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# vit-finetuned-1

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: 1.2750
- Accuracy: 0.5

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 0.1575          | 1.0      |
| No log        | 2.0   | 2    | 0.1166          | 1.0      |
| No log        | 3.0   | 3    | 0.2496          | 1.0      |
| No log        | 4.0   | 4    | 0.4093          | 0.5      |
| No log        | 5.0   | 5    | 0.6732          | 0.5      |
| No log        | 6.0   | 6    | 0.9200          | 0.5      |
| No log        | 7.0   | 7    | 1.0925          | 0.5      |
| No log        | 8.0   | 8    | 1.1963          | 0.5      |
| No log        | 9.0   | 9    | 1.2521          | 0.5      |
| No log        | 10.0  | 10   | 1.2750          | 0.5      |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1+cpu
- Datasets 3.1.0
- Tokenizers 0.20.1

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