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---
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license: apache-2.0
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base_model: microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft
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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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model-index:
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- name: swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-BreastCancer-BreakHis-AH-Shuffled
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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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# swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-BreastCancer-BreakHis-AH-Shuffled
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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 None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0289
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- Accuracy: 0.9953
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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: 12
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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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| 0.1894 | 1.0 | 199 | 0.1739 | 0.9307 |
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| 0.3951 | 2.0 | 398 | 0.1066 | 0.9614 |
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| 0.1021 | 3.0 | 597 | 0.0741 | 0.9708 |
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| 0.0784 | 4.0 | 796 | 0.0815 | 0.9760 |
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| 0.0835 | 5.0 | 995 | 0.0723 | 0.9774 |
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| 0.1394 | 6.0 | 1194 | 0.0532 | 0.9840 |
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| 0.1755 | 7.0 | 1393 | 0.1068 | 0.9722 |
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| 0.1134 | 8.0 | 1592 | 0.0390 | 0.9892 |
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| 0.0237 | 9.0 | 1791 | 0.0789 | 0.9863 |
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| 0.027 | 10.0 | 1990 | 0.0492 | 0.9887 |
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| 0.0081 | 11.0 | 2189 | 0.0429 | 0.9934 |
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| 0.011 | 12.0 | 2388 | 0.0289 | 0.9953 |
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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 2.14.0
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- Tokenizers 0.13.3
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