Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

VQA: add option for beam-search validation during fine-tuning #79

Merged
merged 6 commits into from
Apr 24, 2022

Conversation

yangapku
Copy link
Member

VQA: add option for beam-search validation during fine-tuning

@yangapku
Copy link
Member Author

yangapku commented Apr 23, 2022

This PR is related to #69.

As mentioned in the readme (Finetuning & Inference, VQA, 4.inference section), we have prepared 2 types of inference for evaluation after fine-tuning. However, in the validation during fine-tuning, the user can only use all-candidate validation, which may be much slower. Now we have added a new option named val_inference_type in the fine-tuning scripts of VQA (see Line 61 in run_scripts/vqa/train_vqa_base_distributed.sh and run_scripts/vqa/train_vqa_distributed.sh). This option can be set as allcand (by default) or beamsearch, which stand for all-candidate and beam-search evaluation, respectively. Compared to the default all-candidate validation used in previous commits, switching to beam-search validation will be much faster (with around 0.5-0.6 validation score degradation compared with all-candidate validation).

@yangapku yangapku changed the title Feature/vqa VQA: add option for beam-search validation during fine-tuning Apr 23, 2022
@yangapku yangapku merged commit 7c844fe into OFA-Sys:main Apr 24, 2022
Absolute-Value pushed a commit to Absolute-Value/OFA that referenced this pull request Mar 15, 2023
VQA: add option for beam-search validation during fine-tuning
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

None yet

1 participant