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# switch_gate-leaf-disease-convnextv2-base-1k-224

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: 0.1746
- Accuracy: 0.9355

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6169        | 0.98  | 16   | 0.4210          | 0.8285   |
| 0.3115        | 1.97  | 32   | 0.2653          | 0.8949   |
| 0.2375        | 2.95  | 48   | 0.2198          | 0.9117   |
| 0.1999        | 4.0   | 65   | 0.2004          | 0.9234   |
| 0.1916        | 4.98  | 81   | 0.1841          | 0.9290   |
| 0.1771        | 5.97  | 97   | 0.1897          | 0.9238   |
| 0.168         | 6.95  | 113  | 0.1799          | 0.9308   |
| 0.1592        | 8.0   | 130  | 0.1782          | 0.9332   |
| 0.1542        | 8.98  | 146  | 0.1728          | 0.9322   |
| 0.1521        | 9.97  | 162  | 0.1808          | 0.9346   |
| 0.1501        | 10.95 | 178  | 0.1728          | 0.9388   |
| 0.1426        | 12.0  | 195  | 0.1756          | 0.9346   |
| 0.1389        | 12.98 | 211  | 0.1759          | 0.9369   |
| 0.1391        | 13.97 | 227  | 0.1747          | 0.9364   |
| 0.136         | 14.95 | 243  | 0.1744          | 0.9364   |
| 0.1327        | 15.75 | 256  | 0.1746          | 0.9355   |


### Framework versions

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

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