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: 0.3480
Accuracy: 0.8404
Precision: 0.8500
Recall: 0.9666
F1: 0.9045
Roc Auc: 0.8758

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
0.3847	1.0	1344	0.3480	0.8404	0.8500	0.9666	0.9045	0.8758

Framework versions

Transformers 4.39.2
Pytorch 2.3.0
Datasets 2.18.0
Tokenizers 0.15.2

hchcsuim/batch-size16_FFPP-c23_ffmpeg-1FPS-qv31_unaugmentation

batch-size16_FFPP-c23_ffmpeg-1FPS-qv31_unaugmentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hchcsuim/
batch-size16_FFPP-c23_ffmpeg-1FPS-qv31_unaugmentation