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# 0.50-500Train-100Test-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: 0.7076
- Accuracy: 0.8515

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.2287        | 0.9973 | 92   | 0.6058          | 0.8157   |
| 0.1191        | 1.9946 | 184  | 0.7659          | 0.8070   |
| 0.0311        | 2.9919 | 276  | 0.6945          | 0.8271   |
| 0.0076        | 4.0    | 369  | 0.7174          | 0.8437   |
| 0.0012        | 4.9864 | 460  | 0.7076          | 0.8515   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1

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