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# tsec_vit_model

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2717
- Accuracy: 0.8866

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4387        | 1.0   | 280  | 0.4179          | 0.8151   |
| 0.4239        | 2.0   | 560  | 0.3611          | 0.8399   |
| 0.3148        | 3.0   | 840  | 0.3156          | 0.8600   |
| 0.2988        | 4.0   | 1120 | 0.3002          | 0.8729   |
| 0.2498        | 5.0   | 1400 | 0.3087          | 0.8694   |
| 0.3028        | 6.0   | 1680 | 0.2966          | 0.8716   |
| 0.2179        | 7.0   | 1960 | 0.2742          | 0.8808   |
| 0.2274        | 8.0   | 2240 | 0.2861          | 0.8814   |
| 0.2195        | 9.0   | 2520 | 0.2626          | 0.8895   |
| 0.1886        | 10.0  | 2800 | 0.2717          | 0.8866   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1

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