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---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-base-22k-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: 0.8827102803738318
---
<!-- 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-224-finetuned-cassava-leaf-disease
This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3524
- Accuracy: 0.8827
## 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: 360
- eval_batch_size: 360
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1440
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.504 | 0.96 | 13 | 0.9739 | 0.6159 |
| 0.9073 | 2.0 | 27 | 0.5204 | 0.8187 |
| 0.4289 | 2.96 | 40 | 0.4312 | 0.85 |
| 0.3901 | 4.0 | 54 | 0.3916 | 0.8645 |
| 0.34 | 4.96 | 67 | 0.3755 | 0.8715 |
| 0.3326 | 6.0 | 81 | 0.3746 | 0.8710 |
| 0.3153 | 6.96 | 94 | 0.3684 | 0.8771 |
| 0.3103 | 8.0 | 108 | 0.3543 | 0.8780 |
| 0.292 | 8.96 | 121 | 0.3620 | 0.8804 |
| 0.2953 | 10.0 | 135 | 0.3545 | 0.8794 |
| 0.2879 | 10.96 | 148 | 0.3550 | 0.8808 |
| 0.2779 | 12.0 | 162 | 0.3504 | 0.8799 |
| 0.2736 | 12.96 | 175 | 0.3554 | 0.8818 |
| 0.2769 | 14.0 | 189 | 0.3526 | 0.8846 |
| 0.2625 | 14.96 | 202 | 0.3527 | 0.8813 |
| 0.2625 | 15.41 | 208 | 0.3524 | 0.8827 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1
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