---
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: 0.4871
- Accuracy: 0.8705
- F1: 0.8762
- Precision: 0.8862
- Recall: 0.8705

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1966        | 1.0   | 626  | 0.3647          | 0.8290   | 0.8307 | 0.8431    | 0.8290 |
| 0.1434        | 2.0   | 1252 | 0.3884          | 0.8238   | 0.8259 | 0.8418    | 0.8238 |
| 0.058         | 3.0   | 1878 | 0.5064          | 0.8187   | 0.8137 | 0.8183    | 0.8187 |
| 0.02          | 4.0   | 2504 | 0.5477          | 0.8394   | 0.8431 | 0.8538    | 0.8394 |
| 0.0018        | 5.0   | 3130 | 0.4876          | 0.8705   | 0.8749 | 0.8864    | 0.8705 |
| 0.0003        | 6.0   | 3756 | 0.4871          | 0.8705   | 0.8762 | 0.8862    | 0.8705 |


### Framework versions

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