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# polished-resonance-217

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: 0.5649
- Accuracy: 0.6562
- Precision: 0.6901
- Recall: 0.6562
- F1: 0.6610
- Roc Auc: 0.8810

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 1.4116        | 1.0   | 17   | 1.3279          | 0.4857   | 0.4335    | 0.4857 | 0.4311 | 0.6864  |
| 1.3746        | 2.0   | 34   | 1.1750          | 0.4870   | 0.5240    | 0.4870 | 0.4995 | 0.7706  |
| 1.1647        | 3.0   | 51   | 0.9635          | 0.5221   | 0.5858    | 0.5221 | 0.5105 | 0.7994  |
| 1.0134        | 4.0   | 68   | 0.8929          | 0.5234   | 0.5823    | 0.5234 | 0.5402 | 0.7975  |
| 0.9625        | 5.0   | 85   | 0.8761          | 0.5729   | 0.5577    | 0.5729 | 0.5576 | 0.8274  |
| 0.9373        | 6.0   | 102  | 0.9938          | 0.5768   | 0.5625    | 0.5768 | 0.5512 | 0.8306  |
| 0.8421        | 7.0   | 119  | 0.7692          | 0.4492   | 0.6542    | 0.4492 | 0.4196 | 0.8073  |
| 0.7684        | 8.0   | 136  | 0.6549          | 0.5977   | 0.6615    | 0.5977 | 0.6121 | 0.8453  |
| 0.7312        | 9.0   | 153  | 0.6826          | 0.5794   | 0.6666    | 0.5794 | 0.5661 | 0.8618  |
| 0.6827        | 10.0  | 170  | 0.6071          | 0.6068   | 0.6560    | 0.6068 | 0.6057 | 0.8665  |
| 0.6731        | 11.0  | 187  | 0.5996          | 0.6146   | 0.6701    | 0.6146 | 0.6224 | 0.8691  |
| 0.6675        | 12.0  | 204  | 0.6269          | 0.5703   | 0.7065    | 0.5703 | 0.5792 | 0.8664  |
| 0.658         | 13.0  | 221  | 0.5710          | 0.6536   | 0.6925    | 0.6536 | 0.6603 | 0.8783  |
| 0.6081        | 14.0  | 238  | 0.5664          | 0.6562   | 0.6910    | 0.6562 | 0.6603 | 0.8807  |
| 0.6179        | 15.0  | 255  | 0.5649          | 0.6562   | 0.6901    | 0.6562 | 0.6610 | 0.8810  |


### Framework versions

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

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