---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: car_orientation_classification_zoomed
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# car_orientation_classification_zoomed

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: 0.6108
- Accuracy: 0.7597

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9887        | 1.0   | 68   | 1.9011          | 0.3463   |
| 1.4388        | 2.0   | 136  | 1.3001          | 0.4594   |
| 1.1799        | 3.0   | 204  | 1.1267          | 0.4841   |
| 1.0245        | 4.0   | 272  | 0.9695          | 0.5936   |
| 0.8203        | 5.0   | 340  | 0.8157          | 0.6890   |
| 0.7146        | 6.0   | 408  | 0.7898          | 0.6678   |
| 0.6137        | 7.0   | 476  | 0.6343          | 0.7420   |
| 0.5746        | 8.0   | 544  | 0.6351          | 0.7527   |
| 0.5316        | 9.0   | 612  | 0.5899          | 0.7986   |
| 0.5073        | 10.0  | 680  | 0.6193          | 0.7491   |
| 0.4854        | 11.0  | 748  | 0.5721          | 0.7845   |
| 0.4347        | 12.0  | 816  | 0.6495          | 0.7562   |
| 0.3937        | 13.0  | 884  | 0.6108          | 0.7597   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1