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# hardy-bee-220

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: 0.0965
- Accuracy: 0.9648
- Precision: 0.9660
- Recall: 0.9648
- F1: 0.9650
- Roc Auc: 0.9978

## 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: 0.0001
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 1.3971        | 1.0   | 17   | 1.3628          | 0.3997   | 0.4611    | 0.3997 | 0.3922 | 0.6197  |
| 1.343         | 2.0   | 34   | 1.2959          | 0.4206   | 0.5256    | 0.4206 | 0.4184 | 0.7270  |
| 1.218         | 3.0   | 51   | 1.1328          | 0.5104   | 0.5209    | 0.5104 | 0.5114 | 0.7725  |
| 1.0866        | 4.0   | 68   | 1.0127          | 0.5482   | 0.5251    | 0.5482 | 0.5135 | 0.7935  |
| 0.979         | 5.0   | 85   | 0.9274          | 0.5182   | 0.5688    | 0.5182 | 0.5264 | 0.7989  |
| 0.7709        | 6.0   | 102  | 0.8019          | 0.5508   | 0.5959    | 0.5508 | 0.5541 | 0.8207  |
| 0.6793        | 7.0   | 119  | 0.7300          | 0.5729   | 0.6291    | 0.5729 | 0.5779 | 0.8376  |
| 0.7004        | 8.0   | 136  | 0.7979          | 0.5820   | 0.6178    | 0.5820 | 0.5900 | 0.8433  |
| 0.5933        | 9.0   | 153  | 0.7219          | 0.5456   | 0.6553    | 0.5456 | 0.5559 | 0.8498  |
| 0.5292        | 10.0  | 170  | 0.6114          | 0.6888   | 0.7024    | 0.6888 | 0.6911 | 0.8923  |
| 0.4391        | 11.0  | 187  | 0.5453          | 0.6758   | 0.7536    | 0.6758 | 0.6758 | 0.9062  |
| 0.3856        | 12.0  | 204  | 0.5515          | 0.6810   | 0.7299    | 0.6810 | 0.6793 | 0.9156  |
| 0.3171        | 13.0  | 221  | 0.4486          | 0.7188   | 0.7829    | 0.7188 | 0.7172 | 0.9330  |
| 0.3035        | 14.0  | 238  | 0.4295          | 0.7227   | 0.7859    | 0.7227 | 0.7248 | 0.9364  |
| 0.2196        | 15.0  | 255  | 0.3438          | 0.8229   | 0.8298    | 0.8229 | 0.8243 | 0.9563  |
| 0.1842        | 16.0  | 272  | 0.2979          | 0.8190   | 0.8539    | 0.8190 | 0.8180 | 0.9690  |
| 0.1423        | 17.0  | 289  | 0.2747          | 0.8646   | 0.8638    | 0.8646 | 0.8638 | 0.9717  |
| 0.1387        | 18.0  | 306  | 0.3680          | 0.7904   | 0.8535    | 0.7904 | 0.7934 | 0.9793  |
| 0.1137        | 19.0  | 323  | 0.2358          | 0.8490   | 0.8744    | 0.8490 | 0.8486 | 0.9824  |
| 0.1013        | 20.0  | 340  | 0.1700          | 0.9193   | 0.9191    | 0.9193 | 0.9191 | 0.9894  |
| 0.0763        | 21.0  | 357  | 0.1573          | 0.9193   | 0.9241    | 0.9193 | 0.9199 | 0.9906  |
| 0.0648        | 22.0  | 374  | 0.1423          | 0.9323   | 0.9336    | 0.9323 | 0.9324 | 0.9915  |
| 0.0433        | 23.0  | 391  | 0.1344          | 0.9414   | 0.9413    | 0.9414 | 0.9412 | 0.9933  |
| 0.0392        | 24.0  | 408  | 0.1444          | 0.9427   | 0.9444    | 0.9427 | 0.9423 | 0.9938  |
| 0.0282        | 25.0  | 425  | 0.1134          | 0.9622   | 0.9627    | 0.9622 | 0.9623 | 0.9952  |
| 0.0249        | 26.0  | 442  | 0.1243          | 0.9466   | 0.9500    | 0.9466 | 0.9470 | 0.9953  |
| 0.015         | 27.0  | 459  | 0.1377          | 0.9336   | 0.9379    | 0.9336 | 0.9339 | 0.9959  |
| 0.0175        | 28.0  | 476  | 0.1320          | 0.9492   | 0.9497    | 0.9492 | 0.9493 | 0.9954  |
| 0.029         | 29.0  | 493  | 0.1202          | 0.9583   | 0.9592    | 0.9583 | 0.9582 | 0.9961  |
| 0.0138        | 30.0  | 510  | 0.0889          | 0.9714   | 0.9714    | 0.9714 | 0.9714 | 0.9976  |
| 0.0135        | 31.0  | 527  | 0.1064          | 0.9622   | 0.9635    | 0.9622 | 0.9624 | 0.9969  |
| 0.0076        | 32.0  | 544  | 0.1238          | 0.9427   | 0.9466    | 0.9427 | 0.9428 | 0.9969  |
| 0.0098        | 33.0  | 561  | 0.0871          | 0.9635   | 0.9643    | 0.9635 | 0.9636 | 0.9974  |
| 0.0066        | 34.0  | 578  | 0.1342          | 0.9518   | 0.9547    | 0.9518 | 0.9522 | 0.9968  |
| 0.0055        | 35.0  | 595  | 0.0965          | 0.9648   | 0.9660    | 0.9648 | 0.9650 | 0.9978  |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.7.0+cpu
- Datasets 3.6.0
- Tokenizers 0.21.0

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