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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-Lesion-Classification-HAM10000-S |
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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-Lesion-Classification-HAM10000-S |
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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: 0.0069 |
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- Accuracy: 0.9975 |
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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: 10 |
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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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| 1.2378 | 1.0 | 114 | 0.9976 | 0.5936 | |
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| 0.7272 | 2.0 | 228 | 0.4749 | 0.8309 | |
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| 0.4335 | 2.99 | 342 | 0.2488 | 0.9195 | |
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| 0.3298 | 4.0 | 457 | 0.1700 | 0.9310 | |
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| 0.177 | 5.0 | 571 | 0.2116 | 0.9261 | |
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| 0.2299 | 6.0 | 685 | 0.0933 | 0.9754 | |
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| 0.2586 | 6.99 | 799 | 0.0316 | 0.9869 | |
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| 0.1053 | 8.0 | 914 | 0.0256 | 0.9910 | |
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| 0.2159 | 9.0 | 1028 | 0.0147 | 0.9959 | |
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| 0.0607 | 9.98 | 1140 | 0.0069 | 0.9975 | |
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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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