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Wound-Image-classification

Image Classification
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vit
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  1. README.md +35 -19
  2. runs/Mar12_07-01-24_ff168037f406/events.out.tfevents.1710226885.ff168037f406.34.4 +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: 0.3576
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- - Accuracy: 0.9167
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  ## Model description
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@@ -46,28 +46,44 @@ 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: 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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  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: 0.2278
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+ - Accuracy: 0.9524
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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: 32
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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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+ | 1.8831 | 1.0 | 147 | 1.2970 | 0.6531 |
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+ | 0.9115 | 2.0 | 294 | 0.8685 | 0.7143 |
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+ | 0.6506 | 3.0 | 441 | 0.7251 | 0.7653 |
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+ | 0.5561 | 4.0 | 588 | 0.6598 | 0.7959 |
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+ | 0.4606 | 5.0 | 735 | 0.6454 | 0.7806 |
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+ | 0.3946 | 6.0 | 882 | 0.5916 | 0.8282 |
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+ | 0.3433 | 7.0 | 1029 | 0.5672 | 0.8265 |
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+ | 0.281 | 8.0 | 1176 | 0.6194 | 0.8265 |
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+ | 0.2735 | 9.0 | 1323 | 0.4681 | 0.8571 |
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+ | 0.2452 | 10.0 | 1470 | 0.4842 | 0.8673 |
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+ | 0.2358 | 11.0 | 1617 | 0.4283 | 0.8776 |
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+ | 0.1693 | 12.0 | 1764 | 0.4548 | 0.8759 |
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+ | 0.1715 | 13.0 | 1911 | 0.5153 | 0.8724 |
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+ | 0.159 | 14.0 | 2058 | 0.3161 | 0.9184 |
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+ | 0.1557 | 15.0 | 2205 | 0.4901 | 0.8861 |
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+ | 0.1137 | 16.0 | 2352 | 0.4257 | 0.9031 |
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+ | 0.1239 | 17.0 | 2499 | 0.3844 | 0.9031 |
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+ | 0.1426 | 18.0 | 2646 | 0.3769 | 0.8980 |
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+ | 0.128 | 19.0 | 2793 | 0.3641 | 0.9082 |
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+ | 0.1168 | 20.0 | 2940 | 0.3241 | 0.9133 |
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+ | 0.1139 | 21.0 | 3087 | 0.2318 | 0.9320 |
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+ | 0.0975 | 22.0 | 3234 | 0.3019 | 0.9286 |
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+ | 0.0989 | 23.0 | 3381 | 0.2984 | 0.9269 |
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+ | 0.0847 | 24.0 | 3528 | 0.2930 | 0.9201 |
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+ | 0.0659 | 25.0 | 3675 | 0.3112 | 0.9371 |
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+ | 0.0789 | 26.0 | 3822 | 0.2835 | 0.9354 |
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+ | 0.0432 | 27.0 | 3969 | 0.3100 | 0.9303 |
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+ | 0.0438 | 28.0 | 4116 | 0.3168 | 0.9320 |
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+ | 0.0371 | 29.0 | 4263 | 0.2361 | 0.9490 |
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+ | 0.039 | 30.0 | 4410 | 0.2714 | 0.9473 |
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+ | 0.0435 | 31.0 | 4557 | 0.2547 | 0.9524 |
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+ | 0.0512 | 32.0 | 4704 | 0.2278 | 0.9524 |
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  ### Framework versions
runs/Mar12_07-01-24_ff168037f406/events.out.tfevents.1710226885.ff168037f406.34.4 CHANGED
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