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# image_classification

This model is a fine-tuned version of [google/vit-large-patch32-384](https://huggingface.co/google/vit-large-patch32-384) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8452
- Accuracy: 0.3

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1828        | 1.0   | 20   | 2.1899          | 0.1125   |
| 2.1419        | 2.0   | 40   | 2.1018          | 0.1625   |
| 2.078         | 3.0   | 60   | 2.1286          | 0.1625   |
| 2.0943        | 4.0   | 80   | 2.1462          | 0.15     |
| 2.0486        | 5.0   | 100  | 2.0665          | 0.2      |
| 1.9442        | 6.0   | 120  | 1.9868          | 0.2562   |
| 1.9307        | 7.0   | 140  | 1.9403          | 0.2375   |
| 1.8743        | 8.0   | 160  | 1.8866          | 0.275    |
| 1.7348        | 9.0   | 180  | 1.7927          | 0.3312   |
| 1.6455        | 10.0  | 200  | 1.7579          | 0.3187   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0

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