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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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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: swin-tiny-patch4-window7-224-finetuned-RCC |
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results: [] |
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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-RCC |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3526 |
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- Accuracy: 0.8226 |
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- Precision: 0.9245 |
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- Recall: 0.875 |
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- F1: 0.5829 |
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- Auc: 0.6042 |
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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 | Precision | Recall | F1 | Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:| |
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| No log | 1.0 | 7 | 0.3296 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 | |
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| 0.4795 | 2.0 | 14 | 0.3129 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 | |
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| 0.2503 | 3.0 | 21 | 0.3182 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 | |
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| 0.2503 | 4.0 | 28 | 0.2973 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 | |
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| 0.2231 | 5.0 | 35 | 0.3275 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 | |
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| 0.1791 | 6.0 | 42 | 0.3147 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 | |
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| 0.1791 | 7.0 | 49 | 0.3401 | 0.8978 | 0.9071 | 0.9881 | 0.5206 | 0.5218 | |
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| 0.1361 | 8.0 | 56 | 0.3885 | 0.7849 | 0.9211 | 0.8333 | 0.5529 | 0.5833 | |
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| 0.1245 | 9.0 | 63 | 0.3192 | 0.8817 | 0.9195 | 0.9524 | 0.6012 | 0.5873 | |
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| 0.0902 | 10.0 | 70 | 0.3526 | 0.8226 | 0.9245 | 0.875 | 0.5829 | 0.6042 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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