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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-sealv1 |
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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: validation |
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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: 0.9119804400977995 |
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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-sealv1 |
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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: 0.2553 |
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- Accuracy: 0.9120 |
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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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| 1.1068 | 0.95 | 14 | 0.6518 | 0.7066 | |
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| 0.4912 | 1.97 | 29 | 0.4668 | 0.8435 | |
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| 0.2749 | 2.98 | 44 | 0.4127 | 0.8704 | |
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| 0.3189 | 4.0 | 59 | 0.3626 | 0.8875 | |
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| 0.2226 | 4.95 | 73 | 0.2638 | 0.9046 | |
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| 0.2394 | 5.97 | 88 | 0.3584 | 0.8802 | |
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| 0.2241 | 6.98 | 103 | 0.2821 | 0.9046 | |
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| 0.1815 | 8.0 | 118 | 0.2138 | 0.9218 | |
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| 0.1862 | 8.95 | 132 | 0.2738 | 0.9046 | |
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| 0.1942 | 9.49 | 140 | 0.2553 | 0.9120 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 1.10.2+cu113 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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