---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
- recall
- f1
- precision
model-index:
- name: vit-base-modified-augmented-ph2-patch-16
  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-modified-augmented-ph2-patch-16

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 ahishamm/Modified_Augmented_PH2_db_sharpened dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0010
- Accuracy: 1.0
- Recall: 1.0
- F1: 1.0
- Precision: 1.0

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.1238        | 0.29  | 50   | 0.1973          | 0.9332   | 0.9332 | 0.9332 | 0.9332    |
| 0.1857        | 0.59  | 100  | 0.1084          | 0.9623   | 0.9623 | 0.9623 | 0.9623    |
| 0.2506        | 0.88  | 150  | 0.0773          | 0.9692   | 0.9692 | 0.9692 | 0.9692    |
| 0.0247        | 1.18  | 200  | 0.1158          | 0.9606   | 0.9606 | 0.9606 | 0.9606    |
| 0.0089        | 1.47  | 250  | 0.0162          | 0.9914   | 0.9914 | 0.9914 | 0.9914    |
| 0.0226        | 1.76  | 300  | 0.0020          | 1.0      | 1.0    | 1.0    | 1.0       |
| 0.0261        | 2.06  | 350  | 0.0017          | 1.0      | 1.0    | 1.0    | 1.0       |
| 0.0014        | 2.35  | 400  | 0.0014          | 1.0      | 1.0    | 1.0    | 1.0       |
| 0.0012        | 2.65  | 450  | 0.0013          | 1.0      | 1.0    | 1.0    | 1.0       |
| 0.0013        | 2.94  | 500  | 0.0012          | 1.0      | 1.0    | 1.0    | 1.0       |
| 0.0011        | 3.24  | 550  | 0.0011          | 1.0      | 1.0    | 1.0    | 1.0       |
| 0.001         | 3.53  | 600  | 0.0011          | 1.0      | 1.0    | 1.0    | 1.0       |
| 0.0011        | 3.82  | 650  | 0.0010          | 1.0      | 1.0    | 1.0    | 1.0       |


### Framework versions

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