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# test2

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8384
- Accuracy: 0.75

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 1.1029          | 0.125    |
| No log        | 2.0   | 2    | 1.0384          | 0.625    |
| No log        | 3.0   | 3    | 0.9989          | 0.75     |
| No log        | 4.0   | 4    | 0.9557          | 0.75     |
| No log        | 5.0   | 5    | 0.8941          | 0.75     |
| No log        | 6.0   | 6    | 0.8952          | 0.75     |
| No log        | 7.0   | 7    | 0.8669          | 0.75     |
| No log        | 8.0   | 8    | 0.8705          | 0.75     |
| No log        | 9.0   | 9    | 0.8357          | 0.75     |
| 0.4538        | 10.0  | 10   | 0.8384          | 0.75     |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1

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