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# Train-Test-Augmentation-V6-beit-large

This model is a fine-tuned version of [microsoft/beit-large-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-large-patch16-224-pt22k-ft22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6235
- Accuracy: 0.8521

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0299        | 1.0   | 57   | 0.8461          | 0.7798   |
| 0.0202        | 2.0   | 114  | 0.7776          | 0.8137   |
| 0.0148        | 3.0   | 171  | 0.7231          | 0.8120   |
| 0.004         | 4.0   | 228  | 0.6273          | 0.8481   |
| 0.0004        | 5.0   | 285  | 0.6235          | 0.8521   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

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