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--- |
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license: apache-2.0 |
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base_model: microsoft/swinv2-base-patch4-window12-192-22k |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: Psoriasis-500-100aug-224-swinv2-base-patch4-window12-192-22k |
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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: imagefolder |
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type: imagefolder |
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config: default |
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split: validation |
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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: 0.8200873362445414 |
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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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# Psoriasis-500-100aug-224-swinv2-base-patch4-window12-192-22k |
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This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1589 |
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- Accuracy: 0.8201 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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| 0.5248 | 0.9973 | 92 | 0.7503 | 0.7694 | |
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| 0.2461 | 1.9946 | 184 | 0.8202 | 0.7764 | |
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| 0.1164 | 2.9919 | 276 | 0.8260 | 0.8052 | |
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| 0.0656 | 4.0 | 369 | 1.0366 | 0.7860 | |
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| 0.0525 | 4.9973 | 461 | 1.0025 | 0.8148 | |
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| 0.0223 | 5.9946 | 553 | 1.1363 | 0.7965 | |
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| 0.0022 | 6.9919 | 645 | 1.1911 | 0.8061 | |
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| 0.009 | 8.0 | 738 | 1.2139 | 0.7965 | |
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| 0.0073 | 8.9973 | 830 | 1.2066 | 0.8166 | |
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| 0.0014 | 9.9729 | 920 | 1.1589 | 0.8201 | |
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# Classification Report |
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| Class | Precision (%) | Recall (%) | F1-Score (%) | Support | |
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|---------------------|---------------|------------|--------------|---------| |
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| Abnormal | 68 | 67 | 67 | 108 | |
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| Erythrodermic | 99 | 75 | 85 | 100 | |
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| Guttate | 94 | 84 | 89 | 114 | |
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| Inverse | 88 | 93 | 90 | 108 | |
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| Nail | 88 | 86 | 87 | 99 | |
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| Normal | 84 | 87 | 85 | 82 | |
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| Not Define | 98 | 99 | 98 | 92 | |
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| Palm Soles | 80 | 80 | 80 | 102 | |
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| Plaque | 73 | 92 | 81 | 84 | |
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| Psoriatic Arthritis | 88 | 75 | 81 | 104 | |
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| Pustular | 76 | 86 | 80 | 112 | |
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| Scalp | 86 | 94 | 90 | 80 | |
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| **Accuracy** | | | **84** | 1185 | |
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| **Macro Avg** | **85** | **85** | **84** | 1185 | |
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| **Weighted Avg** | **85** | **84** | **84** | 1185 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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