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--- |
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library_name: transformers |
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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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- medmnist-v2 |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: ViT_bloodmnist |
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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: medmnist-v2 |
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type: medmnist-v2 |
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config: bloodmnist |
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split: validation |
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args: bloodmnist |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9748611517100263 |
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- name: F1 |
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type: f1 |
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value: 0.97180354304681 |
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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_bloodmnist |
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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 medmnist-v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0879 |
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- Accuracy: 0.9749 |
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- F1: 0.9718 |
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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: 8 |
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- seed: 42 |
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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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.2747 | 1.0 | 374 | 0.0930 | 0.9696 | 0.9652 | |
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| 0.0955 | 2.0 | 748 | 0.0998 | 0.9702 | 0.9670 | |
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| 0.0405 | 3.0 | 1122 | 0.0812 | 0.9743 | 0.9725 | |
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| 0.0194 | 4.0 | 1496 | 0.0829 | 0.9796 | 0.9784 | |
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| 0.0081 | 5.0 | 1870 | 0.1328 | 0.9720 | 0.9696 | |
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| 0.0026 | 6.0 | 2244 | 0.1252 | 0.9743 | 0.9735 | |
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| 0.0004 | 7.0 | 2618 | 0.0997 | 0.9790 | 0.9778 | |
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| 0.0001 | 8.0 | 2992 | 0.1049 | 0.9784 | 0.9768 | |
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| 0.0001 | 9.0 | 3366 | 0.1072 | 0.9778 | 0.9761 | |
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| 0.0001 | 10.0 | 3740 | 0.1077 | 0.9778 | 0.9761 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.2 |
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- Tokenizers 0.19.1 |
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