---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Expert1-leaf-disease-convnextv2-base-22k-224-0_4
  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: 0.8337874659400545
---

<!-- 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. -->

# Expert1-leaf-disease-convnextv2-base-22k-224-0_4

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: 0.3647
- Accuracy: 0.8338

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.73  | 2    | 1.4423          | 0.3842   |
| No log        | 1.82  | 5    | 0.6525          | 0.6921   |
| No log        | 2.91  | 8    | 0.4914          | 0.7466   |
| 0.9097        | 4.0   | 11   | 0.4710          | 0.7793   |
| 0.9097        | 4.73  | 13   | 0.4358          | 0.8011   |
| 0.9097        | 5.82  | 16   | 0.4048          | 0.8174   |
| 0.9097        | 6.91  | 19   | 0.3875          | 0.8229   |
| 0.3808        | 8.0   | 22   | 0.3756          | 0.8365   |
| 0.3808        | 8.73  | 24   | 0.3794          | 0.8229   |
| 0.3808        | 9.82  | 27   | 0.3701          | 0.8283   |
| 0.3221        | 10.91 | 30   | 0.3659          | 0.8338   |
| 0.3221        | 11.64 | 32   | 0.3647          | 0.8338   |


### Framework versions

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