
<!-- 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: 0.2836
- Accuracy: 0.8897

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.9231  | 9    | 1.7808          | 0.1691   |
| 1.8057        | 1.9487  | 19   | 1.6808          | 0.3309   |
| 1.7394        | 2.9744  | 29   | 1.5825          | 0.3382   |
| 1.6408        | 4.0     | 39   | 1.4576          | 0.375    |
| 1.5428        | 4.9231  | 48   | 1.3281          | 0.5221   |
| 1.3931        | 5.9487  | 58   | 1.2044          | 0.5588   |
| 1.2669        | 6.9744  | 68   | 1.0756          | 0.6103   |
| 1.1355        | 8.0     | 78   | 0.9845          | 0.6324   |
| 1.0379        | 8.9231  | 87   | 0.9260          | 0.6618   |
| 0.9571        | 9.9487  | 97   | 0.8539          | 0.6618   |
| 0.8376        | 10.9744 | 107  | 0.7998          | 0.7279   |
| 0.7942        | 12.0    | 117  | 0.7573          | 0.75     |
| 0.7095        | 12.9231 | 126  | 0.7005          | 0.7426   |
| 0.7022        | 13.9487 | 136  | 0.6834          | 0.7868   |
| 0.6504        | 14.9744 | 146  | 0.6552          | 0.7721   |
| 0.589         | 16.0    | 156  | 0.6192          | 0.8015   |
| 0.5679        | 16.9231 | 165  | 0.5738          | 0.8088   |
| 0.5236        | 17.9487 | 175  | 0.5617          | 0.8015   |
| 0.5244        | 18.9744 | 185  | 0.5073          | 0.8235   |
| 0.4781        | 20.0    | 195  | 0.5112          | 0.8162   |
| 0.453         | 20.9231 | 204  | 0.4650          | 0.8235   |
| 0.4544        | 21.9487 | 214  | 0.4591          | 0.8456   |
| 0.419         | 22.9744 | 224  | 0.4403          | 0.8309   |
| 0.4146        | 24.0    | 234  | 0.4292          | 0.8382   |
| 0.398         | 24.9231 | 243  | 0.4315          | 0.8382   |
| 0.3918        | 25.9487 | 253  | 0.3980          | 0.8676   |
| 0.361         | 26.9744 | 263  | 0.3758          | 0.8603   |
| 0.3355        | 28.0    | 273  | 0.3657          | 0.8603   |
| 0.3483        | 28.9231 | 282  | 0.3669          | 0.875    |
| 0.3171        | 29.9487 | 292  | 0.3492          | 0.8603   |
| 0.3249        | 30.9744 | 302  | 0.3400          | 0.875    |
| 0.3087        | 32.0    | 312  | 0.3251          | 0.875    |
| 0.3029        | 32.9231 | 321  | 0.3167          | 0.8824   |
| 0.3018        | 33.9487 | 331  | 0.3192          | 0.875    |
| 0.2823        | 34.9744 | 341  | 0.3066          | 0.875    |
| 0.2744        | 36.0    | 351  | 0.3003          | 0.875    |
| 0.258         | 36.9231 | 360  | 0.2964          | 0.875    |
| 0.2714        | 37.9487 | 370  | 0.3039          | 0.875    |
| 0.2486        | 38.9744 | 380  | 0.2937          | 0.875    |
| 0.2511        | 40.0    | 390  | 0.2739          | 0.8824   |
| 0.2511        | 40.9231 | 399  | 0.2836          | 0.8897   |
| 0.2659        | 41.9487 | 409  | 0.2804          | 0.875    |
| 0.2379        | 42.9744 | 419  | 0.2747          | 0.8824   |
| 0.2279        | 44.0    | 429  | 0.2726          | 0.8897   |
| 0.2153        | 44.9231 | 438  | 0.2732          | 0.8897   |
| 0.2461        | 45.9487 | 448  | 0.2738          | 0.8897   |
| 0.2482        | 46.1538 | 450  | 0.2738          | 0.8897   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1

ascus cancer hsil lsil nilm non-diagnostic