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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
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: 0.8841121495327103
---
<!-- 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: 0.3624
- Accuracy: 0.8841
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 7.5825 | 0.96 | 13 | 2.5252 | 0.4874 |
| 2.4869 | 2.0 | 27 | 1.0172 | 0.6388 |
| 0.7793 | 2.96 | 40 | 0.6048 | 0.7925 |
| 0.5807 | 4.0 | 54 | 0.4873 | 0.8327 |
| 0.5079 | 4.96 | 67 | 0.4330 | 0.8514 |
| 0.4363 | 6.0 | 81 | 0.4140 | 0.8668 |
| 0.4118 | 6.96 | 94 | 0.3962 | 0.8743 |
| 0.3918 | 8.0 | 108 | 0.3924 | 0.8748 |
| 0.3669 | 8.96 | 121 | 0.3816 | 0.8822 |
| 0.3687 | 10.0 | 135 | 0.3784 | 0.8776 |
| 0.3645 | 10.96 | 148 | 0.3684 | 0.8846 |
| 0.349 | 12.0 | 162 | 0.3706 | 0.8804 |
| 0.3341 | 12.96 | 175 | 0.3678 | 0.8813 |
| 0.3304 | 14.0 | 189 | 0.3618 | 0.8794 |
| 0.3318 | 14.96 | 202 | 0.3677 | 0.8808 |
| 0.3178 | 16.0 | 216 | 0.3626 | 0.8818 |
| 0.3209 | 16.96 | 229 | 0.3606 | 0.8822 |
| 0.3129 | 18.0 | 243 | 0.3615 | 0.8836 |
| 0.3013 | 18.96 | 256 | 0.3627 | 0.8841 |
| 0.3046 | 19.26 | 260 | 0.3624 | 0.8841 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1
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