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# 0.50-800Train-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: 0.7501
- Accuracy: 0.8192

## 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: 16
- total_train_batch_size: 512
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7627        | 0.9536 | 18   | 0.6991          | 0.7860   |
| 0.3414        | 1.9603 | 37   | 0.5881          | 0.8070   |
| 0.1402        | 2.9669 | 56   | 0.5879          | 0.8114   |
| 0.0663        | 3.9735 | 75   | 0.6249          | 0.8175   |
| 0.0377        | 4.9801 | 94   | 0.6539          | 0.8210   |
| 0.0314        | 5.9868 | 113  | 0.7074          | 0.8175   |
| 0.0189        | 6.9934 | 132  | 0.7596          | 0.8210   |
| 0.0147        | 8.0    | 151  | 0.7211          | 0.8253   |
| 0.0157        | 8.9536 | 169  | 0.7412          | 0.8166   |
| 0.0095        | 9.5364 | 180  | 0.7501          | 0.8192   |


### Framework versions

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

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