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# 2025-02-05-14-22-36-vit-base-patch16-224

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0410
- Precision: 0.9931
- Recall: 0.9927
- F1: 0.9927
- Accuracy: 0.9931
- Top1 Accuracy: 0.9927
- Error Rate: 0.0069

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 3407
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Top1 Accuracy | Error Rate |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|
| 0.9229        | 1.0   | 103  | 0.2079          | 0.9541    | 0.9366 | 0.9386 | 0.9333   | 0.9366        | 0.0667     |
| 0.1707        | 2.0   | 206  | 0.1222          | 0.9726    | 0.9707 | 0.9688 | 0.9664   | 0.9707        | 0.0336     |
| 0.0937        | 3.0   | 309  | 0.1807          | 0.9552    | 0.9512 | 0.9505 | 0.9561   | 0.9512        | 0.0439     |
| 0.0619        | 4.0   | 412  | 0.1122          | 0.9764    | 0.9756 | 0.9754 | 0.9778   | 0.9756        | 0.0222     |
| 0.0309        | 5.0   | 515  | 0.0803          | 0.9884    | 0.9878 | 0.9875 | 0.9863   | 0.9878        | 0.0137     |
| 0.0275        | 6.0   | 618  | 0.0437          | 0.9904    | 0.9902 | 0.9902 | 0.9905   | 0.9902        | 0.0095     |
| 0.0103        | 7.0   | 721  | 0.0426          | 0.9905    | 0.9902 | 0.9903 | 0.9908   | 0.9902        | 0.0092     |
| 0.0065        | 8.0   | 824  | 0.0414          | 0.9953    | 0.9951 | 0.9951 | 0.9949   | 0.9951        | 0.0051     |
| 0.004         | 9.0   | 927  | 0.0410          | 0.9931    | 0.9927 | 0.9927 | 0.9931   | 0.9927        | 0.0069     |
| 0.0007        | 10.0  | 1030 | 0.0416          | 0.9953    | 0.9951 | 0.9951 | 0.9949   | 0.9951        | 0.0051     |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.20.3

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