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# vit-base-patch16-224

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: 1.2817
- Accuracy: 0.7205

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8025        | 0.98  | 27   | 0.6852          | 0.6407   |
| 0.5648        | 1.98  | 54   | 0.7587          | 0.6971   |
| 0.2165        | 2.98  | 81   | 0.6410          | 0.7387   |
| 0.0587        | 3.98  | 108  | 1.9350          | 0.5682   |
| 0.041         | 4.98  | 135  | 0.9925          | 0.7348   |
| 0.013         | 5.98  | 162  | 1.3159          | 0.6980   |
| 0.025         | 6.98  | 189  | 1.4855          | 0.7456   |
| 0.0243        | 7.98  | 216  | 1.4230          | 0.7489   |
| 0.0016        | 8.98  | 243  | 1.2937          | 0.7117   |
| 0.0026        | 9.98  | 270  | 1.2817          | 0.7205   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2

imposter real