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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-large-1k-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: convnextv2-large-1k-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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# convnextv2-large-1k-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20-Shuffled-3rd |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0672 |
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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-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: 15 |
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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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| 1.9123 | 1.0 | 114 | 1.9145 | 0.2241 | |
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| 1.7059 | 2.0 | 229 | 1.6895 | 0.5599 | |
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| 1.3919 | 3.0 | 343 | 1.3194 | 0.6634 | |
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| 1.0811 | 4.0 | 458 | 1.0303 | 0.7151 | |
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| 0.9301 | 5.0 | 572 | 0.8376 | 0.7562 | |
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| 0.7336 | 6.0 | 687 | 0.6449 | 0.8374 | |
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| 0.5805 | 7.0 | 801 | 0.5091 | 0.8736 | |
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| 0.5982 | 8.0 | 916 | 0.4677 | 0.8826 | |
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| 0.4939 | 9.0 | 1030 | 0.4029 | 0.8842 | |
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| 0.3296 | 10.0 | 1145 | 0.3051 | 0.9204 | |
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| 0.3559 | 11.0 | 1259 | 0.5266 | 0.8366 | |
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| 0.3089 | 12.0 | 1374 | 0.3569 | 0.8883 | |
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| 0.2272 | 13.0 | 1488 | 0.1487 | 0.9680 | |
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| 0.3355 | 14.0 | 1603 | 0.2344 | 0.9269 | |
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| 0.1581 | 14.93 | 1710 | 0.0672 | 0.9893 | |
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### Framework versions |
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- Transformers 4.32.0 |
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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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