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# 2025-01-21-16-13-04-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: 0.0188
- Precision: 0.9929
- Recall: 0.9926
- F1: 0.9926
- Accuracy: 0.9931
- Top1 Accuracy: 0.9926
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|
| 0.7465        | 1.0   | 34   | 0.1092          | 0.9536    | 0.9407 | 0.9400 | 0.9366   | 0.9407        | 0.0634     |
| 0.212         | 2.0   | 68   | 0.2754          | 0.9338    | 0.9111 | 0.9061 | 0.9049   | 0.9111        | 0.0951     |
| 0.115         | 3.0   | 102  | 0.0534          | 0.9854    | 0.9852 | 0.9852 | 0.9851   | 0.9852        | 0.0149     |
| 0.0723        | 4.0   | 136  | 0.0188          | 0.9929    | 0.9926 | 0.9926 | 0.9931   | 0.9926        | 0.0069     |
| 0.0716        | 5.0   | 170  | 0.0195          | 0.9928    | 0.9926 | 0.9926 | 0.992    | 0.9926        | 0.0080     |
| 0.0161        | 6.0   | 204  | 0.0389          | 0.9791    | 0.9778 | 0.9778 | 0.9775   | 0.9778        | 0.0225     |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3

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