---
license: other
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: parking-utcustom-train-SF-RGB-b0_4
  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. -->

# parking-utcustom-train-SF-RGB-b0_4

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: 0.6504
- Mean Iou: 0.3176
- Mean Accuracy: 0.9528
- Overall Accuracy: 0.9528
- Accuracy Unlabeled: nan
- Accuracy Parking: nan
- Accuracy Unparking: 0.9528
- Iou Unlabeled: 0.0
- Iou Parking: 0.0
- Iou Unparking: 0.9528

## 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: 4e-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:----------------:|:------------------:|:-------------:|:-----------:|:-------------:|
| 1.1564        | 20.0  | 20   | 1.1510          | 0.1413   | 0.4239        | 0.4239           | nan                | nan              | 0.4239             | 0.0           | 0.0         | 0.4239        |
| 0.924         | 40.0  | 40   | 1.1282          | 0.2675   | 0.8024        | 0.8024           | nan                | nan              | 0.8024             | 0.0           | 0.0         | 0.8024        |
| 0.8182        | 60.0  | 60   | 0.9038          | 0.2908   | 0.8723        | 0.8723           | nan                | nan              | 0.8723             | 0.0           | 0.0         | 0.8723        |
| 0.6976        | 80.0  | 80   | 0.7238          | 0.3070   | 0.9211        | 0.9211           | nan                | nan              | 0.9211             | 0.0           | 0.0         | 0.9211        |
| 0.6843        | 100.0 | 100  | 0.6362          | 0.3221   | 0.9663        | 0.9663           | nan                | nan              | 0.9663             | 0.0           | 0.0         | 0.9663        |
| 0.6309        | 120.0 | 120  | 0.6504          | 0.3176   | 0.9528        | 0.9528           | nan                | nan              | 0.9528             | 0.0           | 0.0         | 0.9528        |


### Framework versions

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