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: 0.0674
Accuracy: 0.9754
Precision: 0.9893
Recall: 0.9814
F1: 0.9853
Roc Auc: 0.9951

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
0.0756	1.0000	18848	0.0674	0.9754	0.9893	0.9814	0.9853	0.9951

Framework versions

Transformers 4.41.2
Pytorch 2.3.1
Datasets 2.20.0
Tokenizers 0.19.1

hchcsuim/batch-size16_DFDC_opencv-1FPS_unaugmentation

batch-size16_DFDC_opencv-1FPS_unaugmentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hchcsuim/
batch-size16_DFDC_opencv-1FPS_unaugmentation