| --- |
| 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: 0.7794117647058824 |
| --- |
| |
| <!-- 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: 0.6033 |
| - Accuracy: 0.7794 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 64 |
| - 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 | |
| |:-------------:|:-------:|:----:|:---------------:|:--------:| |
| | 1.8151 | 0.9870 | 19 | 1.6491 | 0.3456 | |
| | 1.6104 | 1.9740 | 38 | 1.4322 | 0.4265 | |
| | 1.4002 | 2.9610 | 57 | 1.2286 | 0.5882 | |
| | 1.203 | 4.0 | 77 | 1.0559 | 0.6544 | |
| | 1.047 | 4.9870 | 96 | 0.9357 | 0.6765 | |
| | 0.9083 | 5.9740 | 115 | 0.8477 | 0.7279 | |
| | 0.8756 | 6.9610 | 134 | 0.7762 | 0.75 | |
| | 0.7853 | 8.0 | 154 | 0.7258 | 0.7647 | |
| | 0.7198 | 8.9870 | 173 | 0.7023 | 0.7574 | |
| | 0.7151 | 9.9740 | 192 | 0.6756 | 0.7574 | |
| | 0.7049 | 10.9610 | 211 | 0.6493 | 0.7574 | |
| | 0.6387 | 12.0 | 231 | 0.6256 | 0.7721 | |
| | 0.6387 | 12.9870 | 250 | 0.6295 | 0.7721 | |
| | 0.6233 | 13.9740 | 269 | 0.6033 | 0.7794 | |
| | 0.632 | 14.8052 | 285 | 0.6010 | 0.7794 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.44.0 |
| - Pytorch 2.4.0 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
|
|
