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

This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the ahishamm/Modified_Augmented_PH2_db_sharpened dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0827
- Accuracy: 0.9709
- Recall: 0.9709
- F1: 0.9709
- Precision: 0.9709

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.3402        | 0.29  | 50   | 0.6269          | 0.7945   | 0.7945 | 0.7945 | 0.7945    |
| 0.1387        | 0.59  | 100  | 0.2957          | 0.8921   | 0.8921 | 0.8921 | 0.8921    |
| 0.2921        | 0.88  | 150  | 0.3157          | 0.8836   | 0.8836 | 0.8836 | 0.8836    |
| 0.1268        | 1.18  | 200  | 0.4557          | 0.8527   | 0.8527 | 0.8527 | 0.8527    |
| 0.2071        | 1.47  | 250  | 0.2690          | 0.8818   | 0.8818 | 0.8818 | 0.8818    |
| 0.1238        | 1.76  | 300  | 0.2999          | 0.9178   | 0.9178 | 0.9178 | 0.9178    |
| 0.1327        | 2.06  | 350  | 0.6026          | 0.7877   | 0.7877 | 0.7877 | 0.7877    |
| 0.1453        | 2.35  | 400  | 0.2887          | 0.8990   | 0.8990 | 0.8990 | 0.8990    |
| 0.0686        | 2.65  | 450  | 0.2049          | 0.9503   | 0.9503 | 0.9503 | 0.9503    |
| 0.0414        | 2.94  | 500  | 0.3040          | 0.9195   | 0.9195 | 0.9195 | 0.9195    |
| 0.0851        | 3.24  | 550  | 0.2244          | 0.9298   | 0.9298 | 0.9298 | 0.9298    |
| 0.0054        | 3.53  | 600  | 0.1356          | 0.9555   | 0.9555 | 0.9555 | 0.9555    |
| 0.0029        | 3.82  | 650  | 0.0827          | 0.9709   | 0.9709 | 0.9709 | 0.9709    |


### Framework versions

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