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# vit-base-patch16-224-finetuned-landscape-test

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1536
- Accuracy: 0.9524

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8077        | 0.9684 | 23   | 0.2954          | 0.9273   |
| 0.2325        | 1.9789 | 47   | 0.1675          | 0.9445   |
| 0.1987        | 2.9895 | 71   | 0.1601          | 0.9511   |
| 0.1641        | 4.0    | 95   | 0.1565          | 0.9498   |
| 0.1497        | 4.8421 | 115  | 0.1536          | 0.9524   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1

cnv dme drusen normal