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# Train-Augmentation-vit-base

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: 0.9262
- Accuracy: 0.7866

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6254        | 0.99  | 93   | 0.8623          | 0.7194   |
| 0.2129        | 2.0   | 187  | 0.7057          | 0.7510   |
| 0.0877        | 2.99  | 280  | 0.8545          | 0.7194   |
| 0.0164        | 4.0   | 374  | 0.9221          | 0.7549   |
| 0.0057        | 4.99  | 467  | 0.8149          | 0.7708   |
| 0.0021        | 6.0   | 561  | 0.8764          | 0.7866   |
| 0.0016        | 6.99  | 654  | 0.9059          | 0.7905   |
| 0.0013        | 8.0   | 748  | 0.9132          | 0.7866   |
| 0.0011        | 8.99  | 841  | 0.9236          | 0.7866   |
| 0.0013        | 9.95  | 930  | 0.9262          | 0.7866   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.15.2

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