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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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- image-classification |
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- generated_from_trainer |
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datasets: |
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- generator |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: stool-condition-classification |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: stool-image |
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type: generator |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8171064604185623 |
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- name: F1 |
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type: f1 |
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value: 0.7841031149301826 |
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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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# stool-condition-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 the stool-image dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4538 |
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- Auroc: 0.8897 |
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- Accuracy: 0.8171 |
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- Sensitivity: 0.8111 |
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- Specificty: 0.8213 |
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- F1: 0.7841 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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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- num_epochs: 100 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Auroc | Accuracy | Sensitivity | Specificty | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:-----------:|:----------:|:------:| |
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| 0.5303 | 0.98 | 100 | 0.4327 | 0.8826 | 0.7942 | 0.7191 | 0.8607 | 0.7665 | |
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| 0.3909 | 1.96 | 200 | 0.5196 | 0.8675 | 0.8047 | 0.8539 | 0.7612 | 0.8042 | |
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| 0.5328 | 2.94 | 300 | 0.4421 | 0.8864 | 0.8074 | 0.7528 | 0.8557 | 0.7859 | |
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| 0.4834 | 3.92 | 400 | 0.4721 | 0.8596 | 0.7757 | 0.7135 | 0.8308 | 0.7493 | |
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| 0.4209 | 4.9 | 500 | 0.4797 | 0.8625 | 0.7863 | 0.6798 | 0.8806 | 0.7492 | |
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| 0.4567 | 5.88 | 600 | 0.5150 | 0.8688 | 0.7942 | 0.6011 | 0.9652 | 0.7329 | |
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### Framework versions |
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- Transformers 4.36.1 |
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- Pytorch 2.0.1 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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