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# Expert2-leaf-disease-convnextv2-base-1k-224-1_2_3

This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1892
- Accuracy: 0.9391

## 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: 300
- eval_batch_size: 300
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1200
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 16

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5107        | 0.96  | 13   | 1.0756          | 0.7422   |
| 1.0022        | 2.0   | 27   | 0.5781          | 0.7603   |
| 0.4503        | 2.96  | 40   | 0.3902          | 0.8697   |
| 0.3704        | 4.0   | 54   | 0.3101          | 0.9058   |
| 0.2996        | 4.96  | 67   | 0.2573          | 0.9165   |
| 0.2405        | 6.0   | 81   | 0.2647          | 0.9075   |
| 0.2268        | 6.96  | 94   | 0.2259          | 0.9233   |
| 0.2036        | 8.0   | 108  | 0.2126          | 0.9329   |
| 0.1957        | 8.96  | 121  | 0.2149          | 0.9329   |
| 0.1885        | 10.0  | 135  | 0.1974          | 0.9385   |
| 0.1866        | 10.96 | 148  | 0.1983          | 0.9318   |
| 0.1771        | 12.0  | 162  | 0.2066          | 0.9363   |
| 0.1752        | 12.96 | 175  | 0.1975          | 0.9357   |
| 0.1744        | 14.0  | 189  | 0.1893          | 0.9380   |
| 0.1636        | 14.96 | 202  | 0.1889          | 0.9391   |
| 0.1636        | 15.41 | 208  | 0.1892          | 0.9391   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1

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