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# art_classifier

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: 0.6729
- Accuracy: 0.8868

## 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        | 0.8571 | 3    | 1.0830          | 0.3962   |
| No log        | 2.0    | 7    | 1.0106          | 0.6415   |
| 1.0286        | 2.8571 | 10   | 0.9347          | 0.8302   |
| 1.0286        | 4.0    | 14   | 0.8509          | 0.8679   |
| 1.0286        | 4.8571 | 17   | 0.7853          | 0.8868   |
| 0.7956        | 6.0    | 21   | 0.7458          | 0.8868   |
| 0.7956        | 6.8571 | 24   | 0.7045          | 0.8679   |
| 0.7956        | 8.0    | 28   | 0.6863          | 0.8868   |
| 0.6554        | 8.5714 | 30   | 0.6729          | 0.8868   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1

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