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--- |
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license: apache-2.0 |
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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: swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-BreastCancer-BreakHis-AH-60-20-20 |
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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: Splitted-Resized |
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split: train |
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args: Splitted-Resized |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9943422913719944 |
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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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# swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-BreastCancer-BreakHis-AH-60-20-20 |
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This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0229 |
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- Accuracy: 0.9943 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 0.5 |
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- num_epochs: 7 |
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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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| 0.2053 | 1.0 | 199 | 0.1227 | 0.9496 | |
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| 0.1302 | 2.0 | 398 | 0.0665 | 0.9736 | |
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| 0.0784 | 3.0 | 597 | 0.0600 | 0.9778 | |
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| 0.1181 | 4.0 | 796 | 0.0449 | 0.9849 | |
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| 0.208 | 5.0 | 995 | 0.0393 | 0.9887 | |
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| 0.0057 | 6.0 | 1194 | 0.0229 | 0.9943 | |
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| 0.0017 | 7.0 | 1393 | 0.0263 | 0.9939 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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