---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: VIT_AI_image_detector
  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_AI_image_detector

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0278
- Accuracy: 0.9931

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1943        | 1.0   | 1406  | 0.0682          | 0.9757   |
| 0.1288        | 2.0   | 2812  | 0.0423          | 0.9852   |
| 0.0952        | 3.0   | 4218  | 0.0393          | 0.9866   |
| 0.0743        | 4.0   | 5625  | 0.0410          | 0.9866   |
| 0.0587        | 5.0   | 7031  | 0.0332          | 0.9889   |
| 0.0493        | 6.0   | 8437  | 0.0253          | 0.9919   |
| 0.06          | 7.0   | 9843  | 0.0279          | 0.9922   |
| 0.0738        | 8.0   | 11250 | 0.0326          | 0.9907   |
| 0.065         | 9.0   | 12656 | 0.0278          | 0.9931   |
| 0.045         | 10.0  | 14060 | 0.0279          | 0.9928   |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.13.3