transformers tensorboard safetensors vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224-in21k license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-augment-v1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# vit-augment-v1

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 SkinCancerClassification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4269
- Accuracy: 0.8582

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6898        | 0.31  | 100  | 0.7782          | 0.7299   |
| 0.6945        | 0.62  | 200  | 0.7745          | 0.7459   |
| 0.8574        | 0.93  | 300  | 0.6510          | 0.7683   |
| 0.6146        | 1.25  | 400  | 0.6806          | 0.7594   |
| 0.5394        | 1.56  | 500  | 0.6110          | 0.7963   |
| 0.4653        | 1.87  | 600  | 0.6123          | 0.7903   |
| 0.4021        | 2.18  | 700  | 0.5375          | 0.8088   |
| 0.4112        | 2.49  | 800  | 0.5154          | 0.8088   |
| 0.4165        | 2.8   | 900  | 0.4868          | 0.8313   |
| 0.235         | 3.12  | 1000 | 0.4463          | 0.8437   |
| 0.1638        | 3.43  | 1100 | 0.4490          | 0.8527   |
| 0.3126        | 3.74  | 1200 | 0.4269          | 0.8582   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
