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# ResNet_AI_image_detector

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1330
- Accuracy: 0.9507

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.441         | 1.0   | 1093  | 0.3588          | 0.8458   |
| 0.2977        | 2.0   | 2187  | 0.2798          | 0.8806   |
| 0.3006        | 3.0   | 3281  | 0.1957          | 0.9222   |
| 0.2916        | 4.0   | 4375  | 0.1800          | 0.9323   |
| 0.2835        | 5.0   | 5468  | 0.1784          | 0.9307   |
| 0.2623        | 6.0   | 6562  | 0.1505          | 0.9425   |
| 0.2791        | 7.0   | 7656  | 0.1408          | 0.9460   |
| 0.2686        | 8.0   | 8750  | 0.1490          | 0.9433   |
| 0.2219        | 9.0   | 9843  | 0.1479          | 0.9445   |
| 0.2552        | 9.99  | 10930 | 0.1330          | 0.9507   |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.13.3

fake real