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

abi23rdx/finetuned-ai-real-cifake

finetuned-ai-real-cifake

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

abi23rdx/
finetuned-ai-real-cifake