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# vit-base-patch16-224-Diastar

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: 0.0730
- Accuracy: 0.9591

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4516        | 0.9939 | 123  | 0.2494          | 0.8957   |
| 0.2492        | 1.9960 | 247  | 0.1599          | 0.9324   |
| 0.2829        | 2.9980 | 371  | 0.1078          | 0.9461   |
| 0.211         | 4.0    | 495  | 0.0833          | 0.9532   |
| 0.2783        | 4.9939 | 618  | 0.0933          | 0.9514   |
| 0.2205        | 5.9960 | 742  | 0.0825          | 0.9520   |
| 0.1809        | 6.9980 | 866  | 0.0768          | 0.9526   |
| 0.1878        | 8.0    | 990  | 0.0786          | 0.9538   |
| 0.2291        | 8.9939 | 1113 | 0.0750          | 0.9549   |
| 0.1736        | 9.9394 | 1230 | 0.0730          | 0.9591   |


### Framework versions

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

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