              | 0.8762             | 0.0           | 0.0         | 0.8762        |
| 0.7749        | 80.0  | 80   | 0.8291          | 0.2977   | 0.8930        | 0.8930           | nan                | nan              | 0.8930             | 0.0           | 0.0         | 0.8930        |
| 0.7452        | 100.0 | 100  | 0.7801          | 0.3075   | 0.9226        | 0.9226           | nan                | nan              | 0.9226             | 0.0           | 0.0         | 0.9226        |
| 0.7238        | 120.0 | 120  | 0.7736          | 0.3038   | 0.9115        | 0.9115           | nan                | nan              | 0.9115             | 0.0           | 0.0         | 0.9115        |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
