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---
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-randomflip
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: 0.8766355140186916
---
<!-- 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-randomflip
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: 0.3704
- Accuracy: 0.8766
## 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: 400
- eval_batch_size: 400
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1600
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5605 | 0.98 | 12 | 1.2754 | 0.6150 |
| 1.2015 | 1.96 | 24 | 0.9009 | 0.6290 |
| 0.9048 | 2.94 | 36 | 0.6987 | 0.7701 |
| 0.7362 | 4.0 | 49 | 0.5497 | 0.8206 |
| 0.5294 | 4.98 | 61 | 0.4712 | 0.8542 |
| 0.4777 | 5.96 | 73 | 0.4451 | 0.8547 |
| 0.458 | 6.94 | 85 | 0.4197 | 0.8579 |
| 0.4208 | 8.0 | 98 | 0.4084 | 0.8682 |
| 0.4042 | 8.98 | 110 | 0.3930 | 0.8692 |
| 0.4071 | 9.96 | 122 | 0.3879 | 0.8743 |
| 0.3868 | 10.94 | 134 | 0.3923 | 0.8715 |
| 0.3849 | 12.0 | 147 | 0.3763 | 0.8748 |
| 0.3744 | 12.98 | 159 | 0.3732 | 0.8776 |
| 0.3739 | 13.96 | 171 | 0.3708 | 0.8748 |
| 0.361 | 14.94 | 183 | 0.3693 | 0.8818 |
| 0.3725 | 15.67 | 192 | 0.3704 | 0.8766 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1
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