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# vit-base-patch16-224-9models

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0167
- Accuracy: 0.9959

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5952        | 0.9790 | 35   | 0.2206          | 0.9344   |
| 0.1228        | 1.9860 | 71   | 0.0889          | 0.9754   |
| 0.1133        | 2.9930 | 107  | 0.0701          | 0.9816   |
| 0.0877        | 4.0    | 143  | 0.0808          | 0.9754   |
| 0.0597        | 4.9790 | 178  | 0.0234          | 0.9939   |
| 0.0718        | 5.9860 | 214  | 0.0325          | 0.9898   |
| 0.0666        | 6.9930 | 250  | 0.0459          | 0.9836   |
| 0.0467        | 8.0    | 286  | 0.0162          | 0.9959   |
| 0.0446        | 8.9790 | 321  | 0.0155          | 0.9959   |
| 0.0391        | 9.7902 | 350  | 0.0167          | 0.9959   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1

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