---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-images
  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-images

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the marmal88/skin_cancer dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0918
- Accuracy: 0.981

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8785        | 0.4   | 100  | 0.7795          | 0.711    |
| 0.7076        | 0.8   | 200  | 0.5421          | 0.818    |
| 0.4283        | 1.2   | 300  | 0.3951          | 0.876    |
| 0.4251        | 1.6   | 400  | 0.3818          | 0.864    |
| 0.335         | 2.0   | 500  | 0.2474          | 0.924    |
| 0.2286        | 2.4   | 600  | 0.1675          | 0.952    |
| 0.1523        | 2.8   | 700  | 0.1641          | 0.954    |
| 0.1346        | 3.2   | 800  | 0.1120          | 0.969    |
| 0.0638        | 3.6   | 900  | 0.1025          | 0.978    |
| 0.0574        | 4.0   | 1000 | 0.0918          | 0.981    |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1