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--- |
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license: apache-2.0 |
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base_model: microsoft/swinv2-base-patch4-window16-256 |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: SwinV2-Base-Document-Classifier |
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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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# SwinV2-Base-Document-Classifier |
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This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window16-256](https://huggingface.co/microsoft/swinv2-base-patch4-window16-256) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0573 |
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- Accuracy: 0.9810 |
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- F1: 0.9810 |
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- Precision: 0.9813 |
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- Recall: 0.9810 |
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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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- training_steps: 400 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.0814 | 0.12 | 50 | 0.0876 | 0.9740 | 0.9741 | 0.9749 | 0.9740 | |
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| 0.078 | 0.13 | 51 | 0.0658 | 0.9797 | 0.9797 | 0.9799 | 0.9797 | |
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| 0.143 | 0.13 | 52 | 0.0609 | 0.9831 | 0.9831 | 0.9832 | 0.9831 | |
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| 0.0863 | 0.13 | 53 | 0.0595 | 0.9832 | 0.9832 | 0.9834 | 0.9832 | |
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| 0.0561 | 0.14 | 54 | 0.0650 | 0.9825 | 0.9825 | 0.9826 | 0.9825 | |
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| 0.1118 | 0.14 | 55 | 0.0697 | 0.9804 | 0.9804 | 0.9806 | 0.9804 | |
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| 0.1258 | 0.14 | 56 | 0.1053 | 0.9678 | 0.9678 | 0.9697 | 0.9678 | |
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| 0.132 | 0.14 | 57 | 0.0672 | 0.9781 | 0.9781 | 0.9785 | 0.9781 | |
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| 0.1564 | 0.14 | 58 | 0.0582 | 0.9827 | 0.9827 | 0.9829 | 0.9827 | |
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| 0.1085 | 0.15 | 59 | 0.0557 | 0.9849 | 0.9848 | 0.9849 | 0.9848 | |
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| 0.0506 | 0.15 | 60 | 0.0548 | 0.9845 | 0.9845 | 0.9845 | 0.9845 | |
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| 0.0787 | 0.15 | 61 | 0.1049 | 0.9660 | 0.9661 | 0.9681 | 0.9660 | |
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| 0.1211 | 0.15 | 62 | 0.0792 | 0.9741 | 0.9741 | 0.9746 | 0.9741 | |
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| 0.0907 | 0.16 | 63 | 0.0608 | 0.9826 | 0.9825 | 0.9826 | 0.9826 | |
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| 0.0419 | 0.16 | 64 | 0.0577 | 0.9832 | 0.9832 | 0.9833 | 0.9832 | |
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| 0.1659 | 0.16 | 65 | 0.0548 | 0.9843 | 0.9843 | 0.9844 | 0.9843 | |
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| 0.0983 | 0.17 | 66 | 0.0657 | 0.9805 | 0.9805 | 0.9814 | 0.9804 | |
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| 0.0535 | 0.17 | 67 | 0.0493 | 0.9851 | 0.9851 | 0.9851 | 0.9851 | |
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| 0.0936 | 0.17 | 68 | 0.0588 | 0.9827 | 0.9827 | 0.9830 | 0.9827 | |
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| 0.0933 | 0.17 | 69 | 0.0573 | 0.9810 | 0.9810 | 0.9813 | 0.9810 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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