---
license: other
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: parking-utcustom-train-SF-RGB-b0_2
  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_2

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: 0.7834
- Mean Iou: 0.3040
- Mean Accuracy: 0.9120
- Overall Accuracy: 0.9120
- Accuracy Unlabeled: nan
- Accuracy Parking: nan
- Accuracy Unparking: 0.9120
- Iou Unlabeled: 0.0
- Iou Parking: 0.0
- Iou Unparking: 0.9120

## 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: 3e-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:----------------:|:------------------:|:-------------:|:-----------:|:-------------:|
| 1.0965        | 20.0  | 20   | 1.0974          | 0.1433   | 0.4299        | 0.4299           | nan                | nan              | 0.4299             | 0.0           | 0.0         | 0.4299        |
| 0.9563        | 40.0  | 40   | 1.0286          | 0.2412   | 0.7235        | 0.7235           | nan                | nan              | 0.7235             | 0.0           | 0.0         | 0.7235        |
| 0.8707        | 60.0  | 60   | 0.9260          | 0.2870   | 0.8609        | 0.8609           | nan                | nan              | 0.8609             | 0.0           | 0.0         | 0.8609        |
| 0.7662        | 80.0  | 80   | 0.8392          | 0.2951   | 0.8853        | 0.8853           | nan                | nan              | 0.8853             | 0.0           | 0.0         | 0.8853        |
| 0.7385        | 100.0 | 100  | 0.7800          | 0.3058   | 0.9173        | 0.9173           | nan                | nan              | 0.9173             | 0.0           | 0.0         | 0.9173        |
| 0.7107        | 120.0 | 120  | 0.7834          | 0.3040   | 0.9120        | 0.9120           | nan                | nan              | 0.9120             | 0.0           | 0.0         | 0.9120        |


### Framework versions

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