NYUAD-ComNets/FaceScanPaliGemma_Gender

paligemma_gender

from PIL import Image
import torch
from transformers import PaliGemmaProcessor, PaliGemmaForConditionalGeneration, BitsAndBytesConfig, TrainingArguments, Trainer


model = PaliGemmaForConditionalGeneration.from_pretrained('NYUAD-ComNets/FaceScanPaliGemma_Gender',torch_dtype=torch.bfloat16)

input_text = "what is gender of person in the image?"

processor = PaliGemmaProcessor.from_pretrained("google/paligemma-3b-pt-224")

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

model.to(device)


input_image = Image.open('image_path')
inputs = processor(text=input_text, images=input_image, padding="longest", do_convert_rgb=True, return_tensors="pt").to(device)
inputs = inputs.to(dtype=model.dtype)
      
with torch.no_grad():
          output = model.generate(**inputs, max_length=500)
result=processor.decode(output[0], skip_special_tokens=True)[len(input_text):].strip()

Model description

This model is a fine-tuned version of google/paligemma-3b-pt-224 on the FairFace dataset. The model aims to classify the gender of face image or image with one person into Male and Female

Intended uses & limitations

This model is used for research purposes

Training and evaluation data

FairFace dataset was used for training and validating the model

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 2
• num_epochs: 5

Results

The model has an accuracy of %

Framework versions

• Transformers 4.42.4
• Pytorch 2.1.2+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1

BibTeX entry and citation info

@misc{ComNets,
      url={https://huggingface.co/NYUAD-ComNets/FaceScanPaliGemma_Gender](https://huggingface.co/NYUAD-ComNets/FaceScanPaliGemma_Gender)},
      title={FaceScanPaliGemma_Gender},
      author={Nouar AlDahoul, Yasir Zaki}
}