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README.md ADDED
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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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+ metrics:
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+ - accuracy
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+ - recall
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+ - f1
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+ - precision
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+ model-index:
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+ - name: vit-base-16-thesis-demo-ISIC-multi-class
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+ results: []
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+ ---
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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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+
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+ # vit-base-16-thesis-demo-ISIC-multi-class
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+
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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: 0.0906
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+ - Accuracy: 0.9748
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+ - Recall: 0.9748
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+ - F1: 0.9748
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+ - Precision: 0.9748
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 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: 4
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1 | Precision |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
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+ | 0.575 | 0.98 | 50 | 0.4132 | 0.8491 | 0.8491 | 0.8491 | 0.8491 |
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+ | 0.2771 | 1.96 | 100 | 0.2329 | 0.9182 | 0.9182 | 0.9182 | 0.9182 |
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+ | 0.1703 | 2.94 | 150 | 0.1821 | 0.9497 | 0.9497 | 0.9497 | 0.9497 |
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+ | 0.1186 | 3.92 | 200 | 0.0906 | 0.9748 | 0.9748 | 0.9748 | 0.9748 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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