vit_model

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the beans dataset. It achieves the following results on the evaluation set:

• Loss: 0.0821
• Accuracy: 0.9774

Model description

This model distinguishes between healthy and diseased bean leaves. It can also categorize between two diseases: bean rust and angular leaf spot. Just upload a photo and the model will tell you the probability of these three categories.

Healty

Bean Rust

Angular Leaf Spot

Intended uses & limitations

Just classifies bean leaves

Training and evaluation data

The model was trained with the dataset beans: https://huggingface.co/datasets/beans

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0002
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1435	3.85	500	0.0821	0.9774

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu118
• Datasets 2.14.2
• Tokenizers 0.13.3