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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-wuhan |
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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: 0.4 |
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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-wuhan |
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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: 0.7953 |
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- Accuracy: 0.4 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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: 20 |
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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 | 1.0 | 3 | 0.7953 | 0.4 | |
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| No log | 2.0 | 6 | 0.9477 | 0.4 | |
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| No log | 3.0 | 9 | 1.0106 | 0.4 | |
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| 0.5883 | 4.0 | 12 | 1.4170 | 0.4 | |
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| 0.5883 | 5.0 | 15 | 1.7436 | 0.4 | |
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| 0.5883 | 6.0 | 18 | 2.5380 | 0.4 | |
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| 0.241 | 7.0 | 21 | 3.8803 | 0.4 | |
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| 0.241 | 8.0 | 24 | 2.4040 | 0.2222 | |
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| 0.241 | 9.0 | 27 | 3.9968 | 0.4 | |
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| 0.125 | 10.0 | 30 | 3.2731 | 0.4 | |
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| 0.125 | 11.0 | 33 | 3.2202 | 0.2222 | |
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| 0.125 | 12.0 | 36 | 4.7008 | 0.4 | |
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| 0.125 | 13.0 | 39 | 4.5588 | 0.3556 | |
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| 0.0766 | 14.0 | 42 | 4.5434 | 0.2444 | |
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| 0.0766 | 15.0 | 45 | 4.9792 | 0.2667 | |
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| 0.0766 | 16.0 | 48 | 5.4095 | 0.2667 | |
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| 0.0239 | 17.0 | 51 | 5.8507 | 0.2222 | |
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| 0.0239 | 18.0 | 54 | 6.1023 | 0.2222 | |
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| 0.0239 | 19.0 | 57 | 6.1666 | 0.2222 | |
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| 0.0129 | 20.0 | 60 | 6.1948 | 0.2222 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.1 |
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- Tokenizers 0.13.3 |
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