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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: skin_decease |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: test |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9871794871794872 |
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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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# skin_decease |
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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 the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0680 |
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- Accuracy: 0.9872 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 8 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 0.2359 | 0.8621 | 100 | 0.2427 | 0.9744 | |
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| 0.086 | 1.7241 | 200 | 0.1178 | 0.9872 | |
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| 0.0435 | 2.5862 | 300 | 0.0801 | 0.9872 | |
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| 0.0312 | 3.4483 | 400 | 0.0748 | 0.9872 | |
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| 0.023 | 4.3103 | 500 | 0.0715 | 0.9872 | |
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| 0.0197 | 5.1724 | 600 | 0.0696 | 0.9872 | |
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| 0.0174 | 6.0345 | 700 | 0.0687 | 0.9872 | |
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| 0.0161 | 6.8966 | 800 | 0.0684 | 0.9872 | |
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| 0.0151 | 7.7586 | 900 | 0.0680 | 0.9872 | |
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### Framework versions |
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- Transformers 4.43.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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