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# polar-pond-221

This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1960
- Accuracy: 0.9688
- Precision: 0.9703
- Recall: 0.9688
- F1: 0.9683
- Roc Auc: 0.9987

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 1.3843        | 1.0   | 17   | 1.3585          | 0.4896   | 0.2458    | 0.4896 | 0.3273 | 0.7094  |
| 1.3004        | 2.0   | 34   | 1.2273          | 0.4180   | 0.5441    | 0.4180 | 0.4640 | 0.7541  |
| 1.0841        | 3.0   | 51   | 1.1291          | 0.5430   | 0.5094    | 0.5430 | 0.4415 | 0.8077  |
| 0.8792        | 4.0   | 68   | 0.7692          | 0.4831   | 0.6620    | 0.4831 | 0.5065 | 0.7978  |
| 0.7057        | 5.0   | 85   | 0.7192          | 0.6510   | 0.6349    | 0.6510 | 0.6354 | 0.8585  |
| 0.6424        | 6.0   | 102  | 0.6292          | 0.5299   | 0.6840    | 0.5299 | 0.5244 | 0.8628  |
| 0.5829        | 7.0   | 119  | 0.5684          | 0.5898   | 0.7109    | 0.5898 | 0.6047 | 0.8724  |
| 0.4313        | 8.0   | 136  | 0.3756          | 0.7930   | 0.7945    | 0.7930 | 0.7936 | 0.9476  |
| 0.2881        | 9.0   | 153  | 0.2655          | 0.8516   | 0.8713    | 0.8516 | 0.8530 | 0.9716  |
| 0.1871        | 10.0  | 170  | 0.3171          | 0.8060   | 0.8729    | 0.8060 | 0.8089 | 0.9834  |
| 0.158         | 11.0  | 187  | 0.1419          | 0.9440   | 0.9441    | 0.9440 | 0.9439 | 0.9921  |
| 0.1137        | 12.0  | 204  | 0.1567          | 0.9245   | 0.9283    | 0.9245 | 0.9232 | 0.9932  |
| 0.0658        | 13.0  | 221  | 0.1298          | 0.9453   | 0.9462    | 0.9453 | 0.9455 | 0.9944  |
| 0.0696        | 14.0  | 238  | 0.1345          | 0.9466   | 0.9470    | 0.9466 | 0.9467 | 0.9948  |
| 0.043         | 15.0  | 255  | 0.1541          | 0.9674   | 0.9684    | 0.9674 | 0.9674 | 0.9972  |
| 0.0393        | 16.0  | 272  | 0.0805          | 0.9622   | 0.9633    | 0.9622 | 0.9624 | 0.9973  |
| 0.0339        | 17.0  | 289  | 0.1905          | 0.9466   | 0.9522    | 0.9466 | 0.9469 | 0.9966  |
| 0.0466        | 18.0  | 306  | 0.1001          | 0.9401   | 0.9468    | 0.9401 | 0.9413 | 0.9975  |
| 0.0322        | 19.0  | 323  | 0.0643          | 0.9792   | 0.9800    | 0.9792 | 0.9792 | 0.9990  |
| 0.0184        | 20.0  | 340  | 0.1204          | 0.9844   | 0.9846    | 0.9844 | 0.9842 | 0.9985  |
| 0.0201        | 21.0  | 357  | 0.0876          | 0.9779   | 0.9786    | 0.9779 | 0.9778 | 0.9992  |
| 0.0212        | 22.0  | 374  | 0.1340          | 0.9570   | 0.9611    | 0.9570 | 0.9574 | 0.9985  |
| 0.0168        | 23.0  | 391  | 0.0807          | 0.9661   | 0.9689    | 0.9661 | 0.9664 | 0.9992  |
| 0.0158        | 24.0  | 408  | 0.1210          | 0.9740   | 0.9745    | 0.9740 | 0.9738 | 0.9983  |
| 0.0135        | 25.0  | 425  | 0.1960          | 0.9688   | 0.9703    | 0.9688 | 0.9683 | 0.9987  |


### Framework versions

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

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