---
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: MoE-leaf-disease-convnextv2-base-1k-224
  results: []
---

<!-- 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. -->

# MoE-leaf-disease-convnextv2-base-1k-224

This model is a fine-tuned version of [](https://huggingface.co/) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4329
- Accuracy: 0.8668

## 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: 200
- eval_batch_size: 200
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 800
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4831        | 0.99  | 24   | 0.5000          | 0.8607   |
| 0.3545        | 1.98  | 48   | 0.4135          | 0.8696   |
| 0.3388        | 2.97  | 72   | 0.4527          | 0.8654   |
| 0.3378        | 4.0   | 97   | 0.4225          | 0.8706   |
| 0.3372        | 4.99  | 121  | 0.4032          | 0.8654   |
| 0.326         | 5.98  | 145  | 0.4222          | 0.8654   |
| 0.3437        | 6.97  | 169  | 0.4231          | 0.8640   |
| 0.3157        | 8.0   | 194  | 0.3980          | 0.8720   |
| 0.3193        | 8.99  | 218  | 0.4001          | 0.8682   |
| 0.3027        | 9.98  | 242  | 0.4163          | 0.8650   |
| 0.2933        | 10.97 | 266  | 0.4105          | 0.8715   |
| 0.3041        | 12.0  | 291  | 0.4004          | 0.8729   |
| 0.2845        | 12.99 | 315  | 0.4020          | 0.8720   |
| 0.2845        | 13.98 | 339  | 0.4223          | 0.8715   |
| 0.2797        | 14.97 | 363  | 0.4089          | 0.8678   |
| 0.295         | 16.0  | 388  | 0.4162          | 0.8701   |
| 0.2767        | 16.99 | 412  | 0.4369          | 0.8678   |
| 0.2692        | 17.98 | 436  | 0.4292          | 0.8678   |
| 0.2543        | 18.97 | 460  | 0.4328          | 0.8659   |
| 0.2743        | 19.79 | 480  | 0.4329          | 0.8668   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1