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# mammals_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: 0.2452
- Accuracy: 0.9496

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5501        | 1.0   | 394  | 0.3697          | 0.9207   |
| 0.0757        | 2.0   | 788  | 0.2894          | 0.9311   |
| 0.034         | 3.0   | 1182 | 0.2865          | 0.9304   |
| 0.0043        | 4.0   | 1576 | 0.2610          | 0.9385   |
| 0.0024        | 5.0   | 1970 | 0.2526          | 0.9415   |
| 0.0007        | 6.0   | 2364 | 0.2452          | 0.9496   |
| 0.0006        | 7.0   | 2758 | 0.2432          | 0.9481   |
| 0.0004        | 8.0   | 3152 | 0.2442          | 0.9481   |
| 0.0004        | 9.0   | 3546 | 0.2484          | 0.9496   |
| 0.0003        | 10.0  | 3940 | 0.2545          | 0.9467   |
| 0.0003        | 11.0  | 4334 | 0.2543          | 0.9481   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3

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