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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224 |
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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: 0.941747572815534 |
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- name: F1 |
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type: f1 |
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value: 0.9302325581395349 |
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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](https://huggingface.co/google/vit-base-patch16-224) on the stool-image dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4237 |
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- Auroc: 0.9418 |
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- Accuracy: 0.9417 |
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- Sensitivity: 0.9091 |
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- Specificty: 0.9661 |
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- Ppv: 0.9524 |
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- Npv: 0.9344 |
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- F1: 0.9302 |
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- Model Selection: 0.9215 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Auroc | Accuracy | Sensitivity | Specificty | Ppv | Npv | F1 | Model Selection | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:-----------:|:----------:|:------:|:------:|:------:|:---------------:| |
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| 0.5076 | 0.98 | 100 | 0.5361 | 0.8538 | 0.7731 | 0.5393 | 0.9801 | 0.96 | 0.7061 | 0.6906 | 0.5592 | |
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| 0.4086 | 1.96 | 200 | 0.4857 | 0.8728 | 0.7836 | 0.6011 | 0.9453 | 0.9068 | 0.7280 | 0.7230 | 0.6558 | |
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| 0.5208 | 2.94 | 300 | 0.5109 | 0.8059 | 0.7599 | 0.6124 | 0.8905 | 0.8321 | 0.7218 | 0.7055 | 0.7218 | |
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| 0.474 | 3.92 | 400 | 0.5212 | 0.8601 | 0.7995 | 0.6180 | 0.9602 | 0.9322 | 0.7395 | 0.7432 | 0.6578 | |
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| 0.4285 | 4.9 | 500 | 0.4511 | 0.8728 | 0.7757 | 0.7472 | 0.8010 | 0.7688 | 0.7816 | 0.7578 | 0.9462 | |
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| 0.3506 | 5.88 | 600 | 0.4716 | 0.8691 | 0.8047 | 0.6798 | 0.9154 | 0.8768 | 0.7635 | 0.7658 | 0.7644 | |
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| 0.4239 | 6.86 | 700 | 0.5043 | 0.8517 | 0.8100 | 0.6685 | 0.9353 | 0.9015 | 0.7611 | 0.7677 | 0.7332 | |
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| 0.2447 | 7.84 | 800 | 0.5804 | 0.8592 | 0.8074 | 0.6910 | 0.9104 | 0.8723 | 0.7689 | 0.7712 | 0.7806 | |
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| 0.1739 | 8.82 | 900 | 0.6225 | 0.8562 | 0.8074 | 0.7135 | 0.8905 | 0.8523 | 0.7783 | 0.7768 | 0.8229 | |
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| 0.2888 | 9.8 | 1000 | 0.5807 | 0.8570 | 0.8047 | 0.7528 | 0.8507 | 0.8171 | 0.7953 | 0.7836 | 0.9021 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.0.1 |
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- Datasets 2.14.7 |
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- Tokenizers 0.15.2 |
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