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# finetuned-bank-images

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: 0.4629
- Accuracy: 0.9125

## 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: 160
- eval_batch_size: 32
- seed: 42
- 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
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8836        | 1.1765 | 100  | 0.6595          | 0.8818   |
| 0.681         | 2.3529 | 200  | 0.5422          | 0.8965   |
| 0.5669        | 3.5294 | 300  | 0.4629          | 0.9125   |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.4.1
- Datasets 3.2.0
- Tokenizers 0.21.0

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