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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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metrics: |
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- accuracy |
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model-index: |
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- name: Main_fashion-swin |
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results: [] |
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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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# Main_fashion-swin |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7830 |
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- Accuracy: 0.7053 |
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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: 12 |
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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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| 2.019 | 0.9630 | 13 | 1.7204 | 0.3805 | |
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| 1.646 | 2.0 | 27 | 1.2356 | 0.5940 | |
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| 0.9911 | 2.9630 | 40 | 0.9948 | 0.6821 | |
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| 0.9104 | 4.0 | 54 | 0.9069 | 0.6775 | |
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| 0.8337 | 4.9630 | 67 | 0.8472 | 0.6961 | |
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| 0.7425 | 6.0 | 81 | 0.8436 | 0.6891 | |
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| 0.6625 | 6.9630 | 94 | 0.8257 | 0.6937 | |
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| 0.6814 | 8.0 | 108 | 0.8274 | 0.6914 | |
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| 0.6445 | 8.9630 | 121 | 0.7940 | 0.7053 | |
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| 0.6032 | 10.0 | 135 | 0.8015 | 0.7030 | |
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| 0.6231 | 10.9630 | 148 | 0.7825 | 0.7077 | |
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| 0.6337 | 11.5556 | 156 | 0.7830 | 0.7053 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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