---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: BaseModel-leaf-disease-convnextv2-base-22k-224-0_1_2_3_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: 0.8813084112149533
---

<!-- 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. -->

# BaseModel-leaf-disease-convnextv2-base-22k-224-0_1_2_3_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: 0.3419
- Accuracy: 0.8813

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4178        | 0.98  | 16   | 0.9457          | 0.6215   |
| 0.6112        | 1.97  | 32   | 0.4856          | 0.8294   |
| 0.4468        | 2.95  | 48   | 0.4163          | 0.8575   |
| 0.3659        | 4.0   | 65   | 0.3790          | 0.8715   |
| 0.3481        | 4.98  | 81   | 0.3655          | 0.8785   |
| 0.3338        | 5.97  | 97   | 0.3637          | 0.8748   |
| 0.3216        | 6.95  | 113  | 0.3568          | 0.8752   |
| 0.2948        | 8.0   | 130  | 0.3493          | 0.8808   |
| 0.2944        | 8.98  | 146  | 0.3483          | 0.8808   |
| 0.2857        | 9.97  | 162  | 0.3474          | 0.8808   |
| 0.2711        | 10.95 | 178  | 0.3442          | 0.8790   |
| 0.2682        | 12.0  | 195  | 0.3418          | 0.8813   |
| 0.252         | 12.98 | 211  | 0.3409          | 0.8827   |
| 0.2598        | 13.97 | 227  | 0.3405          | 0.8827   |
| 0.2621        | 14.95 | 243  | 0.3432          | 0.8813   |
| 0.2602        | 15.75 | 256  | 0.3419          | 0.8813   |


### Framework versions

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