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Melanoma-Cancer-Image-Classification

Image Classification
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vit
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  1. README.md +9 -9
  2. model.safetensors +1 -1
  3. runs/Mar17_10-40-10_f48e69b0942e/events.out.tfevents.1710672011.f48e69b0942e.33.0 +2 -2
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.1974
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- - Accuracy: 0.9227
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  ## Model description
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.3901 | 0.99 | 68 | 0.2364 | 0.9064 |
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- | 0.2121 | 1.99 | 137 | 0.2138 | 0.9109 |
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- | 0.1789 | 3.0 | 206 | 0.2010 | 0.92 |
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- | 0.1528 | 3.96 | 272 | 0.1974 | 0.9227 |
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  ### Framework versions
 
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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: 0.1753
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+ - Accuracy: 0.9236
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  ## Model description
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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: 16
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+ - eval_batch_size: 16
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  - seed: 42
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  - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.3456 | 1.0 | 137 | 0.2080 | 0.9173 |
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+ | 0.1999 | 2.0 | 275 | 0.1894 | 0.9223 |
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+ | 0.1655 | 3.0 | 412 | 0.1801 | 0.9336 |
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+ | 0.1397 | 3.99 | 548 | 0.1753 | 0.9236 |
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  ### Framework versions
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