| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: facebook/convnext-tiny-224 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: convnext-tiny-224-finetuned-papsmear |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.8088235294117647 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # convnext-tiny-224-finetuned-papsmear |
|
|
| This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4893 |
| - Accuracy: 0.8088 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 15 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-------:|:----:|:---------------:|:--------:| |
| | 1.706 | 0.9935 | 38 | 1.6028 | 0.2794 | |
| | 1.3867 | 1.9869 | 76 | 1.2961 | 0.4853 | |
| | 1.0784 | 2.9804 | 114 | 1.0588 | 0.5221 | |
| | 0.9128 | 4.0 | 153 | 0.8886 | 0.6618 | |
| | 0.7466 | 4.9935 | 191 | 0.8913 | 0.6029 | |
| | 0.6886 | 5.9869 | 229 | 0.7380 | 0.7059 | |
| | 0.6198 | 6.9804 | 267 | 0.7622 | 0.7132 | |
| | 0.6001 | 8.0 | 306 | 0.7083 | 0.6838 | |
| | 0.5542 | 8.9935 | 344 | 0.5909 | 0.7721 | |
| | 0.5161 | 9.9869 | 382 | 0.5909 | 0.7574 | |
| | 0.4631 | 10.9804 | 420 | 0.5677 | 0.7721 | |
| | 0.4284 | 12.0 | 459 | 0.5229 | 0.7868 | |
| | 0.4334 | 12.9935 | 497 | 0.5160 | 0.8015 | |
| | 0.4386 | 13.9869 | 535 | 0.4788 | 0.8015 | |
| | 0.3728 | 14.9020 | 570 | 0.4893 | 0.8088 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.19.1 |
|
|
