
# vit-base-patch16-224-in21k_male_or_female_eyes

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0810
- Accuracy: 0.9727
- F1: 0.9741
- Recall: 0.9666
- Precision: 0.9818

## Model description

This is a binary classification model to distinguish between male and female eyes.

For more information on how it was created, check out the following link: https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Computer%20Vision/Image%20Classification/Binary%20Classification/Male%20or%20Female%20Eyes/are_they_male_or_female_eyes_ViT.ipynb

## Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

## Training and evaluation data

Dataset Source: https://www.kaggle.com/datasets/pavelbiz/eyes-rtte

_Sample Images From Dataset:_

![Sample Images](https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/raw/main/Computer%20Vision/Image%20Classification/Binary%20Classification/Male%20or%20Female%20Eyes/Images/Sample%20Images.png)

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.1998        | 1.0   | 577  | 0.2365          | 0.9072   | 0.9196 | 0.9976 | 0.8530    |
| 0.0846        | 2.0   | 1154 | 0.0810          | 0.9727   | 0.9741 | 0.9666 | 0.9818    |
| 0.0309        | 3.0   | 1731 | 0.0852          | 0.9809   | 0.9821 | 0.9837 | 0.9805    |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.12.1
female_eyes male_eyes