CoolFace
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NTQAI/pedestrian_gender_recognition

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
19likes17kdownloads
Model Card

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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 .

python
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
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 1337
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 5.0

Training results

Training LossEpochStepValidation LossAccuracy
0.51931.020000.33460.8533
0.3372.040000.28920.8778
0.37713.060000.24930.8969
0.38194.080000.22750.9100
0.35815.0100000.21700.9107

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).