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Hemg
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Melanoma-Cancer-Image-Classification

Image Classification
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vit
Generated from Trainer
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  1. README.md +19 -7
  2. model.safetensors +1 -1
  3. runs/Mar17_11-00-51_f48e69b0942e/events.out.tfevents.1710673251.f48e69b0942e.33.1 +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: 0.1753
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- - Accuracy: 0.9236
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  ## Model description
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@@ -46,16 +46,28 @@ The following hyperparameters were used during training:
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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: 4
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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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- | 0.3456 | 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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  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: 0.2535
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+ - Accuracy: 0.9295
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  ## Model description
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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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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.4294 | 1.0 | 137 | 0.2553 | 0.8982 |
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+ | 0.2306 | 2.0 | 275 | 0.2277 | 0.9086 |
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+ | 0.1863 | 3.0 | 412 | 0.2013 | 0.9191 |
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+ | 0.1579 | 4.0 | 550 | 0.2061 | 0.9155 |
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+ | 0.1421 | 5.0 | 687 | 0.2080 | 0.9195 |
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+ | 0.1126 | 6.0 | 825 | 0.1900 | 0.9259 |
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+ | 0.0903 | 7.0 | 962 | 0.2054 | 0.9273 |
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+ | 0.0829 | 8.0 | 1100 | 0.2090 | 0.9286 |
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+ | 0.0677 | 9.0 | 1237 | 0.2242 | 0.9241 |
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+ | 0.0585 | 10.0 | 1375 | 0.2385 | 0.9218 |
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+ | 0.0524 | 11.0 | 1512 | 0.2440 | 0.9236 |
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+ | 0.0475 | 12.0 | 1650 | 0.2388 | 0.9268 |
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+ | 0.0367 | 13.0 | 1787 | 0.2407 | 0.9305 |
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+ | 0.033 | 14.0 | 1925 | 0.2500 | 0.9323 |
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+ | 0.0321 | 15.0 | 2062 | 0.2681 | 0.9277 |
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+ | 0.0316 | 15.94 | 2192 | 0.2535 | 0.9295 |
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  ### Framework versions
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