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# still-universe-209

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: 0.5721
- Accuracy: 0.6497
- Precision: 0.6965
- Recall: 0.6497
- F1: 0.6583
- Roc Auc: 0.8795

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 1.379         | 1.0   | 17   | 1.3021          | 0.4544   | 0.5543    | 0.4544 | 0.4617 | 0.7377  |
| 1.3695        | 2.0   | 34   | 1.2286          | 0.5391   | 0.5315    | 0.5391 | 0.5266 | 0.7806  |
| 1.1945        | 3.0   | 51   | 1.1127          | 0.5794   | 0.5651    | 0.5794 | 0.5647 | 0.8098  |
| 1.0517        | 4.0   | 68   | 0.8318          | 0.5872   | 0.6134    | 0.5872 | 0.5961 | 0.8273  |
| 1.0323        | 5.0   | 85   | 0.8958          | 0.5156   | 0.6297    | 0.5156 | 0.5319 | 0.8189  |
| 0.9029        | 6.0   | 102  | 0.7313          | 0.5365   | 0.6126    | 0.5365 | 0.5398 | 0.8267  |
| 0.9002        | 7.0   | 119  | 0.7217          | 0.5794   | 0.5998    | 0.5794 | 0.5558 | 0.8445  |
| 0.7855        | 8.0   | 136  | 0.6522          | 0.6029   | 0.6629    | 0.6029 | 0.6064 | 0.8581  |
| 0.756         | 9.0   | 153  | 0.6371          | 0.5964   | 0.6263    | 0.5964 | 0.5653 | 0.8643  |
| 0.7164        | 10.0  | 170  | 0.6291          | 0.5690   | 0.6930    | 0.5690 | 0.5780 | 0.8579  |
| 0.6894        | 11.0  | 187  | 0.6194          | 0.5938   | 0.6360    | 0.5938 | 0.5735 | 0.8699  |
| 0.6606        | 12.0  | 204  | 0.5834          | 0.6289   | 0.6906    | 0.6289 | 0.6402 | 0.8742  |
| 0.6273        | 13.0  | 221  | 0.5766          | 0.6510   | 0.6972    | 0.6510 | 0.6607 | 0.8780  |
| 0.6046        | 14.0  | 238  | 0.5732          | 0.6497   | 0.6965    | 0.6497 | 0.6583 | 0.8790  |
| 0.6255        | 15.0  | 255  | 0.5721          | 0.6497   | 0.6965    | 0.6497 | 0.6583 | 0.8795  |


### Framework versions

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

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