---
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: 0.3758
- Accuracy: 0.8762

## 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: 2000
- eval_batch_size: 2000
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8000
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.8   | 2    | 0.4078          | 0.8724   |
| No log        | 2.0   | 5    | 0.3771          | 0.8776   |
| No log        | 2.8   | 7    | 0.3776          | 0.8762   |
| 0.3197        | 4.0   | 10   | 0.3773          | 0.8762   |
| 0.3197        | 4.8   | 12   | 0.3768          | 0.8762   |
| 0.3197        | 6.0   | 15   | 0.3762          | 0.8762   |
| 0.3197        | 6.8   | 17   | 0.3760          | 0.8762   |
| 0.2995        | 8.0   | 20   | 0.3759          | 0.8762   |
| 0.2995        | 8.8   | 22   | 0.3759          | 0.8762   |
| 0.2995        | 10.0  | 25   | 0.3758          | 0.8762   |
| 0.2995        | 10.8  | 27   | 0.3758          | 0.8762   |
| 0.2996        | 12.0  | 30   | 0.3758          | 0.8762   |
| 0.2996        | 12.8  | 32   | 0.3758          | 0.8762   |
| 0.2996        | 14.0  | 35   | 0.3758          | 0.8762   |
| 0.2996        | 14.8  | 37   | 0.3758          | 0.8762   |
| 0.3024        | 16.0  | 40   | 0.3758          | 0.8762   |


### Framework versions

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