---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
widget:
- src: >-
    https://huggingface.co/SSM10/vit_models/blob/main/healthy_66daaf31-4e54-476e-85e5-42d062377763.jpeg
  example_title: Healthy
- src: >-
    https://huggingface.co/SSM10/vit_models/blob/main/bean_rust_f1500068-80a0-41b1-b57c-2a601fb95e66.jpeg
  example_title: Bean Rust
model-index:
- name: vit_models
  results: []
datasets:
- AI-Lab-Makerere/beans
pipeline_tag: image-classification
---

<!-- 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_models

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: 0.0299
- Accuracy: 0.9774

## 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: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.1297        | 3.8462 | 500  | 0.0299          | 0.9774   |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1