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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_breastmnist |
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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: breastmnist |
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split: validation |
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args: breastmnist |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8653846153846154 |
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- name: F1 |
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type: f1 |
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value: 0.8156962025316457 |
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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_breastmnist |
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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: 0.3570 |
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- Accuracy: 0.8654 |
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- F1: 0.8157 |
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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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| 0.5391 | 0.5556 | 10 | 0.4007 | 0.7949 | 0.6698 | |
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| 0.3685 | 1.1111 | 20 | 0.3650 | 0.8718 | 0.8120 | |
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| 0.2275 | 1.6667 | 30 | 0.3601 | 0.8462 | 0.8101 | |
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| 0.1604 | 2.2222 | 40 | 0.2938 | 0.8718 | 0.8319 | |
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| 0.0624 | 2.7778 | 50 | 0.2966 | 0.8846 | 0.8511 | |
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| 0.0597 | 3.3333 | 60 | 0.4313 | 0.8974 | 0.8556 | |
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| 0.029 | 3.8889 | 70 | 0.4105 | 0.8718 | 0.8194 | |
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| 0.0094 | 4.4444 | 80 | 0.3746 | 0.9103 | 0.8803 | |
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| 0.0077 | 5.0 | 90 | 0.4098 | 0.8974 | 0.8655 | |
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| 0.0082 | 5.5556 | 100 | 0.4451 | 0.9103 | 0.8803 | |
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| 0.0024 | 6.1111 | 110 | 0.4599 | 0.8974 | 0.8655 | |
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| 0.0028 | 6.6667 | 120 | 0.4739 | 0.8974 | 0.8608 | |
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| 0.0013 | 7.2222 | 130 | 0.4653 | 0.8974 | 0.8655 | |
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| 0.0016 | 7.7778 | 140 | 0.4927 | 0.8974 | 0.8608 | |
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| 0.0011 | 8.3333 | 150 | 0.5115 | 0.8974 | 0.8608 | |
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| 0.0015 | 8.8889 | 160 | 0.5055 | 0.8974 | 0.8608 | |
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| 0.0007 | 9.4444 | 170 | 0.4982 | 0.8974 | 0.8608 | |
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| 0.0011 | 10.0 | 180 | 0.4975 | 0.8974 | 0.8608 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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