---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
datasets:
- AI-Lab-Makerere/beans
metrics:
- accuracy
widget:
- src: https://huggingface.co/RaymundoSGlz/vit_model_beans/resolve/main/bean_rust.jpeg
  example_title: Bean rust
- src: https://huggingface.co/RaymundoSGlz/vit_model_beans/resolve/main/healthy.jpeg
  example_title: Healthy
base_model: google/vit-base-patch16-224-in21k
model-index:
- name: vit_model_beans
  results:
  - task:
      type: image-classification
      name: Image Classification
    dataset:
      name: beans
      type: beans
      config: default
      split: validation
      args: default
    metrics:
    - type: accuracy
      value: 0.9924812030075187
      name: Accuracy
---

<!-- 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. -->

# vit_model_beans

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0310
- Accuracy: 0.9925

## 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: 0.0002
- 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: 2

### Training results



### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3