---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: vit-focal-skin
  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. -->

# vit-focal-skin

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5830
- Accuracy: 0.8497
- F1: 0.8472
- Precision: 0.8527
- Recall: 0.8497

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1586        | 1.0   | 626  | 0.3295          | 0.8808   | 0.8764 | 0.9007    | 0.8808 |
| 0.096         | 2.0   | 1252 | 0.4315          | 0.8601   | 0.8562 | 0.8600    | 0.8601 |
| 0.0181        | 3.0   | 1878 | 0.4395          | 0.8756   | 0.8685 | 0.8799    | 0.8756 |
| 0.0058        | 4.0   | 2504 | 0.5563          | 0.8549   | 0.8571 | 0.8653    | 0.8549 |
| 0.0004        | 5.0   | 3130 | 0.6044          | 0.8653   | 0.8619 | 0.8688    | 0.8653 |
| 0.0003        | 6.0   | 3756 | 0.5830          | 0.8497   | 0.8472 | 0.8527    | 0.8497 |


### Framework versions

- Transformers 4.29.2
- Pytorch 1.13.1
- Datasets 2.14.5
- Tokenizers 0.13.3