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# bhutanese_currency_model

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3152
- Accuracy: 0.975

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9781        | 1.0   | 20   | 1.8946          | 0.5844   |
| 1.5451        | 2.0   | 40   | 1.4346          | 0.8781   |
| 1.0404        | 3.0   | 60   | 0.9740          | 0.9281   |
| 0.7007        | 4.0   | 80   | 0.6779          | 0.9656   |
| 0.5091        | 5.0   | 100  | 0.4903          | 0.9781   |
| 0.3778        | 6.0   | 120  | 0.4151          | 0.9656   |
| 0.3274        | 7.0   | 140  | 0.3602          | 0.9812   |
| 0.2779        | 8.0   | 160  | 0.3155          | 0.9875   |
| 0.2644        | 9.0   | 180  | 0.2932          | 0.9812   |
| 0.2576        | 10.0  | 200  | 0.3152          | 0.975    |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1

label_0 label_1 label_2 label_3 label_4 label_5 label_6 label_7