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# 2025-02-10-08-48-20-convnextv2-tiny-1k-224

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: 0.0276
- Precision: 0.9953
- Recall: 0.9951
- F1: 0.9951
- Accuracy: 0.9952
- Top1 Accuracy: 0.9951
- Error Rate: 0.0048

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 3407
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Top1 Accuracy | Error Rate |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|
| 1.1857        | 1.0   | 103  | 0.2269          | 0.9480    | 0.9390 | 0.9396 | 0.9449   | 0.9390        | 0.0551     |
| 0.2112        | 2.0   | 206  | 0.1580          | 0.9583    | 0.9561 | 0.9563 | 0.9554   | 0.9561        | 0.0446     |
| 0.1067        | 3.0   | 309  | 0.1165          | 0.9634    | 0.9610 | 0.9613 | 0.9571   | 0.9610        | 0.0429     |
| 0.0922        | 4.0   | 412  | 0.1750          | 0.9608    | 0.9537 | 0.9532 | 0.9549   | 0.9537        | 0.0451     |
| 0.0346        | 5.0   | 515  | 0.0920          | 0.9827    | 0.9805 | 0.9805 | 0.9845   | 0.9805        | 0.0155     |
| 0.018         | 6.0   | 618  | 0.0483          | 0.9881    | 0.9878 | 0.9877 | 0.9886   | 0.9878        | 0.0114     |
| 0.0114        | 7.0   | 721  | 0.0276          | 0.9953    | 0.9951 | 0.9951 | 0.9952   | 0.9951        | 0.0048     |
| 0.0067        | 8.0   | 824  | 0.0423          | 0.9906    | 0.9902 | 0.9903 | 0.9894   | 0.9902        | 0.0106     |
| 0.0014        | 9.0   | 927  | 0.0310          | 0.9953    | 0.9951 | 0.9951 | 0.9952   | 0.9951        | 0.0048     |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.20.3

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