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: 0.2388
Accuracy: 0.9033
Precision: 0.8971
Recall: 0.9901
F1: 0.9413
Roc Auc: 0.9623

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
0.2365	0.9998	1381	0.2388	0.9033	0.8971	0.9901	0.9413	0.9623

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_unaugmentation

batch-size16_FFPP-raw_opencv-1FPS_unaugmentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hchcsuim/
batch-size16_FFPP-raw_opencv-1FPS_unaugmentation