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---
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
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