---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: skin-lesion-vit-finetuned
  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. -->

# skin-lesion-vit-finetuned

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: 0.1761
- Accuracy: 0.9458
- F1 Macro: 0.9465
- Melanoma Recall: 0.9607

## 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: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1 Macro | Melanoma Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:---------------:|
| 0.7039        | 0.9983 | 299  | 0.7625          | 0.7335   | 0.6859   | 0.6             |
| 0.7119        | 2.0    | 599  | 0.4936          | 0.8327   | 0.7772   | 0.7536          |
| 0.4416        | 2.9983 | 898  | 0.4881          | 0.8287   | 0.8242   | 0.8036          |
| 0.3581        | 4.0    | 1198 | 0.4164          | 0.8616   | 0.8286   | 0.8929          |
| 0.2949        | 4.9983 | 1497 | 0.3000          | 0.9021   | 0.8916   | 0.8893          |
| 0.2687        | 6.0    | 1797 | 0.2685          | 0.9041   | 0.9206   | 0.95            |
| 0.1699        | 6.9983 | 2096 | 0.2058          | 0.9318   | 0.9346   | 0.9643          |
| 0.0908        | 7.9866 | 2392 | 0.1761          | 0.9458   | 0.9465   | 0.9607          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.11.0+cu128
- Datasets 2.21.0
- Tokenizers 0.19.1