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Melanoma-Cancer-Image-Classification

Image Classification
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vit
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  1. README.md +79 -0
  2. model.safetensors +1 -1
  3. runs/Mar12_02-45-38_bcfc62ceb3a9/events.out.tfevents.1710211539.bcfc62ceb3a9.34.0 +2 -2
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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+ model-index:
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+ - name: Melanoma-Cancer-Image-Classification
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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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+ # Melanoma-Cancer-Image-Classification
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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: 0.2301
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+ - Accuracy: 0.9272
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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: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 16
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.5231 | 1.0 | 74 | 0.2938 | 0.8822 |
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+ | 0.2544 | 1.99 | 148 | 0.2562 | 0.8956 |
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+ | 0.2214 | 2.99 | 222 | 0.2421 | 0.8910 |
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+ | 0.1882 | 4.0 | 297 | 0.2090 | 0.9112 |
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+ | 0.1584 | 5.0 | 371 | 0.2186 | 0.9125 |
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+ | 0.1328 | 5.99 | 445 | 0.2061 | 0.9192 |
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+ | 0.1123 | 6.99 | 519 | 0.2157 | 0.9184 |
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+ | 0.0982 | 8.0 | 594 | 0.2007 | 0.9259 |
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+ | 0.0868 | 9.0 | 668 | 0.2206 | 0.9297 |
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+ | 0.0738 | 9.99 | 742 | 0.2263 | 0.9209 |
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+ | 0.0666 | 10.99 | 816 | 0.2197 | 0.9268 |
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+ | 0.0604 | 12.0 | 891 | 0.2050 | 0.9306 |
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+ | 0.0527 | 13.0 | 965 | 0.2288 | 0.9259 |
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+ | 0.0488 | 13.99 | 1039 | 0.2543 | 0.9251 |
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+ | 0.0461 | 14.99 | 1113 | 0.2289 | 0.9322 |
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+ | 0.0387 | 15.95 | 1184 | 0.2301 | 0.9272 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.1.2
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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