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README.md
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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: convnextv2-large-1k-224-finetuned-BreastCancer-Classification-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: 0.9900990099009901
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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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# convnextv2-large-1k-224-finetuned-BreastCancer-Classification-BreakHis-AH-60-20-20
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This model is a fine-tuned version of [facebook/convnextv2-large-1k-224](https://huggingface.co/facebook/convnextv2-large-1k-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0353
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- Accuracy: 0.9901
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 2
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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: 0.9
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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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| 0.5207 | 1.0 | 199 | 0.4745 | 0.8887 |
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| 0.2029 | 2.0 | 398 | 0.2072 | 0.9401 |
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| 0.1615 | 3.0 | 597 | 0.1489 | 0.9547 |
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| 0.1662 | 4.0 | 796 | 0.1312 | 0.9562 |
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| 0.1986 | 5.0 | 995 | 0.1026 | 0.9698 |
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| 0.0854 | 6.0 | 1194 | 0.0583 | 0.9802 |
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| 0.0538 | 7.0 | 1393 | 0.0568 | 0.9835 |
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| 0.0977 | 8.0 | 1592 | 0.0654 | 0.9793 |
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| 0.6971 | 9.0 | 1791 | 0.6821 | 0.5450 |
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| 0.211 | 10.0 | 1990 | 0.1654 | 0.9326 |
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| 0.1775 | 11.0 | 2189 | 0.0859 | 0.9665 |
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| 0.0042 | 12.0 | 2388 | 0.0353 | 0.9901 |
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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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