Paligemma VQAv2 Ko

--- 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

Source context: 3 downloads · 0 likes · Pipeline visual-question-answering · Library peft · Repo namyi/paligemma_VQAv2_ko