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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-finalterm |
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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: 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: 0.9313077939233818 |
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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-finalterm |
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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: 0.1837 |
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- Accuracy: 0.9313 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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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| 1.2727 | 0.9684 | 23 | 0.5536 | 0.8336 | |
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| 0.3845 | 1.9789 | 47 | 0.2386 | 0.9115 | |
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| 0.2725 | 2.9895 | 71 | 0.2135 | 0.9234 | |
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| 0.2442 | 4.0 | 95 | 0.2291 | 0.9075 | |
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| 0.2097 | 4.9684 | 118 | 0.1964 | 0.9207 | |
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| 0.2237 | 5.9789 | 142 | 0.1920 | 0.9287 | |
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| 0.2199 | 6.9895 | 166 | 0.1844 | 0.9353 | |
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| 0.2209 | 8.0 | 190 | 0.1857 | 0.9273 | |
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| 0.1717 | 8.9684 | 213 | 0.1842 | 0.9313 | |
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| 0.1754 | 9.6842 | 230 | 0.1837 | 0.9313 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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