---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-base-22k-384-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: 0.8785046728971962
---

<!-- 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-384-finetuned-cassava-leaf-disease

This model is a fine-tuned version of [facebook/convnextv2-base-22k-384](https://huggingface.co/facebook/convnextv2-base-22k-384) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3755
- Accuracy: 0.8785

## 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: 140
- eval_batch_size: 140
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 560
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7713        | 0.99  | 34   | 0.5754          | 0.7949   |
| 0.3953        | 2.0   | 69   | 0.3769          | 0.8650   |
| 0.3478        | 2.99  | 103  | 0.3717          | 0.8673   |
| 0.3296        | 4.0   | 138  | 0.3696          | 0.8752   |
| 0.3058        | 4.99  | 172  | 0.3387          | 0.8808   |
| 0.2791        | 6.0   | 207  | 0.3480          | 0.8804   |
| 0.2541        | 6.99  | 241  | 0.3483          | 0.8799   |
| 0.247         | 8.0   | 276  | 0.3590          | 0.8743   |
| 0.2395        | 8.99  | 310  | 0.3505          | 0.8794   |
| 0.2139        | 10.0  | 345  | 0.3702          | 0.8766   |
| 0.2116        | 10.99 | 379  | 0.3702          | 0.8766   |
| 0.204         | 12.0  | 414  | 0.3661          | 0.8762   |
| 0.183         | 12.99 | 448  | 0.3705          | 0.8776   |
| 0.1856        | 14.0  | 483  | 0.3861          | 0.8780   |
| 0.1641        | 14.99 | 517  | 0.3758          | 0.8766   |
| 0.1784        | 15.77 | 544  | 0.3755          | 0.8785   |


### Framework versions

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