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: 0.0500
Accuracy: 0.9815
Recall: 0.9432
Precision: 0.9707
F1: 0.9567
Roc Auc: 0.9981

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: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall	Precision	F1	Roc Auc
0.0661	1.0	1377	0.0500	0.9815	0.9432	0.9707	0.9567	0.9981

Framework versions

Transformers 4.39.2
Pytorch 2.2.2
Datasets 2.18.0
Tokenizers 0.15.2

hchcsuim/batch-size-16_FFPP-Raw_1FPS_faces-expand-0-aligned_0Real-1Fake

batch-size-16_FFPP-Raw_1FPS_faces-expand-0-aligned_0Real-1Fake

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hchcsuim/
batch-size-16_FFPP-Raw_1FPS_faces-expand-0-aligned_0Real-1Fake