---
base_model: google/paligemma-3b-pt-224
library_name: peft
license: gemma
tags:
- generated_from_trainer
model-index:
- name: paligemma_VQAv2_ko
  results: []
pipeline_tag: visual-question-answering
datasets:
- HuggingFaceM4/VQAv2
language:
- ko
- en
---

<!-- 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_VQAv2_ko

This model is a fine-tuned version of [google/paligemma-3b-pt-224](https://huggingface.co/google/paligemma-3b-pt-224) on an korean VQAv2 dataset.(HuggingFaceM4/VQAv2)

ds = load_dataset('HuggingFaceM4/VQAv2', split="train[:100%]",cache_dir=root_path+'dataset/')

## Model description

This model was finetuned using VQAv2 datasets translated into KOREAN. 

## Intended uses & limitations

Nothing

## Training and evaluation data

Nothing

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 2

### Framework versions

- PEFT 0.8.2
- Transformers 4.45.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1