metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- beans
metrics:
- accuracy
model-index:
- name: vit-base-beans-demo-v5
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: beans
type: beans
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 1
Fine-Tuned ViT for Beans Leaf Disease Classification
Model Information
- Model Name: VIT_Beans_Leaf_Disease_Classifier
- Base Model: Google/ViT-base-patch16-224-in21k
- Task: Image Classification (Beans Leaf Disease Classification)
- Dataset: Beans leaf dataset with images of diseased and healthy leaves.
Problem Statement
The goal of this model is to classify leaf images into three categories:
{
"angular_leaf_spot": 0,
"bean_rust": 1,
"healthy": 2,
}
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.1495 | 1.54 | 100 | 0.0910 | 0.9774 |
0.0121 | 3.08 | 200 | 0.0155 | 1.0 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3