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# flowing-yogurt-213

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: 1.3359
- Accuracy: 0.3841
- Precision: 0.5072
- Recall: 0.3841
- F1: 0.3969
- Roc Auc: 0.6977

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 1.4164        | 1.0   | 17   | 1.4507          | 0.0065   | 0.1680    | 0.0065 | 0.0026 | 0.5489  |
| 1.4036        | 2.0   | 34   | 1.4003          | 0.1120   | 0.4643    | 0.1120 | 0.1725 | 0.5986  |
| 1.3866        | 3.0   | 51   | 1.3685          | 0.3516   | 0.4511    | 0.3516 | 0.3868 | 0.6448  |
| 1.3819        | 4.0   | 68   | 1.3547          | 0.4089   | 0.4425    | 0.4089 | 0.4095 | 0.6679  |
| 1.3686        | 5.0   | 85   | 1.3514          | 0.4206   | 0.4565    | 0.4206 | 0.4196 | 0.6797  |
| 1.3566        | 6.0   | 102  | 1.3485          | 0.4115   | 0.4791    | 0.4115 | 0.4149 | 0.6856  |
| 1.3505        | 7.0   | 119  | 1.3492          | 0.3763   | 0.4884    | 0.3763 | 0.4002 | 0.6901  |
| 1.3416        | 8.0   | 136  | 1.3432          | 0.3984   | 0.4683    | 0.3984 | 0.4025 | 0.6934  |
| 1.3411        | 9.0   | 153  | 1.3422          | 0.3789   | 0.4768    | 0.3789 | 0.3883 | 0.6953  |
| 1.3432        | 10.0  | 170  | 1.3400          | 0.375    | 0.5029    | 0.375  | 0.3917 | 0.6958  |
| 1.3286        | 11.0  | 187  | 1.3365          | 0.3854   | 0.4977    | 0.3854 | 0.3983 | 0.6970  |
| 1.33          | 12.0  | 204  | 1.3354          | 0.3893   | 0.5007    | 0.3893 | 0.4007 | 0.6976  |
| 1.3297        | 13.0  | 221  | 1.3360          | 0.3841   | 0.5072    | 0.3841 | 0.3969 | 0.6976  |
| 1.329         | 14.0  | 238  | 1.3359          | 0.3841   | 0.5072    | 0.3841 | 0.3969 | 0.6977  |
| 1.3398        | 15.0  | 255  | 1.3359          | 0.3841   | 0.5072    | 0.3841 | 0.3969 | 0.6977  |


### Framework versions

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

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