This model is a fine-tuned version of Ateeqq/ai-vs-human-image-detector on the imagefolder dataset. It achieves the following results on the evaluation set:

Accuracy: 0.7561
Loss: 1.1782

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: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 3

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.7523	1.0	58	0.6951	1.1249
0.3123	2.0	116	0.7744	0.7260
0.2716	3.0	174	0.7561	1.1782

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

thrimurthi2025/results

results

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

thrimurthi2025/
results