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# results

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0466
- Accuracy: 0.9967

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2698        | 1.0   | 57   | 0.7910          | 0.9567   |
| 0.1238        | 2.0   | 114  | 0.1673          | 0.99     |
| 0.0269        | 3.0   | 171  | 0.0869          | 0.9967   |
| 0.0096        | 4.0   | 228  | 0.0634          | 0.9967   |
| 0.0059        | 5.0   | 285  | 0.0569          | 0.9967   |
| 0.0049        | 6.0   | 342  | 0.0524          | 0.9967   |
| 0.0043        | 7.0   | 399  | 0.0495          | 0.9967   |
| 0.0036        | 8.0   | 456  | 0.0479          | 0.9967   |
| 0.0036        | 9.0   | 513  | 0.0469          | 0.9967   |
| 0.0032        | 10.0  | 570  | 0.0466          | 0.9967   |


### Framework versions

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

label_0 label_1 label_2 label_3 label_4 label_5 label_6 label_7 label_8 label_9 label_10 label_11 label_12 label_13 label_14 label_15 label_16 label_17 label_18 label_19 label_20 label_21 label_22 label_23 label_24 label_25 label_26 label_27 label_28 label_29