This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0514
Accuracy: 0.9808
Recall: 0.9929
Precision: 0.9826
F1: 0.9878
Roc Auc: 0.9980

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: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall	Precision	F1	Roc Auc
0.1725	1.0	1348	0.1299	0.9464	0.9628	0.9685	0.9656	0.9850
0.1387	2.0	2696	0.0704	0.9734	0.9854	0.9807	0.9831	0.9959
0.0796	3.0	4044	0.0514	0.9808	0.9929	0.9826	0.9878	0.9980

Framework versions

Transformers 4.39.2
Pytorch 2.2.2
Datasets 2.18.0
Tokenizers 0.15.2

hchcsuim/FFPP-Raw_1FPS_faces-expand-40-aligned_0Real-1Fake

FFPP-Raw_1FPS_faces-expand-40-aligned_0Real-1Fake

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hchcsuim/
FFPP-Raw_1FPS_faces-expand-40-aligned_0Real-1Fake