---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: vit-base-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-base-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: 0.4406
- Accuracy: 0.8705
- F1: 0.8724
- Precision: 0.8771
- 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5676        | 1.0   | 626  | 0.5088          | 0.8342   | 0.8242 | 0.8626    | 0.8342 |
| 0.4883        | 2.0   | 1252 | 0.4589          | 0.8446   | 0.8469 | 0.8512    | 0.8446 |
| 0.3582        | 3.0   | 1878 | 0.3833          | 0.8601   | 0.8594 | 0.8740    | 0.8601 |
| 0.0953        | 4.0   | 2504 | 0.4406          | 0.8705   | 0.8724 | 0.8771    | 0.8705 |


### Framework versions

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