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-b5_7
  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-b5_7

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: 0.0410
- 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: 4.5e-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:----------------:|:------------------:|:-------------:|:-----------:|:-------------:|
| 0.5829        | 20.0  | 20   | 0.5323          | 0.5000   | 0.9999        | 0.9999           | nan                | nan              | 0.9999             | nan           | 0.0         | 0.9999        |
| 0.2348        | 40.0  | 40   | 0.1931          | 0.3333   | 0.9999        | 0.9999           | nan                | nan              | 0.9999             | 0.0           | 0.0         | 0.9999        |
| 0.1242        | 60.0  | 60   | 0.1012          | 1.0      | 1.0           | 1.0              | nan                | nan              | 1.0                | nan           | nan         | 1.0           |
| 0.0887        | 80.0  | 80   | 0.0617          | 1.0      | 1.0           | 1.0              | nan                | nan              | 1.0                | nan           | nan         | 1.0           |
| 0.0696        | 100.0 | 100  | 0.0445          | 1.0      | 1.0           | 1.0              | nan                | nan              | 1.0                | nan           | nan         | 1.0           |
| 0.0634        | 120.0 | 120  | 0.0410          | 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
