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Hemg
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Wound-Image-classification

Image Classification
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TensorBoard
Safetensors
vit
Generated from Trainer
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  1. README.md +19 -7
  2. model.safetensors +1 -1
  3. runs/Mar12_06-36-08_ff168037f406/events.out.tfevents.1710225369.ff168037f406.34.3 +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: 0.3558
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- - Accuracy: 0.8929
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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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- | 1.3684 | 1.0 | 147 | 0.9023 | 0.7279 |
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- | 0.6318 | 2.0 | 294 | 0.7183 | 0.7772 |
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- | 0.412 | 3.0 | 441 | 0.4634 | 0.8554 |
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- | 0.2348 | 4.0 | 588 | 0.3558 | 0.8929 |
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.3576
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+ - Accuracy: 0.9167
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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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+ | 1.6946 | 1.0 | 147 | 1.1341 | 0.6973 |
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+ | 0.8288 | 2.0 | 294 | 0.7185 | 0.7806 |
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+ | 0.6119 | 3.0 | 441 | 0.5564 | 0.8163 |
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+ | 0.4444 | 4.0 | 588 | 0.5865 | 0.8197 |
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+ | 0.3407 | 5.0 | 735 | 0.6159 | 0.8163 |
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+ | 0.3009 | 6.0 | 882 | 0.5311 | 0.8452 |
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+ | 0.2226 | 7.0 | 1029 | 0.3886 | 0.8827 |
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+ | 0.1794 | 8.0 | 1176 | 0.5094 | 0.8707 |
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+ | 0.1942 | 9.0 | 1323 | 0.3530 | 0.8980 |
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+ | 0.1516 | 10.0 | 1470 | 0.3911 | 0.8929 |
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+ | 0.1352 | 11.0 | 1617 | 0.3265 | 0.9065 |
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+ | 0.0962 | 12.0 | 1764 | 0.2807 | 0.9286 |
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+ | 0.0972 | 13.0 | 1911 | 0.3031 | 0.9320 |
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+ | 0.0916 | 14.0 | 2058 | 0.2806 | 0.9371 |
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+ | 0.0725 | 15.0 | 2205 | 0.2893 | 0.9320 |
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+ | 0.067 | 16.0 | 2352 | 0.3576 | 0.9167 |
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  ### Framework versions
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