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: 0.0478
Accuracy: 0.9826
Precision: 0.9819
Recall: 0.9961
F1: 0.9889
Roc Auc: 0.9989

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
0.0428	0.9996	1377	0.0478	0.9826	0.9819	0.9961	0.9889	0.9989

Framework versions

Transformers 4.41.2
Pytorch 2.3.1
Datasets 2.20.0
Tokenizers 0.19.1

hchcsuim/batch-size16_FFPP-raw_opencv-1FPS_faces-expand0-aligned_unaugmentation_seeds-42_143_4090

batch-size16_FFPP-raw_opencv-1FPS_faces-expand0-aligned_unaugmentation_seeds-42_143_4090

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hchcsuim/
batch-size16_FFPP-raw_opencv-1FPS_faces-expand0-aligned_unaugmentation_seeds-42_143_4090