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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: vit-base-skin |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# vit-base-skin |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6272 |
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- Accuracy: 0.8549 |
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- F1: 0.8558 |
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- Precision: 0.8590 |
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- Recall: 0.8549 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.4385 | 1.0 | 626 | 0.4796 | 0.8290 | 0.8273 | 0.8726 | 0.8290 | |
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| 0.3573 | 2.0 | 1252 | 0.4745 | 0.8549 | 0.8581 | 0.8651 | 0.8549 | |
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| 0.1444 | 3.0 | 1878 | 0.6086 | 0.8394 | 0.8406 | 0.8440 | 0.8394 | |
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| 0.0055 | 4.0 | 2504 | 0.6272 | 0.8549 | 0.8558 | 0.8590 | 0.8549 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 1.13.1 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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