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: 0.0442
Accuracy: 0.9837
Precision: 0.9831
Recall: 0.9964
F1: 0.9897
Roc Auc: 0.9991

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	Precision	Recall	F1	Roc Auc
0.0483	1.0	1377	0.0442	0.9837	0.9831	0.9964	0.9897	0.9991

Framework versions

Transformers 4.39.2
Pytorch 2.3.0
Datasets 2.18.0
Tokenizers 0.15.2

hchcsuim/batch-size-16_FFPP-Raw_1FPS_faces-expand-0-aligned_unaugmentation

batch-size-16_FFPP-Raw_1FPS_faces-expand-0-aligned_unaugmentation

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_unaugmentation