
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Train-Test-Augmentation-V5-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: 0.6899
- Accuracy: 0.8442

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0473        | 1.0   | 55   | 0.8312          | 0.7759   |
| 0.3767        | 2.0   | 110  | 0.5476          | 0.8336   |
| 0.176         | 3.0   | 165  | 0.5248          | 0.8256   |
| 0.07          | 4.0   | 220  | 0.5597          | 0.8527   |
| 0.043         | 5.0   | 275  | 0.5707          | 0.8472   |
| 0.0272        | 6.0   | 330  | 0.6225          | 0.8264   |
| 0.0168        | 7.0   | 385  | 0.5721          | 0.8553   |
| 0.0076        | 8.0   | 440  | 0.5967          | 0.8608   |
| 0.006         | 9.0   | 495  | 0.7036          | 0.8272   |
| 0.007         | 10.0  | 550  | 0.7167          | 0.8400   |
| 0.0048        | 11.0  | 605  | 0.6734          | 0.8506   |
| 0.0023        | 12.0  | 660  | 0.7424          | 0.8332   |
| 0.0032        | 13.0  | 715  | 0.7283          | 0.8340   |
| 0.002         | 14.0  | 770  | 0.6805          | 0.8502   |
| 0.0021        | 15.0  | 825  | 0.6899          | 0.8442   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.15.2

erythrodermic guttate inverse nail normal not define palm soles plaque psoriatic arthritis pustular scalp upnormal