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--- |
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license: apache-2.0 |
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base_model: microsoft/swin-large-patch4-window7-224 |
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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-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: 0.8227074235807861 |
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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-large |
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This model is a fine-tuned version of [microsoft/swin-large-patch4-window7-224](https://huggingface.co/microsoft/swin-large-patch4-window7-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7383 |
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- Accuracy: 0.8227 |
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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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| 1.4126 | 0.9840 | 46 | 0.9408 | 0.6882 | |
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| 0.3672 | 1.9893 | 93 | 0.6431 | 0.7703 | |
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| 0.133 | 2.9947 | 140 | 0.5938 | 0.7921 | |
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| 0.0624 | 4.0 | 187 | 0.6128 | 0.8035 | |
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| 0.0473 | 4.9840 | 233 | 0.6654 | 0.8114 | |
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| 0.0276 | 5.9893 | 280 | 0.7090 | 0.8166 | |
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| 0.0111 | 6.9947 | 327 | 0.7133 | 0.8140 | |
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| 0.0081 | 8.0 | 374 | 0.7639 | 0.8183 | |
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| 0.0039 | 8.9840 | 420 | 0.7387 | 0.8236 | |
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| 0.0065 | 9.8396 | 460 | 0.7383 | 0.8227 | |
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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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