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Wound-Image-classification

Image Classification
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Safetensors
vit
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  1. README.md +17 -17
  2. runs/Mar12_04-36-17_ff168037f406/events.out.tfevents.1710218178.ff168037f406.34.0 +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: 0.5200
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- - Accuracy: 0.8391
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  ## Model description
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  ### Training hyperparameters
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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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  | 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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  - Transformers 4.38.2
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- - Pytorch 2.1.0+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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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: 0.2590
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+ - Accuracy: 0.9167
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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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: 2
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+ - total_train_batch_size: 16
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.5856 | 1.0 | 147 | 1.2463 | 0.6122 |
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+ | 0.7971 | 2.0 | 294 | 0.7495 | 0.7551 |
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+ | 0.5344 | 3.0 | 441 | 0.5892 | 0.7925 |
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+ | 0.4006 | 4.0 | 588 | 0.5291 | 0.8452 |
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+ | 0.2778 | 5.0 | 735 | 0.3742 | 0.8759 |
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+ | 0.2501 | 6.0 | 882 | 0.3946 | 0.8895 |
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+ | 0.1444 | 7.0 | 1029 | 0.3125 | 0.9031 |
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+ | 0.1396 | 8.0 | 1176 | 0.3348 | 0.9150 |
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+ | 0.1231 | 9.0 | 1323 | 0.2848 | 0.9116 |
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+ | 0.0975 | 10.0 | 1470 | 0.2590 | 0.9167 |
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  ### Framework versions
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  - Transformers 4.38.2
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+ - Pytorch 2.1.2
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
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