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---
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license: apache-2.0
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base_model: microsoft/beit-large-patch16-224
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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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model-index:
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- name: beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20-Shuffled-3rd
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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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# beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20-Shuffled-3rd
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This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0488
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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-06
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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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| 1.9835 | 1.0 | 114 | 1.9296 | 0.2315 |
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| 1.6045 | 2.0 | 229 | 1.4334 | 0.5172 |
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| 1.0525 | 3.0 | 343 | 0.9298 | 0.6962 |
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| 0.795 | 4.0 | 458 | 0.6580 | 0.7709 |
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| 0.5739 | 5.0 | 572 | 0.4717 | 0.8366 |
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| 0.5821 | 6.0 | 687 | 0.3511 | 0.8851 |
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| 0.4566 | 7.0 | 801 | 0.2705 | 0.9204 |
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| 0.2751 | 8.0 | 916 | 0.2114 | 0.9384 |
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| 0.2352 | 9.0 | 1030 | 0.1303 | 0.9688 |
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| 0.1831 | 10.0 | 1145 | 0.1194 | 0.9688 |
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| 0.1515 | 11.0 | 1259 | 0.0673 | 0.9869 |
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| 0.204 | 11.95 | 1368 | 0.0488 | 0.9901 |
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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 2.14.4
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- Tokenizers 0.13.3
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