---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
model-index:
- name: ryan_model314_3
  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. -->

# ryan_model314_3

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: 0.2750
- Na Accuracy: 0.931
- Ordinal Accuracy: 0.6271
- Ordinal Mae: 0.5319

## 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: 16
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Na Accuracy | Ordinal Accuracy | Ordinal Mae |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:----------------:|:-----------:|
| 0.4423        | 0.08  | 50   | 0.3386          | 0.904       | 0.4629           | 0.6578      |
| 0.3088        | 0.16  | 100  | 0.3269          | 0.928       | 0.5371           | 0.5969      |
| 0.316         | 0.24  | 150  | 0.3396          | 0.902       | 0.5143           | 0.6323      |
| 0.2821        | 0.32  | 200  | 0.3234          | 0.927       | 0.5131           | 0.6293      |
| 0.2731        | 0.4   | 250  | 0.3314          | 0.925       | 0.5086           | 0.5856      |
| 0.2975        | 0.48  | 300  | 0.3037          | 0.927       | 0.5964           | 0.5690      |
| 0.2609        | 0.56  | 350  | 0.3209          | 0.928       | 0.5450           | 0.5765      |
| 0.287         | 0.64  | 400  | 0.2908          | 0.931       | 0.5827           | 0.5458      |
| 0.2905        | 0.72  | 450  | 0.3007          | 0.919       | 0.5986           | 0.5484      |
| 0.2574        | 0.8   | 500  | 0.2834          | 0.929       | 0.6032           | 0.5363      |
| 0.2855        | 0.88  | 550  | 0.2750          | 0.931       | 0.6271           | 0.5319      |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2