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Wound-Image-classification

Image Classification
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vit
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  1. README.md +12 -67
  2. model.safetensors +1 -1
  3. runs/Mar12_09-22-32_ff168037f406/events.out.tfevents.1710235353.ff168037f406.34.6 +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: 0.2844
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- - Accuracy: 0.9524
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  ## Model description
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@@ -46,76 +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: 64
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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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- | 2.0494 | 1.0 | 147 | 1.6122 | 0.5612 |
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- | 1.1533 | 2.0 | 294 | 0.9492 | 0.7330 |
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- | 0.7367 | 3.0 | 441 | 0.6831 | 0.8129 |
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- | 0.5485 | 4.0 | 588 | 0.6085 | 0.8112 |
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- | 0.4602 | 5.0 | 735 | 0.6417 | 0.8010 |
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- | 0.4421 | 6.0 | 882 | 0.6718 | 0.7806 |
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- | 0.4397 | 7.0 | 1029 | 0.5751 | 0.8248 |
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- | 0.3958 | 8.0 | 1176 | 0.4965 | 0.8503 |
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- | 0.3675 | 9.0 | 1323 | 0.4673 | 0.8571 |
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- | 0.3292 | 10.0 | 1470 | 0.5529 | 0.8248 |
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- | 0.2941 | 11.0 | 1617 | 0.3971 | 0.8759 |
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- | 0.23 | 12.0 | 1764 | 0.6137 | 0.8469 |
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- | 0.239 | 13.0 | 1911 | 0.5268 | 0.8588 |
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- | 0.2151 | 14.0 | 2058 | 0.4803 | 0.8759 |
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- | 0.2418 | 15.0 | 2205 | 0.4425 | 0.8605 |
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- | 0.1874 | 16.0 | 2352 | 0.4986 | 0.8571 |
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- | 0.2018 | 17.0 | 2499 | 0.4748 | 0.8878 |
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- | 0.1967 | 18.0 | 2646 | 0.3726 | 0.9065 |
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- | 0.1679 | 19.0 | 2793 | 0.4188 | 0.8912 |
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- | 0.167 | 20.0 | 2940 | 0.5495 | 0.8537 |
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- | 0.1584 | 21.0 | 3087 | 0.3908 | 0.9048 |
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- | 0.1569 | 22.0 | 3234 | 0.4526 | 0.8980 |
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- | 0.171 | 23.0 | 3381 | 0.4073 | 0.8844 |
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- | 0.1615 | 24.0 | 3528 | 0.4611 | 0.8759 |
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- | 0.1471 | 25.0 | 3675 | 0.3808 | 0.9048 |
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- | 0.1401 | 26.0 | 3822 | 0.4670 | 0.9014 |
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- | 0.1213 | 27.0 | 3969 | 0.4816 | 0.8844 |
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- | 0.1162 | 28.0 | 4116 | 0.4832 | 0.8827 |
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- | 0.1125 | 29.0 | 4263 | 0.4539 | 0.8929 |
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- | 0.109 | 30.0 | 4410 | 0.3661 | 0.9133 |
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- | 0.0996 | 31.0 | 4557 | 0.3400 | 0.9201 |
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- | 0.0973 | 32.0 | 4704 | 0.3441 | 0.9099 |
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- | 0.1181 | 33.0 | 4851 | 0.3713 | 0.9167 |
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- | 0.0903 | 34.0 | 4998 | 0.3351 | 0.9252 |
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- | 0.1021 | 35.0 | 5145 | 0.4256 | 0.9048 |
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- | 0.0682 | 36.0 | 5292 | 0.3798 | 0.9235 |
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- | 0.1128 | 37.0 | 5439 | 0.3761 | 0.9099 |
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- | 0.0851 | 38.0 | 5586 | 0.3434 | 0.9218 |
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- | 0.0838 | 39.0 | 5733 | 0.3656 | 0.9184 |
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- | 0.0746 | 40.0 | 5880 | 0.3743 | 0.9235 |
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- | 0.0776 | 41.0 | 6027 | 0.3182 | 0.9371 |
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- | 0.0727 | 42.0 | 6174 | 0.3861 | 0.9269 |
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- | 0.0839 | 43.0 | 6321 | 0.3226 | 0.9303 |
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- | 0.0619 | 44.0 | 6468 | 0.3421 | 0.9303 |
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- | 0.0689 | 45.0 | 6615 | 0.3497 | 0.9286 |
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- | 0.0603 | 46.0 | 6762 | 0.2965 | 0.9371 |
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- | 0.0492 | 47.0 | 6909 | 0.3269 | 0.9354 |
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- | 0.0552 | 48.0 | 7056 | 0.3348 | 0.9473 |
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- | 0.0501 | 49.0 | 7203 | 0.3621 | 0.9303 |
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- | 0.0708 | 50.0 | 7350 | 0.3247 | 0.9371 |
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- | 0.0596 | 51.0 | 7497 | 0.2823 | 0.9405 |
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- | 0.0463 | 52.0 | 7644 | 0.3110 | 0.9371 |
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- | 0.0438 | 53.0 | 7791 | 0.3717 | 0.9286 |
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- | 0.0348 | 54.0 | 7938 | 0.3130 | 0.9388 |
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- | 0.0384 | 55.0 | 8085 | 0.2841 | 0.9456 |
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- | 0.0551 | 56.0 | 8232 | 0.3086 | 0.9456 |
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- | 0.0353 | 57.0 | 8379 | 0.2653 | 0.9490 |
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- | 0.0456 | 58.0 | 8526 | 0.3161 | 0.9269 |
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- | 0.0238 | 59.0 | 8673 | 0.2408 | 0.9558 |
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- | 0.0244 | 60.0 | 8820 | 0.2389 | 0.9558 |
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- | 0.0333 | 61.0 | 8967 | 0.2798 | 0.9473 |
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- | 0.0274 | 62.0 | 9114 | 0.2832 | 0.9456 |
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- | 0.0259 | 63.0 | 9261 | 0.2414 | 0.9507 |
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- | 0.0223 | 64.0 | 9408 | 0.2844 | 0.9524 |
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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: 0.3796
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+ - Accuracy: 0.8912
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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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+ | 1.6735 | 1.0 | 147 | 1.0660 | 0.7160 |
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+ | 0.8271 | 2.0 | 294 | 0.7849 | 0.7381 |
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+ | 0.5955 | 3.0 | 441 | 0.6233 | 0.7976 |
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+ | 0.4502 | 4.0 | 588 | 0.5057 | 0.8469 |
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+ | 0.3554 | 5.0 | 735 | 0.5081 | 0.8418 |
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+ | 0.2961 | 6.0 | 882 | 0.4161 | 0.8929 |
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+ | 0.2378 | 7.0 | 1029 | 0.4914 | 0.8656 |
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+ | 0.2063 | 8.0 | 1176 | 0.4416 | 0.8673 |
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+ | 0.2074 | 9.0 | 1323 | 0.3796 | 0.8912 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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