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# Train-Test-Augmentation-V44-beit-base

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5318
- Accuracy: 0.8142

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.6031        | 0.9825 | 28   | 0.9362          | 0.7132   |
| 0.5124        | 2.0    | 57   | 0.6364          | 0.7933   |
| 0.2676        | 2.9825 | 85   | 0.5382          | 0.8125   |
| 0.1263        | 4.0    | 114  | 0.5486          | 0.8114   |
| 0.0833        | 4.9123 | 140  | 0.5318          | 0.8142   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1

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