---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
widget:
- src: https://huggingface.co/wgcv/platzi-vit-model-wgcv/resolve/main/healthy.jpeg
  example_title: Healthy
- src: https://huggingface.co/wgcv/platzi-vit-model-wgcv/resolve/main/bean_rust.jpeg
  example_title: Bean Rust
model-index:
- name: platzi-vit-model-wgcv
  results: []
datasets:
- AI-Lab-Makerere/beans
pipeline_tag: image-classification
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# platzi-vit-model-wgcv

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

## Testing
Bean Rust
![Bean Rust](https://huggingface.co/wgcv/platzi-vit-model-wgcv/resolve/main/bean_rust.jpeg)

Healthy
![Healthy](https://huggingface.co/wgcv/platzi-vit-model-wgcv/resolve/main/healthy.jpeg)


## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 4136, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results



### Framework versions

- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1