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Hemg
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Melanoma-Cancer-Image-Classification

Image Classification
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Safetensors
vit
Generated from Trainer
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  1. README.md +9 -9
  2. model.safetensors +1 -1
  3. runs/Mar18_04-52-27_d7163b31276a/events.out.tfevents.1710737548.d7163b31276a.34.3 +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: 0.2035
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- - Accuracy: 0.9205
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-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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- | 0.3754 | 1.0 | 137 | 0.2462 | 0.9009 |
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- | 0.2061 | 2.0 | 275 | 0.2359 | 0.9095 |
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- | 0.1735 | 3.0 | 412 | 0.2003 | 0.9245 |
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- | 0.1517 | 3.99 | 548 | 0.2035 | 0.9205 |
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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: 0.2146
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+ - Accuracy: 0.9145
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-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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+ | 0.4225 | 0.99 | 68 | 0.2532 | 0.9041 |
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+ | 0.2251 | 1.99 | 137 | 0.2278 | 0.9136 |
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+ | 0.1924 | 3.0 | 206 | 0.2215 | 0.9155 |
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+ | 0.1748 | 3.96 | 272 | 0.2146 | 0.9145 |
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  ### Framework versions
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