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# image_classification

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:
- Loss: 1.5890
- Accuracy: 0.5062

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 10   | 2.0332          | 0.25     |
| No log        | 2.0   | 20   | 1.9720          | 0.3125   |
| No log        | 3.0   | 30   | 1.8937          | 0.3688   |
| No log        | 4.0   | 40   | 1.8265          | 0.375    |
| No log        | 5.0   | 50   | 1.7561          | 0.3937   |
| No log        | 6.0   | 60   | 1.7083          | 0.45     |
| No log        | 7.0   | 70   | 1.6719          | 0.4375   |
| No log        | 8.0   | 80   | 1.6415          | 0.4688   |
| No log        | 9.0   | 90   | 1.6237          | 0.4813   |
| No log        | 10.0  | 100  | 1.6041          | 0.4938   |
| No log        | 11.0  | 110  | 1.5890          | 0.5062   |
| No log        | 12.0  | 120  | 1.5774          | 0.5      |
| No log        | 13.0  | 130  | 1.5700          | 0.5      |
| No log        | 14.0  | 140  | 1.5659          | 0.5062   |
| No log        | 15.0  | 150  | 1.5643          | 0.5062   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1

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