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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-teeth_dataset |
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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: 0.8391304347826087 |
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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-teeth_dataset |
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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: 1.1564 |
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- Accuracy: 0.8391 |
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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: 50 |
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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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| No log | 0.8 | 3 | 4.5796 | 0.0152 | |
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| No log | 1.87 | 7 | 4.5200 | 0.0261 | |
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| 4.5616 | 2.93 | 11 | 4.4705 | 0.0326 | |
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| 4.5616 | 4.0 | 15 | 4.4127 | 0.0674 | |
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| 4.5616 | 4.8 | 18 | 4.3493 | 0.0804 | |
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| 4.44 | 5.87 | 22 | 4.2425 | 0.1130 | |
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| 4.44 | 6.93 | 26 | 4.1107 | 0.1370 | |
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| 4.1823 | 8.0 | 30 | 3.9340 | 0.1609 | |
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| 4.1823 | 8.8 | 33 | 3.7821 | 0.1935 | |
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| 4.1823 | 9.87 | 37 | 3.5314 | 0.2783 | |
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| 3.6357 | 10.93 | 41 | 3.2857 | 0.3043 | |
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| 3.6357 | 12.0 | 45 | 3.1064 | 0.3696 | |
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| 3.6357 | 12.8 | 48 | 2.9713 | 0.3826 | |
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| 3.0041 | 13.87 | 52 | 2.7172 | 0.4870 | |
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| 3.0041 | 14.93 | 56 | 2.5111 | 0.5435 | |
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| 2.4604 | 16.0 | 60 | 2.3561 | 0.5696 | |
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| 2.4604 | 16.8 | 63 | 2.2684 | 0.5717 | |
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| 2.4604 | 17.87 | 67 | 2.0961 | 0.6348 | |
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| 1.971 | 18.93 | 71 | 1.9555 | 0.6783 | |
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| 1.971 | 20.0 | 75 | 1.8400 | 0.6891 | |
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| 1.971 | 20.8 | 78 | 1.7856 | 0.7239 | |
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| 1.651 | 21.87 | 82 | 1.6797 | 0.7370 | |
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| 1.651 | 22.93 | 86 | 1.6007 | 0.7717 | |
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| 1.3665 | 24.0 | 90 | 1.5256 | 0.7739 | |
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| 1.3665 | 24.8 | 93 | 1.4876 | 0.7652 | |
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| 1.3665 | 25.87 | 97 | 1.4395 | 0.7783 | |
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| 1.1954 | 26.93 | 101 | 1.3679 | 0.7870 | |
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| 1.1954 | 28.0 | 105 | 1.3043 | 0.8022 | |
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| 1.1954 | 28.8 | 108 | 1.2906 | 0.8022 | |
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| 0.9886 | 29.87 | 112 | 1.2313 | 0.8109 | |
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| 0.9886 | 30.93 | 116 | 1.1829 | 0.8348 | |
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| 0.8803 | 32.0 | 120 | 1.1564 | 0.8391 | |
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| 0.8803 | 32.8 | 123 | 1.1421 | 0.8304 | |
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| 0.8803 | 33.87 | 127 | 1.1144 | 0.8326 | |
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| 0.815 | 34.93 | 131 | 1.1074 | 0.8304 | |
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| 0.815 | 36.0 | 135 | 1.0919 | 0.8283 | |
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| 0.815 | 36.8 | 138 | 1.0821 | 0.8326 | |
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| 0.7619 | 37.87 | 142 | 1.0701 | 0.8348 | |
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| 0.7619 | 38.93 | 146 | 1.0642 | 0.8348 | |
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| 0.6991 | 40.0 | 150 | 1.0631 | 0.8391 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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