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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
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