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# 0.50-200Train-100Test-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: 0.7055
- Accuracy: 0.8140

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.9228        | 0.9931 | 36   | 1.4677          | 0.5921   |
| 0.5728        | 1.9862 | 72   | 0.7717          | 0.7721   |
| 0.2216        | 2.9793 | 108  | 0.6836          | 0.7930   |
| 0.052         | 4.0    | 145  | 0.6623          | 0.8052   |
| 0.0145        | 4.9931 | 181  | 0.7002          | 0.7991   |
| 0.0075        | 5.9862 | 217  | 0.6851          | 0.8131   |
| 0.0059        | 6.9793 | 253  | 0.6920          | 0.8166   |
| 0.0045        | 8.0    | 290  | 0.6996          | 0.8140   |
| 0.004         | 8.9931 | 326  | 0.7044          | 0.8140   |
| 0.0042        | 9.9310 | 360  | 0.7055          | 0.8140   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1

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