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---
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-tiny-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: 0.8649532710280374
---
<!-- 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-tiny-1k-224-finetuned-cassava-leaf-disease
This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4109
- Accuracy: 0.8650
## 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: 480
- eval_batch_size: 480
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1920
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 7.8796 | 0.98 | 10 | 3.9572 | 0.1706 |
| 2.3762 | 1.95 | 20 | 1.4334 | 0.6178 |
| 1.1413 | 2.93 | 30 | 0.8877 | 0.6841 |
| 0.7549 | 4.0 | 41 | 0.6403 | 0.7724 |
| 0.5904 | 4.98 | 51 | 0.5366 | 0.8098 |
| 0.5152 | 5.95 | 61 | 0.4799 | 0.8369 |
| 0.4764 | 6.93 | 71 | 0.4567 | 0.8486 |
| 0.4386 | 8.0 | 82 | 0.4421 | 0.8509 |
| 0.4306 | 8.98 | 92 | 0.4381 | 0.8519 |
| 0.4266 | 9.95 | 102 | 0.4296 | 0.8603 |
| 0.4072 | 10.93 | 112 | 0.4196 | 0.8593 |
| 0.4033 | 12.0 | 123 | 0.4127 | 0.8621 |
| 0.3982 | 12.98 | 133 | 0.4125 | 0.8640 |
| 0.3993 | 13.95 | 143 | 0.4097 | 0.8631 |
| 0.3812 | 14.63 | 150 | 0.4109 | 0.8650 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1
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