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# 0.50-500Train-100Test-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: 0.7300
- Accuracy: 0.8262

## 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: 7

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4603        | 0.9973 | 92   | 0.6572          | 0.7782   |
| 0.223         | 1.9946 | 184  | 0.6184          | 0.7956   |
| 0.0749        | 2.9919 | 276  | 0.6076          | 0.8262   |
| 0.0218        | 4.0    | 369  | 0.7377          | 0.8140   |
| 0.0082        | 4.9973 | 461  | 0.7851          | 0.8061   |
| 0.0023        | 5.9946 | 553  | 0.7284          | 0.8227   |
| 0.0037        | 6.9810 | 644  | 0.7300          | 0.8262   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1

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