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-v4
  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-v4

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: 0.5370
- Accuracy: 0.8352

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5373        | 1.0   | 321  | 0.6221          | 0.8034   |
| 0.2539        | 2.0   | 642  | 0.5164          | 0.8371   |
| 0.3277        | 3.0   | 963  | 0.5526          | 0.8408   |
| 0.2998        | 4.0   | 1284 | 0.5685          | 0.8315   |
| 0.0924        | 5.0   | 1605 | 0.5767          | 0.8414   |
| 0.0877        | 6.0   | 1926 | 0.6067          | 0.8564   |
| 0.1197        | 7.0   | 2247 | 0.6659          | 0.8683   |
| 0.046         | 8.0   | 2568 | 0.6573          | 0.8652   |
| 0.0581        | 9.0   | 2889 | 0.6949          | 0.8652   |
| 0.0021        | 10.0  | 3210 | 0.7187          | 0.8720   |


### Framework versions

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