|
--- |
|
license: gemma |
|
base_model: google/paligemma-3b-pt-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
model-index: |
|
- name: paligemma_race |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# paligemma_race |
|
|
|
This model is a fine-tuned version of [google/paligemma-3b-pt-224](https://huggingface.co/google/paligemma-3b-pt-224) on the FairFace dataset. |
|
|
|
``` python |
|
|
|
from PIL import Image |
|
import torch |
|
from transformers import PaliGemmaProcessor, PaliGemmaForConditionalGeneration, BitsAndBytesConfig, TrainingArguments, Trainer |
|
|
|
|
|
model = PaliGemmaForConditionalGeneration.from_pretrained('NYUAD-ComNets/paligemma_race',torch_dtype=torch.bfloat16) |
|
|
|
input_text = "what is race 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 |
|
|
|
More information needed |
|
|
|
## 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: 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 |
|
|
|
### Training results |
|
|
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.4 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
