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# vehicle_multiclass_classification

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: 0.0151
- Accuracy: 0.9952

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0389        | 1.0   | 245  | 0.0542          | 0.9857   |
| 0.0006        | 2.0   | 490  | 0.0453          | 0.9905   |
| 0.0003        | 3.0   | 735  | 0.0525          | 0.9845   |
| 0.0002        | 4.0   | 980  | 0.0519          | 0.9857   |
| 0.0001        | 5.0   | 1225 | 0.0523          | 0.9857   |
| 0.0001        | 6.0   | 1470 | 0.0529          | 0.9857   |
| 0.0001        | 7.0   | 1715 | 0.0534          | 0.9857   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3

label_0 label_1 label_2 label_3 label_4 label_5 label_6