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---
license: apache-2.0
base_model: dima806/deepfake_vs_real_image_detection
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: realFake-img
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: ai_real_images
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8518181818181818
---
<!-- 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. -->
# realFake-img
This model is a fine-tuned version of [dima806/deepfake_vs_real_image_detection](https://huggingface.co/dima806/deepfake_vs_real_image_detection) on the ai_real_images dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3329
- Accuracy: 0.8518
## 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4892 | 0.2564 | 100 | 0.5756 | 0.7227 |
| 0.683 | 0.5128 | 200 | 0.6742 | 0.6373 |
| 0.3737 | 0.7692 | 300 | 0.5462 | 0.7555 |
| 0.3554 | 1.0256 | 400 | 0.4354 | 0.8009 |
| 0.2368 | 1.2821 | 500 | 0.4046 | 0.8309 |
| 0.3696 | 1.5385 | 600 | 0.5547 | 0.7809 |
| 0.2824 | 1.7949 | 700 | 0.3329 | 0.8518 |
| 0.2366 | 2.0513 | 800 | 0.4582 | 0.8255 |
| 0.2212 | 2.3077 | 900 | 0.4885 | 0.8255 |
| 0.2031 | 2.5641 | 1000 | 0.4282 | 0.8564 |
| 0.1717 | 2.8205 | 1100 | 0.4373 | 0.85 |
| 0.1303 | 3.0769 | 1200 | 0.3659 | 0.8718 |
| 0.0889 | 3.3333 | 1300 | 0.3663 | 0.8736 |
| 0.1157 | 3.5897 | 1400 | 0.4588 | 0.8436 |
| 0.1215 | 3.8462 | 1500 | 0.4350 | 0.8655 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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