transformers tensorboard safetensors vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-skin-demo-v3
  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-skin-demo-v3

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the skin-cancer dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4066
- Accuracy: 0.8517

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6938        | 0.31  | 100  | 0.9315          | 0.6523   |
| 0.7574        | 0.62  | 200  | 0.9532          | 0.6404   |
| 0.6163        | 0.93  | 300  | 0.6160          | 0.7728   |
| 0.4747        | 1.25  | 400  | 0.6093          | 0.7940   |
| 0.4771        | 1.56  | 500  | 0.6314          | 0.7772   |
| 0.5632        | 1.87  | 600  | 0.6300          | 0.7559   |
| 0.4049        | 2.18  | 700  | 0.4991          | 0.8146   |
| 0.5362        | 2.49  | 800  | 0.4934          | 0.8215   |
| 0.4617        | 2.8   | 900  | 0.4625          | 0.8390   |
| 0.2861        | 3.12  | 1000 | 0.4361          | 0.8464   |
| 0.3559        | 3.43  | 1100 | 0.4040          | 0.8608   |
| 0.2876        | 3.74  | 1200 | 0.3846          | 0.8702   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
