---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: switch_gate-leaf-disease-convnextv2-base-22k-224
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: None
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9378504672897197
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# switch_gate-leaf-disease-convnextv2-base-22k-224

This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1674
- Accuracy: 0.9379

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6005        | 0.98  | 16   | 0.3258          | 0.8701   |
| 0.234         | 1.97  | 32   | 0.2121          | 0.9173   |
| 0.197         | 2.95  | 48   | 0.1869          | 0.9271   |
| 0.1613        | 4.0   | 65   | 0.1692          | 0.9336   |
| 0.1536        | 4.98  | 81   | 0.1616          | 0.9397   |
| 0.1426        | 5.97  | 97   | 0.1628          | 0.9355   |
| 0.132         | 6.95  | 113  | 0.1609          | 0.9407   |
| 0.1304        | 8.0   | 130  | 0.1597          | 0.9402   |
| 0.1245        | 8.98  | 146  | 0.1628          | 0.9350   |
| 0.1224        | 9.97  | 162  | 0.1664          | 0.9364   |
| 0.1143        | 10.95 | 178  | 0.1615          | 0.9388   |
| 0.1106        | 12.0  | 195  | 0.1641          | 0.9393   |
| 0.103         | 12.98 | 211  | 0.1689          | 0.9374   |
| 0.1047        | 13.97 | 227  | 0.1673          | 0.9379   |
| 0.102         | 14.95 | 243  | 0.1681          | 0.9397   |
| 0.1038        | 15.75 | 256  | 0.1674          | 0.9379   |


### Framework versions

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