---
license: other
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: parking-utcustom-train-SF-RGBD-b5_1
  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-RGBD-b5_1

This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the sam1120/parking-utcustom-train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0350
- Mean Iou: 0.4983
- Mean Accuracy: 0.9967
- Overall Accuracy: 0.9967
- Accuracy Unlabeled: nan
- Accuracy Parking: nan
- Accuracy Unparking: 0.9967
- Iou Unlabeled: nan
- Iou Parking: 0.0
- Iou Unparking: 0.9967

## 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: 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: 140

### 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:----------------:|:------------------:|:-------------:|:-----------:|:-------------:|
| 0.4573        | 20.0  | 20   | 0.3024          | 0.3276   | 0.9829        | 0.9829           | nan                | nan              | 0.9829             | 0.0           | 0.0         | 0.9829        |
| 0.2183        | 40.0  | 40   | 0.2365          | 0.3318   | 0.9953        | 0.9953           | nan                | nan              | 0.9953             | 0.0           | 0.0         | 0.9953        |
| 0.1266        | 60.0  | 60   | 0.0999          | 1.0      | 1.0           | 1.0              | nan                | nan              | 1.0                | nan           | nan         | 1.0           |
| 0.0929        | 80.0  | 80   | 0.0590          | 0.4986   | 0.9972        | 0.9972           | nan                | nan              | 0.9972             | nan           | 0.0         | 0.9972        |
| 0.0669        | 100.0 | 100  | 0.0375          | 0.4998   | 0.9996        | 0.9996           | nan                | nan              | 0.9996             | nan           | 0.0         | 0.9996        |
| 0.0557        | 120.0 | 120  | 0.0443          | 0.4953   | 0.9907        | 0.9907           | nan                | nan              | 0.9907             | nan           | 0.0         | 0.9907        |
| 0.0688        | 140.0 | 140  | 0.0350          | 0.4983   | 0.9967        | 0.9967           | nan                | nan              | 0.9967             | nan           | 0.0         | 0.9967        |


### Framework versions

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