---
license: apache-2.0
base_model: facebook/convnextv2-base-1k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-base-1k-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: 0.8841121495327103
---

<!-- 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-1k-224-finetuned-cassava-leaf-disease

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: 0.3624
- Accuracy: 0.8841

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 7.5825        | 0.96  | 13   | 2.5252          | 0.4874   |
| 2.4869        | 2.0   | 27   | 1.0172          | 0.6388   |
| 0.7793        | 2.96  | 40   | 0.6048          | 0.7925   |
| 0.5807        | 4.0   | 54   | 0.4873          | 0.8327   |
| 0.5079        | 4.96  | 67   | 0.4330          | 0.8514   |
| 0.4363        | 6.0   | 81   | 0.4140          | 0.8668   |
| 0.4118        | 6.96  | 94   | 0.3962          | 0.8743   |
| 0.3918        | 8.0   | 108  | 0.3924          | 0.8748   |
| 0.3669        | 8.96  | 121  | 0.3816          | 0.8822   |
| 0.3687        | 10.0  | 135  | 0.3784          | 0.8776   |
| 0.3645        | 10.96 | 148  | 0.3684          | 0.8846   |
| 0.349         | 12.0  | 162  | 0.3706          | 0.8804   |
| 0.3341        | 12.96 | 175  | 0.3678          | 0.8813   |
| 0.3304        | 14.0  | 189  | 0.3618          | 0.8794   |
| 0.3318        | 14.96 | 202  | 0.3677          | 0.8808   |
| 0.3178        | 16.0  | 216  | 0.3626          | 0.8818   |
| 0.3209        | 16.96 | 229  | 0.3606          | 0.8822   |
| 0.3129        | 18.0  | 243  | 0.3615          | 0.8836   |
| 0.3013        | 18.96 | 256  | 0.3627          | 0.8841   |
| 0.3046        | 19.26 | 260  | 0.3624          | 0.8841   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1