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# image_classification

This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2697
- Accuracy: 0.5062

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.5374        | 1.0   | 10   | 2.2324          | 0.1688   |
| 1.9423        | 2.0   | 20   | 1.8484          | 0.35     |
| 1.6386        | 3.0   | 30   | 1.8398          | 0.3312   |
| 1.3437        | 4.0   | 40   | 1.4253          | 0.475    |
| 1.1703        | 5.0   | 50   | 1.4136          | 0.4625   |
| 1.0267        | 6.0   | 60   | 1.3867          | 0.4562   |
| 0.8702        | 7.0   | 70   | 1.2915          | 0.525    |
| 0.7696        | 8.0   | 80   | 1.2238          | 0.5687   |
| 0.6327        | 9.0   | 90   | 1.2732          | 0.5312   |
| 0.5017        | 10.0  | 100  | 1.2810          | 0.5188   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0

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