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---
license: apache-2.0
tags:
- image-classification
- beans-classification
- generated_from_trainer
metrics:
- accuracy
widget:
- src: >-
https://huggingface.co/jolual2747/vit-model-jose-alcocer/resolve/main/healthy.jpeg
example_title: Healthy
- src: >-
https://huggingface.co/jolual2747/vit-model-jose-alcocer/resolve/main/bean_rust.jpeg
example_title: Bean Rust
model-index:
- name: vit-model-jose-alcocer
results: []
---
<!-- 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-jose-alcocer
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: 0.0217
- Accuracy: 0.9925
## Model description
This model classifies beans between healthy, rust and angular_leaf_spot
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1179 | 3.85 | 500 | 0.0217 | 0.9925 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3
|