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 ([email protected]).
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Evaluation results
- Accuracyself-reported0.911