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# car_orientation_classification2

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6800
- Accuracy: 0.6926

## 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9933        | 1.0   | 68   | 1.9084          | 0.4099   |
| 1.4721        | 2.0   | 136  | 1.2870          | 0.5124   |
| 1.1677        | 3.0   | 204  | 1.0780          | 0.5265   |
| 0.9919        | 4.0   | 272  | 0.9454          | 0.5760   |
| 0.8392        | 5.0   | 340  | 0.8184          | 0.6926   |
| 0.7778        | 6.0   | 408  | 0.8311          | 0.6431   |
| 0.7341        | 7.0   | 476  | 0.7425          | 0.6572   |
| 0.6695        | 8.0   | 544  | 0.6800          | 0.6926   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1

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