finetuned-ai-real-cifake
This model is a fine-tuned version of ongtrandong2/ai_vs_real_image_detection on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0622
- Accuracy: 0.9756
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.4286 | 0.3617 | 200 | 0.4256 | 0.8549 |
0.3499 | 0.7233 | 400 | 0.1693 | 0.9353 |
0.2664 | 1.0850 | 600 | 0.3467 | 0.8690 |
0.2303 | 1.4467 | 800 | 0.4582 | 0.8398 |
0.1553 | 1.8083 | 1000 | 0.2135 | 0.9186 |
0.1751 | 2.1700 | 1200 | 0.0793 | 0.9715 |
0.1383 | 2.5316 | 1400 | 0.0638 | 0.9753 |
0.1375 | 2.8933 | 1600 | 0.0622 | 0.9756 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
ongtrandong2/ai_vs_real_image_detection