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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: WinKawaks/vit-tiny-patch16-224 |
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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-tiny-patch16-224-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: 0.9338235294117647 |
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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-tiny-patch16-224-finetuned-papsmear |
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This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2121 |
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- Accuracy: 0.9338 |
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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: 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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| 1.4005 | 0.9935 | 38 | 1.2214 | 0.5294 | |
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| 0.8877 | 1.9869 | 76 | 1.0727 | 0.6691 | |
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| 0.603 | 2.9804 | 114 | 0.6807 | 0.7574 | |
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| 0.465 | 4.0 | 153 | 0.6485 | 0.7574 | |
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| 0.432 | 4.9935 | 191 | 0.5024 | 0.8015 | |
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| 0.2957 | 5.9869 | 229 | 0.4485 | 0.8162 | |
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| 0.2203 | 6.9804 | 267 | 0.3850 | 0.8529 | |
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| 0.236 | 8.0 | 306 | 0.3628 | 0.8456 | |
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| 0.1857 | 8.9935 | 344 | 0.2930 | 0.8824 | |
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| 0.1907 | 9.9869 | 382 | 0.2121 | 0.9338 | |
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| 0.1546 | 10.9804 | 420 | 0.2242 | 0.9265 | |
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| 0.1375 | 12.0 | 459 | 0.1918 | 0.9191 | |
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| 0.1237 | 12.9935 | 497 | 0.1809 | 0.9338 | |
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| 0.1637 | 13.9869 | 535 | 0.1774 | 0.9338 | |
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| 0.0803 | 14.9020 | 570 | 0.1882 | 0.9338 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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