---
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-tiny-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: 0.8649532710280374
---

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

This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4109
- Accuracy: 0.8650

## 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: 480
- eval_batch_size: 480
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1920
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 7.8796        | 0.98  | 10   | 3.9572          | 0.1706   |
| 2.3762        | 1.95  | 20   | 1.4334          | 0.6178   |
| 1.1413        | 2.93  | 30   | 0.8877          | 0.6841   |
| 0.7549        | 4.0   | 41   | 0.6403          | 0.7724   |
| 0.5904        | 4.98  | 51   | 0.5366          | 0.8098   |
| 0.5152        | 5.95  | 61   | 0.4799          | 0.8369   |
| 0.4764        | 6.93  | 71   | 0.4567          | 0.8486   |
| 0.4386        | 8.0   | 82   | 0.4421          | 0.8509   |
| 0.4306        | 8.98  | 92   | 0.4381          | 0.8519   |
| 0.4266        | 9.95  | 102  | 0.4296          | 0.8603   |
| 0.4072        | 10.93 | 112  | 0.4196          | 0.8593   |
| 0.4033        | 12.0  | 123  | 0.4127          | 0.8621   |
| 0.3982        | 12.98 | 133  | 0.4125          | 0.8640   |
| 0.3993        | 13.95 | 143  | 0.4097          | 0.8631   |
| 0.3812        | 14.63 | 150  | 0.4109          | 0.8650   |


### Framework versions

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