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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: vit-base-skin
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-base-skin
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6272
- Accuracy: 0.8549
- F1: 0.8558
- Precision: 0.8590
- Recall: 0.8549
## 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: 16
- 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 | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4385 | 1.0 | 626 | 0.4796 | 0.8290 | 0.8273 | 0.8726 | 0.8290 |
| 0.3573 | 2.0 | 1252 | 0.4745 | 0.8549 | 0.8581 | 0.8651 | 0.8549 |
| 0.1444 | 3.0 | 1878 | 0.6086 | 0.8394 | 0.8406 | 0.8440 | 0.8394 |
| 0.0055 | 4.0 | 2504 | 0.6272 | 0.8549 | 0.8558 | 0.8590 | 0.8549 |
### Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1
- Datasets 2.14.5
- Tokenizers 0.13.3
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