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Wound-Image-classification

Image Classification
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vit
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  1. README.md +17 -15
  2. model.safetensors +1 -1
  3. runs/Mar11_11-15-07_33467ebf2898/events.out.tfevents.1710155707.33467ebf2898.370.14 +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: 0.6986
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- - Accuracy: 0.8621
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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- - train_batch_size: 8
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- - eval_batch_size: 8
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  - seed: 42
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- - gradient_accumulation_steps: 4
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- - total_train_batch_size: 32
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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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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 2.0125 | 0.93 | 10 | 1.7330 | 0.3678 |
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- | 1.4438 | 1.95 | 21 | 1.4018 | 0.6552 |
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- | 1.0862 | 2.98 | 32 | 1.0609 | 0.7701 |
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- | 0.8369 | 4.0 | 43 | 0.8816 | 0.8736 |
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- | 0.7183 | 4.93 | 53 | 0.8076 | 0.8046 |
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- | 0.5529 | 5.95 | 64 | 0.7125 | 0.8506 |
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- | 0.4963 | 6.98 | 75 | 0.7001 | 0.8736 |
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- | 0.4974 | 7.44 | 80 | 0.6986 | 0.8621 |
 
 
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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: 0.5200
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+ - Accuracy: 0.8391
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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  - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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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: 10
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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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+ | 1.7226 | 1.0 | 43 | 1.3689 | 0.6207 |
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+ | 0.9553 | 2.0 | 86 | 0.8472 | 0.7586 |
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+ | 0.5832 | 3.0 | 129 | 0.5262 | 0.8621 |
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+ | 0.3948 | 4.0 | 172 | 0.4701 | 0.8621 |
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+ | 0.3127 | 5.0 | 215 | 0.5299 | 0.8506 |
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+ | 0.207 | 6.0 | 258 | 0.4629 | 0.8621 |
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+ | 0.191 | 7.0 | 301 | 0.5138 | 0.8391 |
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+ | 0.1679 | 8.0 | 344 | 0.4064 | 0.8621 |
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+ | 0.1968 | 9.0 | 387 | 0.3898 | 0.8851 |
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+ | 0.1485 | 10.0 | 430 | 0.5200 | 0.8391 |
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  ### Framework versions
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