---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Expert2-leaf-disease-convnextv2-base-22k-224-1_2_3
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9498025944726453
---

<!-- 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. -->

# Expert2-leaf-disease-convnextv2-base-22k-224-1_2_3

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: 0.1599
- Accuracy: 0.9498

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0623        | 0.96  | 13   | 0.6227          | 0.7456   |
| 0.5754        | 2.0   | 27   | 0.2772          | 0.8996   |
| 0.233         | 2.96  | 40   | 0.2167          | 0.9255   |
| 0.1972        | 4.0   | 54   | 0.1777          | 0.9425   |
| 0.1763        | 4.96  | 67   | 0.1742          | 0.9425   |
| 0.1631        | 6.0   | 81   | 0.1650          | 0.9459   |
| 0.1532        | 6.96  | 94   | 0.1708          | 0.9391   |
| 0.1384        | 8.0   | 108  | 0.1627          | 0.9442   |
| 0.1415        | 8.96  | 121  | 0.1662          | 0.9447   |
| 0.133         | 10.0  | 135  | 0.1620          | 0.9470   |
| 0.1362        | 10.96 | 148  | 0.1715          | 0.9442   |
| 0.1248        | 12.0  | 162  | 0.1628          | 0.9447   |
| 0.1217        | 12.96 | 175  | 0.1607          | 0.9475   |
| 0.1264        | 14.0  | 189  | 0.1587          | 0.9475   |
| 0.1178        | 14.96 | 202  | 0.1595          | 0.9498   |
| 0.1178        | 15.41 | 208  | 0.1599          | 0.9498   |


### Framework versions

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