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# grateful-shape-212

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: 1.3777
- Accuracy: 0.2708
- Precision: 0.4203
- Recall: 0.2708
- F1: 0.3127
- Roc Auc: 0.5428

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 1.4367        | 1.0   | 17   | 1.3810          | 0.0898   | 0.4478    | 0.0898 | 0.1092 | 0.5060  |
| 1.3894        | 2.0   | 34   | 1.3751          | 0.1823   | 0.4052    | 0.1823 | 0.2266 | 0.5250  |
| 1.3619        | 3.0   | 51   | 1.3766          | 0.2422   | 0.4100    | 0.2422 | 0.2876 | 0.5369  |
| 1.3523        | 4.0   | 68   | 1.3776          | 0.2708   | 0.4238    | 0.2708 | 0.3132 | 0.5422  |
| 1.3475        | 5.0   | 85   | 1.3777          | 0.2708   | 0.4203    | 0.2708 | 0.3127 | 0.5428  |


### Framework versions

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

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