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# fancy-plant-219

This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0531
- Accuracy: 0.9805
- Precision: 0.9805
- Recall: 0.9805
- F1: 0.9805
- Roc Auc: 0.9974

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 1.3945        | 1.0   | 17   | 1.4430          | 0.4779   | 0.4233    | 0.4779 | 0.4381 | 0.6365  |
| 1.3203        | 2.0   | 34   | 1.2260          | 0.4049   | 0.5854    | 0.4049 | 0.4639 | 0.7864  |
| 1.1476        | 3.0   | 51   | 0.9415          | 0.5677   | 0.5641    | 0.5677 | 0.5634 | 0.8224  |
| 0.8622        | 4.0   | 68   | 0.6177          | 0.6133   | 0.6349    | 0.6133 | 0.6032 | 0.8612  |
| 0.7741        | 5.0   | 85   | 0.6050          | 0.5964   | 0.5937    | 0.5964 | 0.5373 | 0.8716  |
| 0.6872        | 6.0   | 102  | 0.4559          | 0.6536   | 0.7085    | 0.6536 | 0.6351 | 0.9020  |
| 0.5383        | 7.0   | 119  | 0.3990          | 0.7227   | 0.7441    | 0.7227 | 0.7034 | 0.9283  |
| 0.4257        | 8.0   | 136  | 0.2967          | 0.7643   | 0.8000    | 0.7643 | 0.7658 | 0.9521  |
| 0.3358        | 9.0   | 153  | 0.2559          | 0.8086   | 0.8325    | 0.8086 | 0.8089 | 0.9608  |
| 0.2355        | 10.0  | 170  | 0.1693          | 0.8958   | 0.8956    | 0.8958 | 0.8950 | 0.9789  |
| 0.1634        | 11.0  | 187  | 0.1659          | 0.8945   | 0.8979    | 0.8945 | 0.8950 | 0.9826  |
| 0.112         | 12.0  | 204  | 0.2273          | 0.8320   | 0.8777    | 0.8320 | 0.8334 | 0.9880  |
| 0.1065        | 13.0  | 221  | 0.1733          | 0.8984   | 0.9139    | 0.8984 | 0.8966 | 0.9901  |
| 0.1051        | 14.0  | 238  | 0.1226          | 0.9258   | 0.9298    | 0.9258 | 0.9245 | 0.9934  |
| 0.056         | 15.0  | 255  | 0.0664          | 0.9479   | 0.9499    | 0.9479 | 0.9481 | 0.9959  |
| 0.0501        | 16.0  | 272  | 0.0804          | 0.9531   | 0.9532    | 0.9531 | 0.9532 | 0.9960  |
| 0.0306        | 17.0  | 289  | 0.0784          | 0.9557   | 0.9563    | 0.9557 | 0.9556 | 0.9960  |
| 0.0315        | 18.0  | 306  | 0.0870          | 0.9648   | 0.9652    | 0.9648 | 0.9647 | 0.9968  |
| 0.0263        | 19.0  | 323  | 0.0637          | 0.9622   | 0.9624    | 0.9622 | 0.9623 | 0.9972  |
| 0.0259        | 20.0  | 340  | 0.0949          | 0.9479   | 0.9505    | 0.9479 | 0.9479 | 0.9945  |
| 0.0171        | 21.0  | 357  | 0.0903          | 0.9596   | 0.9601    | 0.9596 | 0.9594 | 0.9952  |
| 0.0236        | 22.0  | 374  | 0.0777          | 0.9714   | 0.9717    | 0.9714 | 0.9713 | 0.9962  |
| 0.0295        | 23.0  | 391  | 0.0733          | 0.9648   | 0.9664    | 0.9648 | 0.9650 | 0.9977  |
| 0.0143        | 24.0  | 408  | 0.0790          | 0.9701   | 0.9705    | 0.9701 | 0.9701 | 0.9967  |
| 0.0116        | 25.0  | 425  | 0.0849          | 0.9635   | 0.9637    | 0.9635 | 0.9634 | 0.9974  |
| 0.0079        | 26.0  | 442  | 0.0496          | 0.9792   | 0.9794    | 0.9792 | 0.9792 | 0.9978  |
| 0.0111        | 27.0  | 459  | 0.0382          | 0.9805   | 0.9806    | 0.9805 | 0.9805 | 0.9977  |
| 0.0097        | 28.0  | 476  | 0.0456          | 0.9792   | 0.9792    | 0.9792 | 0.9792 | 0.9971  |
| 0.004         | 29.0  | 493  | 0.0628          | 0.9766   | 0.9769    | 0.9766 | 0.9765 | 0.9970  |
| 0.0089        | 30.0  | 510  | 0.0584          | 0.9766   | 0.9768    | 0.9766 | 0.9765 | 0.9966  |
| 0.0035        | 31.0  | 527  | 0.0527          | 0.9792   | 0.9792    | 0.9792 | 0.9792 | 0.9982  |
| 0.007         | 32.0  | 544  | 0.0531          | 0.9805   | 0.9805    | 0.9805 | 0.9805 | 0.9974  |


### Framework versions

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

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