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--- |
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license: apache-2.0 |
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base_model: microsoft/swin-tiny-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: swin-tiny-patch4-window7-224-finetuned-piid |
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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: val |
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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: 0.7853881278538812 |
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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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# swin-tiny-patch4-window7-224-finetuned-piid |
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This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-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: 0.5715 |
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- Accuracy: 0.7854 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 20 |
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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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| 1.2088 | 0.98 | 20 | 1.1661 | 0.4521 | |
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| 0.7545 | 2.0 | 41 | 0.8866 | 0.6073 | |
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| 0.6281 | 2.98 | 61 | 0.7788 | 0.6849 | |
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| 0.5939 | 4.0 | 82 | 0.6443 | 0.7397 | |
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| 0.5254 | 4.98 | 102 | 0.5097 | 0.7808 | |
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| 0.5583 | 6.0 | 123 | 0.5715 | 0.7854 | |
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| 0.3463 | 6.98 | 143 | 0.6163 | 0.7352 | |
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| 0.3878 | 8.0 | 164 | 0.5671 | 0.7671 | |
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| 0.3653 | 8.98 | 184 | 0.5690 | 0.7580 | |
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| 0.3529 | 10.0 | 205 | 0.5940 | 0.7580 | |
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| 0.301 | 10.98 | 225 | 0.6303 | 0.7626 | |
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| 0.2639 | 12.0 | 246 | 0.5725 | 0.7763 | |
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| 0.2847 | 12.98 | 266 | 0.6280 | 0.7717 | |
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| 0.25 | 14.0 | 287 | 0.5975 | 0.7717 | |
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| 0.2472 | 14.98 | 307 | 0.5821 | 0.7671 | |
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| 0.1676 | 16.0 | 328 | 0.6456 | 0.7626 | |
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| 0.1327 | 16.98 | 348 | 0.6117 | 0.7671 | |
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| 0.1977 | 18.0 | 369 | 0.6988 | 0.7489 | |
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| 0.1602 | 18.98 | 389 | 0.6448 | 0.7671 | |
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| 0.1785 | 19.51 | 400 | 0.6333 | 0.7717 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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