---
license: apache-2.0
tags:
- generated_from_trainer
- image-classification
- vision
base_model: google/vit-base-patch16-224-in21k
metrics:
- accuracy
model-index:
- name: skincare-detection
  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. -->

# skincare-detection

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4840
- Accuracy: 0.8648

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3961        | 0.99  | 61   | 0.5629          | 0.7725   |
| 0.4982        | 2.0   | 123  | 0.3991          | 0.8435   |
| 0.3563        | 2.99  | 184  | 0.4330          | 0.8272   |
| 0.2314        | 4.0   | 246  | 0.3969          | 0.8554   |
| 0.1815        | 4.99  | 307  | 0.4492          | 0.8435   |
| 0.1332        | 6.0   | 369  | 0.4474          | 0.8580   |
| 0.0869        | 6.99  | 430  | 0.4520          | 0.8631   |
| 0.0844        | 8.0   | 492  | 0.4469          | 0.8640   |
| 0.0681        | 8.99  | 553  | 0.4533          | 0.8717   |
| 0.0574        | 10.0  | 615  | 0.4952          | 0.8597   |
| 0.0477        | 10.99 | 676  | 0.4772          | 0.8674   |
| 0.0454        | 11.9  | 732  | 0.4840          | 0.8648   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.17.1
- Tokenizers 0.15.2