blip2-finetuned-vqa

duythanh1022/blip2-finetuned-vqa

blip2-finetuned-vqa is a machine learning model from duythanh1022. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft.

should probably proofread and complete it, then remove this comment. --

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Hugging Face

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At a glance

Library: peft
Access: Public
Created: May 27, 2025
Updated: May 27, 2025
SHA: 0ba8bd33

Base models

ybelkada/blip2-opt-2.7b-fp16-sharded

Model card

From the Hugging Face model README

blip2-finetuned-vqa

This model is a fine-tuned version of ybelkada/blip2-opt-2.7b-fp16-sharded on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6786

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: 0.0002
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.7789	0.2051	1000	0.7354
0.6987	0.4102	2000	0.7221
0.6893	0.6153	3000	0.6991
0.6997	0.8204	4000	0.6786

Framework versions

PEFT 0.15.2.dev0
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1

Library: peft
Created: May 27, 2025
Updated: May 27, 2025