---
license: apache-2.0
base_model: facebook/convnextv2-base-1k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Expert1-leaf-disease-convnextv2-base-1k-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: 0.776566757493188
---

<!-- 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-1k-224-0_4

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: 0.5130
- Accuracy: 0.7766

## 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    | 1.5191          | 0.4986   |
| No log        | 1.82  | 5    | 1.1824          | 0.7003   |
| No log        | 2.91  | 8    | 0.9376          | 0.7030   |
| 1.2488        | 4.0   | 11   | 0.7720          | 0.7030   |
| 1.2488        | 4.73  | 13   | 0.7011          | 0.7057   |
| 1.2488        | 5.82  | 16   | 0.6272          | 0.7275   |
| 1.2488        | 6.91  | 19   | 0.5783          | 0.7738   |
| 0.6707        | 8.0   | 22   | 0.5519          | 0.7820   |
| 0.6707        | 8.73  | 24   | 0.5381          | 0.7711   |
| 0.6707        | 9.82  | 27   | 0.5263          | 0.7684   |
| 0.5104        | 10.91 | 30   | 0.5152          | 0.7738   |
| 0.5104        | 11.64 | 32   | 0.5130          | 0.7766   |


### Framework versions

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