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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-in21k |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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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-in21k-finetuned-papsmear |
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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: imagefolder |
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type: imagefolder |
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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: 0.9411764705882353 |
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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-in21k-finetuned-papsmear |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co./google/vit-base-patch16-224-in21k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2523 |
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- Accuracy: 0.9412 |
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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: 0.1 |
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- num_epochs: 30 |
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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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| 1.6954 | 0.9935 | 38 | 1.6106 | 0.3456 | |
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| 1.2818 | 1.9869 | 76 | 1.2412 | 0.5735 | |
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| 1.0023 | 2.9804 | 114 | 0.9875 | 0.7132 | |
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| 0.7163 | 4.0 | 153 | 0.8399 | 0.6912 | |
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| 0.5173 | 4.9935 | 191 | 0.6546 | 0.8162 | |
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| 0.5057 | 5.9869 | 229 | 0.6251 | 0.8309 | |
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| 0.4313 | 6.9804 | 267 | 0.5696 | 0.8309 | |
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| 0.325 | 8.0 | 306 | 0.5507 | 0.8309 | |
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| 0.3811 | 8.9935 | 344 | 0.4429 | 0.8676 | |
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| 0.2341 | 9.9869 | 382 | 0.4222 | 0.875 | |
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| 0.3082 | 10.9804 | 420 | 0.6573 | 0.7721 | |
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| 0.2571 | 12.0 | 459 | 0.4229 | 0.8897 | |
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| 0.2374 | 12.9935 | 497 | 0.4233 | 0.875 | |
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| 0.128 | 13.9869 | 535 | 0.3671 | 0.8971 | |
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| 0.1718 | 14.9804 | 573 | 0.3430 | 0.8971 | |
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| 0.16 | 16.0 | 612 | 0.4104 | 0.875 | |
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| 0.1096 | 16.9935 | 650 | 0.2920 | 0.9118 | |
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| 0.1408 | 17.9869 | 688 | 0.2630 | 0.9044 | |
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| 0.113 | 18.9804 | 726 | 0.3084 | 0.8824 | |
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| 0.1272 | 20.0 | 765 | 0.2523 | 0.9412 | |
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| 0.119 | 20.9935 | 803 | 0.4254 | 0.8824 | |
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| 0.1068 | 21.9869 | 841 | 0.3519 | 0.8971 | |
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| 0.0723 | 22.9804 | 879 | 0.3293 | 0.9191 | |
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| 0.0769 | 24.0 | 918 | 0.2613 | 0.9265 | |
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| 0.095 | 24.9935 | 956 | 0.2609 | 0.9412 | |
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| 0.0863 | 25.9869 | 994 | 0.2650 | 0.9265 | |
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| 0.0795 | 26.9804 | 1032 | 0.2978 | 0.9118 | |
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| 0.0564 | 28.0 | 1071 | 0.2737 | 0.9191 | |
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| 0.0562 | 28.9935 | 1109 | 0.2941 | 0.9191 | |
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| 0.0751 | 29.8039 | 1140 | 0.3111 | 0.9191 | |
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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 3.0.1 |
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- Tokenizers 0.19.1 |
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