---
license: apache-2.0
base_model: gianlab/swin-tiny-patch4-window7-224-finetuned-plantdisease
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: CGIAR-Crop-disease
  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. -->

# CGIAR-Crop-disease

This model is a fine-tuned version of [gianlab/swin-tiny-patch4-window7-224-finetuned-plantdisease](https://huggingface.co/gianlab/swin-tiny-patch4-window7-224-finetuned-plantdisease) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7668
- Accuracy: 0.6726

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.047         | 1.0   | 652   | 0.9302          | 0.5817   |
| 0.899         | 2.0   | 1304  | 0.8669          | 0.6285   |
| 0.8656        | 3.0   | 1956  | 0.8434          | 0.6385   |
| 0.8514        | 4.0   | 2608  | 0.8421          | 0.6277   |
| 0.8395        | 5.0   | 3260  | 0.8275          | 0.6506   |
| 0.832         | 6.0   | 3912  | 0.8444          | 0.6415   |
| 0.8065        | 7.0   | 4564  | 0.8204          | 0.6494   |
| 0.8031        | 8.0   | 5216  | 0.8271          | 0.6438   |
| 0.7954        | 9.0   | 5868  | 0.8025          | 0.6632   |
| 0.7939        | 10.0  | 6520  | 0.7917          | 0.6592   |
| 0.7893        | 11.0  | 7172  | 0.8043          | 0.6515   |
| 0.7731        | 12.0  | 7824  | 0.7878          | 0.6695   |
| 0.7759        | 13.0  | 8476  | 0.7806          | 0.6657   |
| 0.7676        | 14.0  | 9128  | 0.7816          | 0.6653   |
| 0.7605        | 15.0  | 9780  | 0.7882          | 0.6550   |
| 0.7566        | 16.0  | 10432 | 0.7881          | 0.6548   |
| 0.7554        | 17.0  | 11084 | 0.7824          | 0.6619   |
| 0.7384        | 18.0  | 11736 | 0.7668          | 0.6726   |
| 0.7442        | 19.0  | 12388 | 0.7830          | 0.6594   |
| 0.7296        | 20.0  | 13040 | 0.7709          | 0.6667   |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.0.0
- Datasets 2.16.1
- Tokenizers 0.15.0