readme: ---
  license: apache-2.0
  tags:
  - image-classification
  - vision
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: outputs
    results:
    - task:
        name: Image Classification
        type: image-classification
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9107332624867163
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # outputs
  
  This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the [PETA dataset](http://mmlab.ie.cuhk.edu.hk/projects/PETA_files/Pedestrian%20Attribute%20Recognition%20At%20Far%20Distance.pdf) 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
  - 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 (nha.nguyen@ntq-solution.com.vn).