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--- |
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license: apache-2.0 |
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base_model: microsoft/beit-large-patch16-224-pt22k |
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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-beit-large |
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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: 0.7991266375545851 |
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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-beit-large |
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This model is a fine-tuned version of [microsoft/beit-large-patch16-224-pt22k](https://huggingface.co/microsoft/beit-large-patch16-224-pt22k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1823 |
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- Accuracy: 0.7991 |
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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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| 0.8236 | 0.9973 | 92 | 1.1536 | 0.6358 | |
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| 0.4282 | 1.9946 | 184 | 0.8848 | 0.7389 | |
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| 0.2305 | 2.9919 | 276 | 0.9811 | 0.7258 | |
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| 0.1206 | 4.0 | 369 | 0.8858 | 0.7808 | |
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| 0.1107 | 4.9973 | 461 | 1.1129 | 0.7397 | |
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| 0.0319 | 5.9946 | 553 | 1.1625 | 0.7703 | |
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| 0.0073 | 6.9919 | 645 | 1.1938 | 0.7895 | |
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| 0.0078 | 8.0 | 738 | 1.3031 | 0.7790 | |
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| 0.0013 | 8.9973 | 830 | 1.2117 | 0.7974 | |
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| 0.002 | 9.9729 | 920 | 1.1823 | 0.7991 | |
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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 | 66 | 62 | 64 | 108 | |
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| Erythrodermic | 96 | 76 | 85 | 100 | |
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| Guttate | 95 | 83 | 89 | 114 | |
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| Inverse | 83 | 91 | 87 | 108 | |
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| Nail | 81 | 84 | 83 | 99 | |
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| Normal | 81 | 79 | 80 | 82 | |
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| Not Define | 98 | 95 | 96 | 92 | |
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| Palm Soles | 82 | 88 | 85 | 102 | |
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| Plaque | 70 | 88 | 78 | 84 | |
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| Psoriatic Arthritis | 78 | 74 | 76 | 104 | |
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| Pustular | 71 | 76 | 74 | 112 | |
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| Scalp | 84 | 86 | 85 | 80 | |
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| **Accuracy** | | | **82** | 1185 | |
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| **Macro Avg** | **82** | **82** | **82** | 1185 | |
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| **Weighted Avg** | **82** | **82** | **82** | 1185 | |
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--- |
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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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