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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: facebook/deit-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: deit-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: 0.8235294117647058 |
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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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# deit-tiny-patch16-224-finetuned-papsmear |
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This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co./facebook/deit-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: 0.4747 |
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- Accuracy: 0.8235 |
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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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| 1.5381 | 0.9935 | 38 | 1.4222 | 0.3897 | |
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| 1.172 | 1.9869 | 76 | 1.1008 | 0.5882 | |
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| 0.8361 | 2.9804 | 114 | 0.8529 | 0.6618 | |
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| 0.6869 | 4.0 | 153 | 0.9582 | 0.6324 | |
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| 0.4995 | 4.9935 | 191 | 0.6926 | 0.7574 | |
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| 0.4576 | 5.9869 | 229 | 0.4967 | 0.8529 | |
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| 0.4187 | 6.9804 | 267 | 0.5350 | 0.8162 | |
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| 0.4075 | 8.0 | 306 | 0.4903 | 0.8088 | |
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| 0.3585 | 8.9935 | 344 | 0.5252 | 0.7868 | |
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| 0.3528 | 9.9869 | 382 | 0.5027 | 0.8088 | |
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| 0.2788 | 10.9804 | 420 | 0.4503 | 0.8456 | |
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| 0.2419 | 12.0 | 459 | 0.4857 | 0.8309 | |
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| 0.2544 | 12.9935 | 497 | 0.5543 | 0.7868 | |
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| 0.2591 | 13.9869 | 535 | 0.4839 | 0.8382 | |
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| 0.207 | 14.9020 | 570 | 0.4747 | 0.8235 | |
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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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