Edit model card

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).

Downloads last month
5,349
Safetensors
Model size
86.2M params
Tensor type
I64
·
F32
·

Spaces using NTQAI/pedestrian_gender_recognition 2