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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-original-10 |
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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: 0.9916476841305999 |
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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-original-10 |
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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: 0.0443 |
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- Accuracy: 0.9916 |
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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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| 5.6259 | 1.0 | 247 | 3.3200 | 0.3994 | |
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| 1.9734 | 2.0 | 494 | 0.5108 | 0.9370 | |
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| 0.6166 | 3.0 | 741 | 0.2288 | 0.9749 | |
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| 0.4348 | 4.0 | 988 | 0.1149 | 0.9858 | |
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| 0.2823 | 5.0 | 1235 | 0.0760 | 0.9899 | |
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| 0.2351 | 6.0 | 1482 | 0.0618 | 0.9906 | |
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| 0.1889 | 7.0 | 1729 | 0.0550 | 0.9894 | |
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| 0.1681 | 8.0 | 1976 | 0.0505 | 0.9901 | |
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| 0.144 | 9.0 | 2223 | 0.0446 | 0.9919 | |
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| 0.1248 | 10.0 | 2470 | 0.0443 | 0.9916 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.15.2 |
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