---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
model-index:
- name: ryan_model3272024
  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_model3272024

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: 0.2552
- Na Accuracy: 0.95
- Ordinal Accuracy: 0.6267
- Ordinal Mae: 1.1586

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Na Accuracy | Ordinal Accuracy | Ordinal Mae |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:----------------:|:-----------:|
| 0.3853        | 0.32  | 100  | 0.3272          | 0.924       | 0.52             | 1.2106      |
| 0.3396        | 0.64  | 200  | 0.2741          | 0.94        | 0.5644           | 1.1640      |
| 0.2075        | 0.96  | 300  | 0.2772          | 0.946       | 0.5933           | 1.1942      |
| 0.196         | 1.28  | 400  | 0.2738          | 0.95        | 0.6133           | 1.1984      |
| 0.2228        | 1.6   | 500  | 0.2685          | 0.956       | 0.62             | 1.1989      |
| 0.1816        | 1.92  | 600  | 0.2552          | 0.95        | 0.6267           | 1.1586      |
| 0.0682        | 2.24  | 700  | 0.2721          | 0.952       | 0.6578           | 1.1558      |
| 0.0795        | 2.56  | 800  | 0.2754          | 0.948       | 0.6333           | 1.1599      |
| 0.1367        | 2.88  | 900  | 0.2953          | 0.946       | 0.64             | 1.1667      |
| 0.0387        | 3.19  | 1000 | 0.2923          | 0.944       | 0.6378           | 1.2025      |
| 0.0293        | 3.51  | 1100 | 0.2885          | 0.948       | 0.6644           | 1.1666      |
| 0.0286        | 3.83  | 1200 | 0.2868          | 0.95        | 0.6711           | 1.1626      |


### Framework versions

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