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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: switch_gate-leaf-disease-convnextv2-base-1k-224
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: None
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9355140186915888
---
<!-- 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. -->
# switch_gate-leaf-disease-convnextv2-base-1k-224
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: 0.1746
- Accuracy: 0.9355
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6169 | 0.98 | 16 | 0.4210 | 0.8285 |
| 0.3115 | 1.97 | 32 | 0.2653 | 0.8949 |
| 0.2375 | 2.95 | 48 | 0.2198 | 0.9117 |
| 0.1999 | 4.0 | 65 | 0.2004 | 0.9234 |
| 0.1916 | 4.98 | 81 | 0.1841 | 0.9290 |
| 0.1771 | 5.97 | 97 | 0.1897 | 0.9238 |
| 0.168 | 6.95 | 113 | 0.1799 | 0.9308 |
| 0.1592 | 8.0 | 130 | 0.1782 | 0.9332 |
| 0.1542 | 8.98 | 146 | 0.1728 | 0.9322 |
| 0.1521 | 9.97 | 162 | 0.1808 | 0.9346 |
| 0.1501 | 10.95 | 178 | 0.1728 | 0.9388 |
| 0.1426 | 12.0 | 195 | 0.1756 | 0.9346 |
| 0.1389 | 12.98 | 211 | 0.1759 | 0.9369 |
| 0.1391 | 13.97 | 227 | 0.1747 | 0.9364 |
| 0.136 | 14.95 | 243 | 0.1744 | 0.9364 |
| 0.1327 | 15.75 | 256 | 0.1746 | 0.9355 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1
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