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# save-model-final-fork

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window16-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window16-256) on the jbarat/plant_species dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0002
- Accuracy: 1.0

## 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: 0.0003
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 21

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| No log        | 1.0   | 10   | 0.725    | 0.7459          |
| No log        | 2.0   | 20   | 0.875    | 0.5996          |
| No log        | 3.0   | 30   | 0.7375   | 0.8398          |
| No log        | 4.0   | 40   | 0.8125   | 0.6444          |
| No log        | 5.0   | 50   | 0.8375   | 0.6891          |
| No log        | 6.0   | 60   | 0.825    | 0.6675          |
| No log        | 7.0   | 70   | 0.8375   | 0.7300          |
| No log        | 8.0   | 80   | 0.85     | 0.8635          |
| No log        | 9.0   | 90   | 0.95     | 0.3333          |
| 0.1657        | 10.0  | 100  | 0.9375   | 0.2634          |
| 0.1657        | 11.0  | 110  | 0.9375   | 0.3821          |
| 0.1657        | 12.0  | 120  | 0.9625   | 0.2343          |
| 0.1657        | 13.0  | 130  | 0.9375   | 0.3103          |
| 0.1657        | 14.0  | 140  | 0.95     | 0.3481          |
| 0.1657        | 15.0  | 150  | 0.9625   | 0.2419          |
| 0.1657        | 16.0  | 160  | 0.9375   | 0.2408          |
| 0.1657        | 17.0  | 170  | 0.95     | 0.3202          |
| 0.1657        | 18.0  | 180  | 0.9125   | 0.4016          |
| 0.1657        | 19.0  | 190  | 0.925    | 0.3918          |
| 0.0254        | 20.0  | 200  | 0.9375   | 0.3874          |
| 0.0254        | 21.0  | 210  | 0.0006   | 1.0             |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2

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