
<!-- 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. -->

# vit-diabetic-retinopathy-classification

This model is a fine-tuned version of [Kontawat/vit-diabetic-retinopathy-classification](https://huggingface.co/Kontawat/vit-diabetic-retinopathy-classification) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0460
- Accuracy: 0.7287

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5645        | 0.94  | 100  | 0.7731          | 0.7239   |
| 0.3971        | 1.89  | 200  | 0.8123          | 0.7038   |
| 0.3239        | 2.83  | 300  | 0.8204          | 0.7239   |
| 0.2178        | 3.77  | 400  | 0.9085          | 0.7204   |
| 0.18          | 4.72  | 500  | 1.0284          | 0.7310   |
| 0.0501        | 5.66  | 600  | 1.0460          | 0.7287   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2

0 1 2 3 4