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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 |
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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 |
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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: 0.0487 |
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- Accuracy: 0.9893 |
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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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| 2.1055 | 1.0 | 114 | 2.0091 | 0.1601 | |
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| 1.6582 | 2.0 | 229 | 1.5953 | 0.4187 | |
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| 1.2399 | 3.0 | 343 | 1.1053 | 0.5977 | |
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| 0.8417 | 4.0 | 458 | 0.7602 | 0.7241 | |
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| 0.5517 | 5.0 | 572 | 0.5651 | 0.8013 | |
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| 0.5777 | 6.0 | 687 | 0.3980 | 0.8768 | |
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| 0.408 | 7.0 | 801 | 0.2912 | 0.9154 | |
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| 0.2395 | 8.0 | 916 | 0.2185 | 0.9417 | |
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| 0.3613 | 9.0 | 1030 | 0.1753 | 0.9475 | |
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| 0.2408 | 10.0 | 1145 | 0.1353 | 0.9614 | |
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| 0.2777 | 11.0 | 1259 | 0.0699 | 0.9860 | |
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| 0.1528 | 11.95 | 1368 | 0.0487 | 0.9893 | |
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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 2.13.1 |
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- Tokenizers 0.13.3 |
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