realFake-food
This model is a fine-tuned version of dima806/deepfake_vs_real_image_detection on the ai_real_images dataset. It achieves the following results on the evaluation set:
- Loss: 0.4344
- Accuracy: 0.8014
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 |
---|---|---|---|---|
0.3941 | 1.9231 | 100 | 0.4344 | 0.8014 |
0.2366 | 3.8462 | 200 | 0.4853 | 0.8630 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for itsLeen/realFake-food
Base model
google/vit-base-patch16-224-in21k
Finetuned
dima806/deepfake_vs_real_image_detection