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# convnext-tiny-224-driverbox

This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0497
- Accuracy: 0.9880

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.3349        | 0.9950  | 99   | 0.2700          | 0.9328   |
| 0.2393        | 2.0     | 199  | 0.1932          | 0.9540   |
| 0.1831        | 2.9950  | 298  | 0.1403          | 0.9618   |
| 0.1397        | 4.0     | 398  | 0.1055          | 0.9689   |
| 0.0795        | 4.9950  | 497  | 0.1030          | 0.9731   |
| 0.0915        | 6.0     | 597  | 0.0966          | 0.9703   |
| 0.0718        | 6.9950  | 696  | 0.0779          | 0.9745   |
| 0.0502        | 8.0     | 796  | 0.0729          | 0.9788   |
| 0.0314        | 8.9950  | 895  | 0.0621          | 0.9802   |
| 0.0408        | 10.0    | 995  | 0.0758          | 0.9752   |
| 0.0335        | 10.9950 | 1094 | 0.0598          | 0.9823   |
| 0.0228        | 12.0    | 1194 | 0.0573          | 0.9823   |
| 0.0229        | 12.9950 | 1293 | 0.0473          | 0.9844   |
| 0.0119        | 14.0    | 1393 | 0.0642          | 0.9844   |
| 0.028         | 14.9950 | 1492 | 0.0526          | 0.9851   |
| 0.0117        | 16.0    | 1592 | 0.0594          | 0.9837   |
| 0.0187        | 16.9950 | 1691 | 0.0497          | 0.9880   |
| 0.0131        | 18.0    | 1791 | 0.0663          | 0.9837   |
| 0.0132        | 18.9950 | 1890 | 0.0478          | 0.9866   |
| 0.014         | 20.0    | 1990 | 0.0465          | 0.9880   |
| 0.0039        | 20.9950 | 2089 | 0.0496          | 0.9851   |
| 0.0102        | 22.0    | 2189 | 0.0468          | 0.9880   |
| 0.0035        | 22.9950 | 2288 | 0.0581          | 0.9866   |
| 0.0071        | 24.0    | 2388 | 0.0519          | 0.9866   |
| 0.0032        | 24.9950 | 2487 | 0.0510          | 0.9880   |
| 0.0049        | 26.0    | 2587 | 0.0575          | 0.9858   |
| 0.0037        | 26.9950 | 2686 | 0.0511          | 0.9880   |
| 0.0029        | 28.0    | 2786 | 0.0484          | 0.9880   |
| 0.0019        | 28.9950 | 2885 | 0.0523          | 0.9866   |
| 0.0058        | 29.8492 | 2970 | 0.0532          | 0.9866   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1

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