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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: 0.8845794392523364
---
<!-- 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: 0.3329
- Accuracy: 0.8846
## 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: 240
- eval_batch_size: 240
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 960
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.7644 | 0.99 | 20 | 1.5288 | 0.6140 |
| 0.8358 | 1.98 | 40 | 0.6582 | 0.7584 |
| 0.5367 | 2.96 | 60 | 0.4823 | 0.8229 |
| 0.4645 | 4.0 | 81 | 0.4269 | 0.8556 |
| 0.4218 | 4.99 | 101 | 0.3912 | 0.8659 |
| 0.391 | 5.98 | 121 | 0.3637 | 0.8748 |
| 0.3789 | 6.96 | 141 | 0.3554 | 0.8748 |
| 0.3684 | 8.0 | 162 | 0.3489 | 0.8790 |
| 0.3671 | 8.99 | 182 | 0.3503 | 0.8813 |
| 0.3545 | 9.98 | 202 | 0.3442 | 0.8818 |
| 0.339 | 10.96 | 222 | 0.3369 | 0.8841 |
| 0.3225 | 12.0 | 243 | 0.3424 | 0.8808 |
| 0.3228 | 12.99 | 263 | 0.3386 | 0.8850 |
| 0.3141 | 13.98 | 283 | 0.3344 | 0.8846 |
| 0.3219 | 14.81 | 300 | 0.3329 | 0.8846 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1
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