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# convnextv2-tiny-1k-224-finetuned-barkley

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: 0.0083
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
- Top1 Accuracy: 1.0
- Error Rate: 0.0

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Top1 Accuracy | Error Rate |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|
| 1.4696        | 1.0   | 38   | 1.1807          | 0.7273    | 0.6513 | 0.6180 | 0.6768   | 0.6513        | 0.3232     |
| 0.7197        | 2.0   | 76   | 0.3719          | 0.9439    | 0.9408 | 0.9404 | 0.9434   | 0.9474        | 0.0566     |
| 0.2388        | 3.0   | 114  | 0.1489          | 0.9688    | 0.9671 | 0.9671 | 0.9716   | 0.9671        | 0.0284     |
| 0.1048        | 4.0   | 152  | 0.0730          | 0.9868    | 0.9868 | 0.9868 | 0.9878   | 0.9868        | 0.0122     |
| 0.1103        | 5.0   | 190  | 0.0288          | 0.9868    | 0.9868 | 0.9868 | 0.9878   | 0.9868        | 0.0122     |
| 0.072         | 6.0   | 228  | 0.0537          | 0.9877    | 0.9868 | 0.9869 | 0.9868   | 0.9868        | 0.0132     |
| 0.0248        | 7.0   | 266  | 0.0083          | 1.0       | 1.0    | 1.0    | 1.0      | 1.0           | 0.0        |
| 0.0371        | 8.0   | 304  | 0.0653          | 0.9819    | 0.9803 | 0.9802 | 0.9800   | 0.9803        | 0.0200     |
| 0.0626        | 9.0   | 342  | 0.2271          | 0.9545    | 0.9408 | 0.9404 | 0.95     | 0.9408        | 0.0500     |
| 0.07          | 10.0  | 380  | 0.0304          | 0.9936    | 0.9934 | 0.9934 | 0.9933   | 0.9934        | 0.0067     |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1

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