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# S2_M1_R1_ViT_42618522

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: 0.0114
- Accuracy: 0.9987

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0551        | 1.0   | 231  | 0.0058          | 0.9987   |
| 0.0032        | 2.0   | 463  | 0.0181          | 0.9962   |
| 0.008         | 3.0   | 694  | 0.0099          | 0.9987   |
| 0.0002        | 4.0   | 926  | 0.0181          | 0.9974   |
| 0.0           | 4.99  | 1155 | 0.0114          | 0.9987   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.3

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