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---
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: 0.0228
- Mean Iou: 1.0
- Mean Accuracy: 1.0
- Overall Accuracy: 1.0
- Accuracy Wht: 1.0
- Iou Wht: 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:-------:|
| 0.1064 | 1.0 | 270 | 0.0228 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|