---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-base-22k-224-finetuned-cassava-leaf-disease
  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: 0.8827102803738318
---

<!-- 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. -->

# convnextv2-base-22k-224-finetuned-cassava-leaf-disease

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: 0.3524
- Accuracy: 0.8827

## 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: 360
- eval_batch_size: 360
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1440
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.504         | 0.96  | 13   | 0.9739          | 0.6159   |
| 0.9073        | 2.0   | 27   | 0.5204          | 0.8187   |
| 0.4289        | 2.96  | 40   | 0.4312          | 0.85     |
| 0.3901        | 4.0   | 54   | 0.3916          | 0.8645   |
| 0.34          | 4.96  | 67   | 0.3755          | 0.8715   |
| 0.3326        | 6.0   | 81   | 0.3746          | 0.8710   |
| 0.3153        | 6.96  | 94   | 0.3684          | 0.8771   |
| 0.3103        | 8.0   | 108  | 0.3543          | 0.8780   |
| 0.292         | 8.96  | 121  | 0.3620          | 0.8804   |
| 0.2953        | 10.0  | 135  | 0.3545          | 0.8794   |
| 0.2879        | 10.96 | 148  | 0.3550          | 0.8808   |
| 0.2779        | 12.0  | 162  | 0.3504          | 0.8799   |
| 0.2736        | 12.96 | 175  | 0.3554          | 0.8818   |
| 0.2769        | 14.0  | 189  | 0.3526          | 0.8846   |
| 0.2625        | 14.96 | 202  | 0.3527          | 0.8813   |
| 0.2625        | 15.41 | 208  | 0.3524          | 0.8827   |


### Framework versions

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