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---
license: other
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: parking-utcustom-train-SF-RGBD-b5_3
  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_3

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: 0.0234
- Mean Iou: 1.0
- Mean Accuracy: 1.0
- Overall Accuracy: 1.0
- Accuracy Unlabeled: nan
- Accuracy Parking: nan
- Accuracy Unparking: 1.0
- Iou Unlabeled: nan
- Iou Parking: nan
- Iou Unparking: 1.0

## 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: 5.7e-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: 150

### Training results

| Training Loss | Epoch | Step | Accuracy Parking | Accuracy Unlabeled | Accuracy Unparking | Iou Parking | Iou Unlabeled | Iou Unparking | Validation Loss | Mean Accuracy | Mean Iou | Overall Accuracy |
|:-------------:|:-----:|:----:|:----------------:|:------------------:|:------------------:|:-----------:|:-------------:|:-------------:|:---------------:|:-------------:|:--------:|:----------------:|
| 0.3831        | 20.0  | 20   | nan              | nan                | 0.9868             | 0.0         | nan           | 0.9868        | 0.3810          | 0.9868        | 0.4934   | 0.9868           |
| 0.1678        | 40.0  | 40   | nan              | nan                | 0.9999             | 0.0         | nan           | 0.9999        | 0.2179          | 0.9999        | 0.5000   | 0.9999           |
| 0.123         | 60.0  | 60   | nan              | nan                | 0.9994             | 0.0         | nan           | 0.9994        | 0.0796          | 0.9994        | 0.4997   | 0.9994           |
| 0.09          | 80.0  | 80   | nan              | nan                | 1.0                | nan         | nan           | 1.0           | 0.0433          | 1.0           | 1.0      | 1.0              |
| 0.0626        | 100.0 | 100  | 0.0283           | 1.0                | 1.0                | 1.0         | nan           | nan           | 1.0             | nan           | nan      | 1.0              |
| 0.0493        | 120.0 | 120  | 0.0272           | 1.0                | 1.0                | 1.0         | nan           | nan           | 1.0             | nan           | nan      | 1.0              |
| 0.0525        | 140.0 | 140  | 0.0234           | 1.0                | 1.0                | 1.0         | nan           | nan           | 1.0             | nan           | nan      | 1.0              |


### Framework versions

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