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Melanoma-Cancer-Image-Classification

Image Classification
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TensorBoard
Safetensors
vit
Generated from Trainer
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  1. README.md +11 -7
  2. model.safetensors +1 -1
  3. runs/Mar18_05-08-55_d7163b31276a/events.out.tfevents.1710738536.d7163b31276a.34.4 +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: 0.2146
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- - Accuracy: 0.9145
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  ## Model description
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@@ -46,17 +46,21 @@ 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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  - mixed_precision_training: Native AMP
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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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- | 0.4225 | 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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  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: 0.1937
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+ - Accuracy: 0.9264
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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: 8
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  - mixed_precision_training: Native AMP
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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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+ | 0.4884 | 0.99 | 68 | 0.2696 | 0.8923 |
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+ | 0.2361 | 1.99 | 137 | 0.2285 | 0.905 |
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+ | 0.1927 | 3.0 | 206 | 0.2121 | 0.9182 |
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+ | 0.1673 | 4.0 | 275 | 0.2066 | 0.9114 |
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+ | 0.1498 | 4.99 | 343 | 0.2038 | 0.9209 |
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+ | 0.1243 | 5.99 | 412 | 0.1965 | 0.9218 |
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+ | 0.1106 | 7.0 | 481 | 0.1829 | 0.9318 |
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+ | 0.1095 | 7.91 | 544 | 0.1937 | 0.9264 |
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  ### Framework versions
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