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# vit-base-church-demo-v5

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 сhurch_data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0623
- Accuracy: 0.9863

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0649        | 0.68  | 100  | 0.0800          | 0.9795   |
| 0.0116        | 1.37  | 200  | 0.0623          | 0.9863   |
| 0.0112        | 2.05  | 300  | 0.0985          | 0.9795   |
| 0.005         | 2.74  | 400  | 0.0716          | 0.9898   |
| 0.0043        | 3.42  | 500  | 0.0715          | 0.9898   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2

byzantine classicism gothic novgorod_pskov