---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
- recall
- f1
- precision
model-index:
- name: vit-base-augmented-ph2-patch-32
  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-base-augmented-ph2-patch-32

This model is a fine-tuned version of [google/vit-base-patch32-224-in21k](https://huggingface.co/google/vit-base-patch32-224-in21k) on the ahishamm/Augmented_PH2_db_sharpened dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3904
- Accuracy: 0.8684
- Recall: 0.8684
- F1: 0.8684
- Precision: 0.8684

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1     | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.1087        | 0.36  | 50   | 0.3904          | 0.8684   | 0.8684 | 0.8684 | 0.8684    |
| 0.066         | 0.72  | 100  | 0.7073          | 0.8274   | 0.8274 | 0.8274 | 0.8274    |
| 0.0092        | 1.09  | 150  | 0.6635          | 0.8154   | 0.8154 | 0.8154 | 0.8154    |
| 0.0716        | 1.45  | 200  | 0.7824          | 0.8342   | 0.8342 | 0.8342 | 0.8342    |
| 0.0056        | 1.81  | 250  | 0.5071          | 0.8957   | 0.8957 | 0.8957 | 0.8957    |
| 0.0023        | 2.17  | 300  | 0.5978          | 0.8855   | 0.8855 | 0.8855 | 0.8855    |
| 0.0019        | 2.54  | 350  | 0.6143          | 0.8855   | 0.8855 | 0.8855 | 0.8855    |
| 0.0016        | 2.9   | 400  | 0.6227          | 0.8889   | 0.8889 | 0.8889 | 0.8889    |
| 0.0015        | 3.26  | 450  | 0.6294          | 0.8889   | 0.8889 | 0.8889 | 0.8889    |
| 0.0014        | 3.62  | 500  | 0.6338          | 0.8889   | 0.8889 | 0.8889 | 0.8889    |
| 0.0014        | 3.99  | 550  | 0.6351          | 0.8889   | 0.8889 | 0.8889 | 0.8889    |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3