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# swinv2-plantclef

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window16-256](https://huggingface.co/microsoft/swinv2-base-patch4-window16-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0548
- Accuracy: 0.8199
- F1: 0.8190

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 16
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 1.1414        | 1.0   | 897   | 0.9819          | 0.7171   | 0.7046 |
| 0.654         | 2.0   | 1794  | 0.7608          | 0.7694   | 0.7688 |
| 0.394         | 3.0   | 2691  | 0.7461          | 0.7795   | 0.7767 |
| 0.2437        | 4.0   | 3588  | 0.7369          | 0.7917   | 0.7908 |
| 0.1428        | 5.0   | 4485  | 0.7939          | 0.7945   | 0.7929 |
| 0.0878        | 6.0   | 5382  | 0.8352          | 0.7958   | 0.7950 |
| 0.0621        | 7.0   | 6279  | 0.8802          | 0.7945   | 0.7928 |
| 0.0353        | 8.0   | 7176  | 0.9028          | 0.8011   | 0.8005 |
| 0.0241        | 9.0   | 8073  | 0.9592          | 0.8043   | 0.8045 |
| 0.0241        | 10.0  | 8970  | 1.0075          | 0.8068   | 0.8047 |
| 0.0129        | 11.0  | 9867  | 1.0254          | 0.8127   | 0.8120 |
| 0.0058        | 12.0  | 10764 | 1.0340          | 0.8162   | 0.8151 |
| 0.007         | 13.0  | 11661 | 1.0661          | 0.8165   | 0.8159 |
| 0.0052        | 14.0  | 12558 | 1.0533          | 0.8168   | 0.8166 |
| 0.0049        | 15.0  | 13455 | 1.0660          | 0.8174   | 0.8164 |
| 0.015         | 16.0  | 14352 | 1.0548          | 0.8199   | 0.8190 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.0
- Datasets 3.1.0
- Tokenizers 0.20.1

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