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# finetuned-blurr-nonblur

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: 0.2435
- Accuracy: 0.9241

## 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: 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6486        | 1.0   | 14   | 0.6255          | 0.6646   |
| 0.552         | 2.0   | 28   | 0.5737          | 0.6772   |
| 0.4207        | 3.0   | 42   | 0.5175          | 0.7975   |
| 0.3545        | 4.0   | 56   | 0.4484          | 0.8861   |
| 0.2082        | 5.0   | 70   | 0.3621          | 0.8861   |
| 0.167         | 6.0   | 84   | 0.2930          | 0.9051   |
| 0.176         | 7.0   | 98   | 0.3003          | 0.8861   |
| 0.1275        | 8.0   | 112  | 0.2435          | 0.9241   |
| 0.11          | 9.0   | 126  | 0.2581          | 0.9051   |
| 0.1009        | 10.0  | 140  | 0.2474          | 0.9114   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2

blurr non blurr