---
base_model: mividia/mit-b2
tags:
- retouch
- image-segmentation
- generated_from_trainer
model-index:
- name: testing_303
  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. -->

# testing_303

This model is a fine-tuned version of [mividia/mit-b2](https://huggingface.co/mividia/mit-b2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0
- Mean Iou: nan
- Mean Accuracy: nan
- Overall Accuracy: nan
- Accuracy Wht: nan
- Iou Wht: nan

## 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: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Wht | Iou Wht |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:-------:|
| 0.0           | 1.0   | 270  | 0.0             | nan      | nan           | nan              | nan          | nan     |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3