---
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: 0.866822429906542
---

<!-- 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: 0.3847
- Accuracy: 0.8668

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4746        | 0.98  | 16   | 1.1574          | 0.6150   |
| 0.9672        | 1.97  | 32   | 0.8080          | 0.7084   |
| 0.7544        | 2.95  | 48   | 0.6316          | 0.7832   |
| 0.5568        | 4.0   | 65   | 0.5164          | 0.8350   |
| 0.4714        | 4.98  | 81   | 0.4622          | 0.8486   |
| 0.4361        | 5.97  | 97   | 0.4373          | 0.8509   |
| 0.412         | 6.95  | 113  | 0.4347          | 0.8570   |
| 0.3786        | 8.0   | 130  | 0.4091          | 0.8598   |
| 0.3741        | 8.98  | 146  | 0.4161          | 0.8598   |
| 0.3649        | 9.97  | 162  | 0.4062          | 0.8668   |
| 0.3532        | 10.95 | 178  | 0.3931          | 0.8668   |
| 0.3467        | 12.0  | 195  | 0.3884          | 0.8645   |
| 0.3379        | 12.98 | 211  | 0.3850          | 0.8645   |
| 0.3428        | 13.97 | 227  | 0.3911          | 0.8715   |
| 0.3409        | 14.95 | 243  | 0.3887          | 0.8687   |
| 0.3397        | 15.75 | 256  | 0.3847          | 0.8668   |


### Framework versions

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