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--- |
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license: apache-2.0 |
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base_model: mansee/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-img_orientation |
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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: 0.9644592530889907 |
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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-img_orientation |
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This model is a fine-tuned version of [mansee/swin-tiny-patch4-window7-224](https://huggingface.co/mansee/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: 0.1069 |
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- Accuracy: 0.9645 |
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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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| 0.5605 | 1.0 | 506 | 0.3984 | 0.8341 | |
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| 0.3828 | 2.0 | 1013 | 0.1944 | 0.9271 | |
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| 0.3092 | 3.0 | 1519 | 0.1862 | 0.9339 | |
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| 0.3234 | 4.0 | 2026 | 0.1415 | 0.9510 | |
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| 0.2471 | 5.0 | 2532 | 0.1355 | 0.9517 | |
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| 0.251 | 6.0 | 3039 | 0.1170 | 0.9606 | |
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| 0.2276 | 7.0 | 3545 | 0.1136 | 0.9627 | |
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| 0.2182 | 8.0 | 4052 | 0.1121 | 0.9628 | |
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| 0.1386 | 9.0 | 4558 | 0.1116 | 0.9632 | |
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| 0.1466 | 9.99 | 5060 | 0.1069 | 0.9645 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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