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# results

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.0673
- eval_model_preparation_time: 0.003
- eval_accuracy: {'accuracy': 0.16875}
- eval_runtime: 22.6244
- eval_samples_per_second: 7.072
- eval_steps_per_second: 0.442
- step: 0

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 3

### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.3.2
- Tokenizers 0.21.0

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