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# vit-base-patch16-224-Rado_5

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: 0.1831
- Accuracy: 0.9185

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.554         | 1.0   | 10   | 0.3765          | 0.8741   |
| 0.2117        | 2.0   | 20   | 0.2063          | 0.8963   |
| 0.1368        | 3.0   | 30   | 0.1797          | 0.9259   |
| 0.0953        | 4.0   | 40   | 0.2555          | 0.9037   |
| 0.0726        | 5.0   | 50   | 0.1396          | 0.9185   |
| 0.079         | 6.0   | 60   | 0.2110          | 0.9185   |
| 0.0622        | 7.0   | 70   | 0.1790          | 0.9259   |
| 0.0655        | 8.0   | 80   | 0.1837          | 0.9333   |
| 0.0736        | 9.0   | 90   | 0.1798          | 0.9259   |
| 0.0541        | 10.0  | 100  | 0.1831          | 0.9185   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1

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