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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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metrics: |
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- accuracy |
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model-index: |
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- name: swin-tiny-patch4-window7-224-vit-finetuned-melanoma |
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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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# swin-tiny-patch4-window7-224-vit-finetuned-melanoma |
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This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2687 |
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- Accuracy: 0.9017 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 0.1 |
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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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| 0.5392 | 1.0 | 112 | 0.5796 | 0.7884 | |
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| 0.4716 | 2.0 | 224 | 0.4380 | 0.8304 | |
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| 0.3932 | 3.0 | 336 | 0.3749 | 0.8534 | |
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| 0.3446 | 4.0 | 448 | 0.3851 | 0.8423 | |
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| 0.3401 | 5.0 | 560 | 0.3141 | 0.8708 | |
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| 0.2842 | 6.0 | 672 | 0.3309 | 0.8685 | |
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| 0.3126 | 7.0 | 784 | 0.3493 | 0.8629 | |
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| 0.2748 | 8.0 | 896 | 0.3391 | 0.8772 | |
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| 0.2455 | 9.0 | 1008 | 0.3053 | 0.8843 | |
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| 0.2361 | 10.0 | 1120 | 0.2749 | 0.8954 | |
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| 0.2218 | 11.0 | 1232 | 0.2842 | 0.8994 | |
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| 0.2071 | 12.0 | 1344 | 0.2507 | 0.9089 | |
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| 0.2228 | 13.0 | 1456 | 0.2614 | 0.8994 | |
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| 0.2018 | 14.0 | 1568 | 0.2664 | 0.9105 | |
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| 0.1774 | 15.0 | 1680 | 0.2687 | 0.9017 | |
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### Framework versions |
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- Transformers 4.28.0 |
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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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