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--- |
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license: apache-2.0 |
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base_model: microsoft/swin-base-patch4-window7-224-in22k |
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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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- f1 |
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model-index: |
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- name: swin-base-patch4-window7-224-in22k |
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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: F1 |
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type: f1 |
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value: 0.976218332192814 |
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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-base-patch4-window7-224-in22k |
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This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0117 |
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- F1: 0.9762 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.0575 | 0.99 | 50 | 0.0560 | 0.9257 | |
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| 0.0561 | 2.0 | 101 | 0.0359 | 0.9475 | |
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| 0.027 | 2.99 | 151 | 0.0212 | 0.9643 | |
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| 0.0236 | 4.0 | 202 | 0.0145 | 0.9737 | |
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| 0.0256 | 4.99 | 252 | 0.0269 | 0.9503 | |
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| 0.0226 | 6.0 | 303 | 0.0123 | 0.9762 | |
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| 0.0265 | 6.99 | 353 | 0.0135 | 0.9731 | |
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| 0.0168 | 8.0 | 404 | 0.0098 | 0.9824 | |
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| 0.0074 | 8.99 | 454 | 0.0172 | 0.9700 | |
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| 0.0125 | 9.9 | 500 | 0.0117 | 0.9762 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 1.12.1+cu102 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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