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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: Expert1-leaf-disease-convnextv2-base-1k-224-0_4
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: 0.776566757493188
---
<!-- 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. -->
# Expert1-leaf-disease-convnextv2-base-1k-224-0_4
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: 0.5130
- Accuracy: 0.7766
## 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: 300
- eval_batch_size: 300
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1200
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.73 | 2 | 1.5191 | 0.4986 |
| No log | 1.82 | 5 | 1.1824 | 0.7003 |
| No log | 2.91 | 8 | 0.9376 | 0.7030 |
| 1.2488 | 4.0 | 11 | 0.7720 | 0.7030 |
| 1.2488 | 4.73 | 13 | 0.7011 | 0.7057 |
| 1.2488 | 5.82 | 16 | 0.6272 | 0.7275 |
| 1.2488 | 6.91 | 19 | 0.5783 | 0.7738 |
| 0.6707 | 8.0 | 22 | 0.5519 | 0.7820 |
| 0.6707 | 8.73 | 24 | 0.5381 | 0.7711 |
| 0.6707 | 9.82 | 27 | 0.5263 | 0.7684 |
| 0.5104 | 10.91 | 30 | 0.5152 | 0.7738 |
| 0.5104 | 11.64 | 32 | 0.5130 | 0.7766 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1
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