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# convnext-tiny-224-finetuned-biopsy

This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0688
- Accuracy: 0.9816

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2488        | 1.0   | 42   | 1.1914          | 0.5360   |
| 0.9265        | 2.0   | 84   | 0.8634          | 0.5544   |
| 0.5701        | 3.0   | 126  | 0.4834          | 0.8543   |
| 0.4041        | 4.0   | 168  | 0.2996          | 0.9213   |
| 0.2747        | 5.0   | 210  | 0.2743          | 0.9146   |
| 0.2518        | 6.0   | 252  | 0.1826          | 0.9497   |
| 0.2363        | 7.0   | 294  | 0.1731          | 0.9497   |
| 0.1782        | 8.0   | 336  | 0.1870          | 0.9363   |
| 0.2122        | 9.0   | 378  | 0.1327          | 0.9615   |
| 0.1856        | 10.0  | 420  | 0.2082          | 0.9313   |
| 0.1736        | 11.0  | 462  | 0.1306          | 0.9564   |
| 0.1423        | 12.0  | 504  | 0.0989          | 0.9732   |
| 0.1296        | 13.0  | 546  | 0.0949          | 0.9732   |
| 0.1158        | 14.0  | 588  | 0.1084          | 0.9631   |
| 0.1383        | 15.0  | 630  | 0.0865          | 0.9715   |
| 0.1384        | 16.0  | 672  | 0.0879          | 0.9715   |
| 0.0924        | 17.0  | 714  | 0.0758          | 0.9782   |
| 0.0966        | 18.0  | 756  | 0.0866          | 0.9682   |
| 0.1324        | 19.0  | 798  | 0.0876          | 0.9715   |
| 0.0995        | 20.0  | 840  | 0.0990          | 0.9648   |
| 0.083         | 21.0  | 882  | 0.0911          | 0.9698   |
| 0.082         | 22.0  | 924  | 0.0816          | 0.9799   |
| 0.1038        | 23.0  | 966  | 0.1453          | 0.9430   |
| 0.0751        | 24.0  | 1008 | 0.0877          | 0.9732   |
| 0.0733        | 25.0  | 1050 | 0.0878          | 0.9682   |
| 0.0813        | 26.0  | 1092 | 0.0688          | 0.9816   |
| 0.0788        | 27.0  | 1134 | 0.0732          | 0.9782   |
| 0.0617        | 28.0  | 1176 | 0.0722          | 0.9749   |
| 0.0568        | 29.0  | 1218 | 0.0883          | 0.9648   |
| 0.0701        | 30.0  | 1260 | 0.0703          | 0.9765   |
| 0.0535        | 31.0  | 1302 | 0.0792          | 0.9782   |
| 0.0716        | 32.0  | 1344 | 0.0684          | 0.9799   |
| 0.0419        | 33.0  | 1386 | 0.0666          | 0.9816   |
| 0.054         | 34.0  | 1428 | 0.0768          | 0.9749   |
| 0.0332        | 35.0  | 1470 | 0.0717          | 0.9799   |
| 0.0524        | 36.0  | 1512 | 0.1067          | 0.9715   |
| 0.0372        | 37.0  | 1554 | 0.0604          | 0.9816   |
| 0.0692        | 38.0  | 1596 | 0.0579          | 0.9799   |
| 0.038         | 39.0  | 1638 | 0.0824          | 0.9732   |
| 0.0524        | 40.0  | 1680 | 0.0635          | 0.9765   |
| 0.0429        | 41.0  | 1722 | 0.0644          | 0.9816   |
| 0.0705        | 42.0  | 1764 | 0.0747          | 0.9765   |
| 0.0325        | 43.0  | 1806 | 0.0685          | 0.9816   |
| 0.0446        | 44.0  | 1848 | 0.0683          | 0.9782   |
| 0.0439        | 45.0  | 1890 | 0.0707          | 0.9749   |
| 0.0346        | 46.0  | 1932 | 0.0642          | 0.9782   |
| 0.0504        | 47.0  | 1974 | 0.0654          | 0.9799   |
| 0.0379        | 48.0  | 2016 | 0.0651          | 0.9765   |
| 0.0433        | 49.0  | 2058 | 0.0654          | 0.9765   |
| 0.0337        | 50.0  | 2100 | 0.0655          | 0.9765   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1

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