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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: Wound-classification |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Wound-classification |
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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: 0.1836 |
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- Accuracy: 0.9575 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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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: 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: 0.01 |
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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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| 1.1241 | 1.0 | 200 | 0.7452 | 0.765 | |
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| 0.5854 | 2.0 | 400 | 0.4880 | 0.835 | |
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| 0.4279 | 3.0 | 600 | 0.5049 | 0.8375 | |
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| 0.4041 | 4.0 | 800 | 0.3321 | 0.8975 | |
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| 0.2805 | 5.0 | 1000 | 0.4105 | 0.895 | |
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| 0.279 | 6.0 | 1200 | 0.4269 | 0.8825 | |
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| 0.1782 | 7.0 | 1400 | 0.3583 | 0.905 | |
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| 0.1834 | 8.0 | 1600 | 0.3009 | 0.925 | |
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| 0.1197 | 9.0 | 1800 | 0.3020 | 0.93 | |
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| 0.1231 | 10.0 | 2000 | 0.3352 | 0.9225 | |
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| 0.1273 | 11.0 | 2200 | 0.2908 | 0.91 | |
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| 0.1019 | 12.0 | 2400 | 0.2528 | 0.94 | |
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| 0.0951 | 13.0 | 2600 | 0.2989 | 0.9325 | |
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| 0.0957 | 14.0 | 2800 | 0.3189 | 0.9325 | |
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| 0.0618 | 15.0 | 3000 | 0.1973 | 0.9475 | |
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| 0.0583 | 16.0 | 3200 | 0.1836 | 0.9575 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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