---
license: apache-2.0
base_model: facebook/convnextv2-huge-1k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-huge-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: 0.8897196261682243
---

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

This model is a fine-tuned version of [facebook/convnextv2-huge-1k-224](https://huggingface.co/facebook/convnextv2-huge-1k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3433
- Accuracy: 0.8897

## 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: 120
- eval_batch_size: 120
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 480
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 7.9894        | 0.25  | 10   | 4.9516          | 0.0206   |
| 2.7782        | 0.5   | 20   | 1.6759          | 0.6196   |
| 1.2699        | 0.75  | 30   | 0.9878          | 0.6626   |
| 0.8247        | 0.99  | 40   | 0.6755          | 0.7640   |
| 0.6353        | 1.24  | 50   | 0.5472          | 0.8079   |
| 0.5418        | 1.49  | 60   | 0.4924          | 0.8369   |
| 0.4577        | 1.74  | 70   | 0.4422          | 0.8537   |
| 0.4627        | 1.99  | 80   | 0.3943          | 0.8706   |
| 0.4235        | 2.24  | 90   | 0.3868          | 0.8715   |
| 0.4068        | 2.48  | 100  | 0.3879          | 0.8645   |
| 0.4088        | 2.73  | 110  | 0.4149          | 0.8579   |
| 0.3866        | 2.98  | 120  | 0.3489          | 0.8836   |
| 0.3776        | 3.23  | 130  | 0.3731          | 0.8743   |
| 0.3303        | 3.48  | 140  | 0.3719          | 0.8734   |
| 0.3548        | 3.73  | 150  | 0.3917          | 0.8668   |
| 0.3638        | 3.98  | 160  | 0.3561          | 0.8738   |
| 0.3292        | 4.22  | 170  | 0.3518          | 0.8855   |
| 0.3363        | 4.47  | 180  | 0.3561          | 0.8850   |
| 0.3123        | 4.72  | 190  | 0.3452          | 0.8794   |
| 0.3395        | 4.97  | 200  | 0.3385          | 0.8841   |
| 0.2851        | 5.22  | 210  | 0.3467          | 0.8883   |
| 0.3113        | 5.47  | 220  | 0.3393          | 0.8841   |
| 0.3035        | 5.71  | 230  | 0.3444          | 0.8785   |
| 0.3123        | 5.96  | 240  | 0.3321          | 0.8804   |
| 0.2683        | 6.21  | 250  | 0.3407          | 0.8813   |
| 0.2811        | 6.46  | 260  | 0.3396          | 0.8850   |
| 0.2779        | 6.71  | 270  | 0.3318          | 0.8869   |
| 0.2733        | 6.96  | 280  | 0.3342          | 0.8897   |
| 0.2661        | 7.2   | 290  | 0.3303          | 0.8916   |
| 0.2588        | 7.45  | 300  | 0.3387          | 0.8921   |
| 0.2586        | 7.7   | 310  | 0.3373          | 0.8888   |
| 0.2641        | 7.95  | 320  | 0.3328          | 0.8860   |
| 0.2408        | 8.2   | 330  | 0.3490          | 0.8818   |
| 0.2375        | 8.45  | 340  | 0.3419          | 0.8846   |
| 0.2507        | 8.7   | 350  | 0.3473          | 0.8874   |
| 0.2555        | 8.94  | 360  | 0.3382          | 0.8874   |
| 0.2299        | 9.19  | 370  | 0.3399          | 0.8888   |
| 0.2309        | 9.44  | 380  | 0.3415          | 0.8855   |
| 0.2344        | 9.69  | 390  | 0.3431          | 0.8897   |
| 0.2253        | 9.94  | 400  | 0.3433          | 0.8897   |


### Framework versions

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