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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- image_folder |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit_base_patch16_224-finetuned-SkinDisease |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: image_folder |
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type: image_folder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9342629482071713 |
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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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# vit_base_patch16_224-finetuned-SkinDisease |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the image_folder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1992 |
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- Accuracy: 0.9343 |
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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: 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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| 0.9099 | 1.0 | 282 | 0.8248 | 0.7647 | |
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| 0.5848 | 2.0 | 565 | 0.4236 | 0.8748 | |
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| 0.3952 | 3.0 | 847 | 0.3154 | 0.9021 | |
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| 0.3957 | 4.0 | 1130 | 0.2695 | 0.9106 | |
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| 0.3146 | 5.0 | 1412 | 0.2381 | 0.9198 | |
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| 0.2883 | 6.0 | 1695 | 0.2407 | 0.9218 | |
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| 0.2264 | 7.0 | 1977 | 0.2160 | 0.9278 | |
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| 0.2339 | 8.0 | 2260 | 0.2121 | 0.9283 | |
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| 0.1966 | 9.0 | 2542 | 0.2044 | 0.9303 | |
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| 0.2366 | 9.98 | 2820 | 0.1992 | 0.9343 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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