outputs

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the PETA dataset dataset. It achieves the following results on the evaluation set:

Loss: 0.2170
Accuracy: 0.9107

Model description

More information needed

How to use

You can use this model with Transformers pipeline .

from transformers import pipeline
gender_classifier = pipeline(model="NTQAI/pedestrian_gender_recognition")
image_path = "abc.jpg"

results = gender_classifier(image_path)
print(results)

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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 1337
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5193	1.0	2000	0.3346	0.8533
0.337	2.0	4000	0.2892	0.8778
0.3771	3.0	6000	0.2493	0.8969
0.3819	4.0	8000	0.2275	0.9100
0.3581	5.0	10000	0.2170	0.9107

Framework versions

Transformers 4.24.0.dev0
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.1

Contact information

For personal communication related to this project, please contact Nha Nguyen Van (nha282@gmail.com).

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