---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Psoriasis-Project-M-beit-base-patch16-224-pt22k-ft22k
  results: []
---

<!-- 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. -->

# Psoriasis-Project-M-beit-base-patch16-224-pt22k-ft22k

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: 0.1695
- Accuracy: 0.9792

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 0.3253          | 0.8958   |
| 0.0442        | 2.0   | 13   | 0.2781          | 0.9167   |
| 0.0442        | 2.92  | 19   | 0.2423          | 0.9167   |
| 0.0205        | 4.0   | 26   | 0.2234          | 0.9375   |
| 0.0073        | 4.92  | 32   | 0.1979          | 0.9583   |
| 0.0073        | 6.0   | 39   | 0.1701          | 0.9792   |
| 0.0055        | 6.92  | 45   | 0.1599          | 0.9792   |
| 0.0071        | 8.0   | 52   | 0.1710          | 0.9792   |
| 0.0071        | 8.92  | 58   | 0.1704          | 0.9792   |
| 0.003         | 9.23  | 60   | 0.1695          | 0.9792   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2