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

Add Janus-1.3B #541

Merged
merged 3 commits into from
Oct 23, 2024
Merged

Add Janus-1.3B #541

merged 3 commits into from
Oct 23, 2024

Conversation

hills-code
Copy link
Contributor

We add Janus-1.3B model to reproduce the results in paper.

MME MMB
(w/o circular)
SEED MMMU_DEV_VAL MM-Vet POPE
VLMEvalkit (Reproduce) 1342.4 69.8 63.8 31.2 36.8 85.5 (overall)
87.1 (random)
Paper 1338.0 69.4 63.7 30.5 34.3 87 (random)

You can run the evaluation with the following code:

torchrun --nproc-per-node=8 run.py --data POPE MMMU_DEV_VAL MMBench_DEV_EN MME SEEDBench_IMG MMVet --model janus_1.3b --verbose

Note:

  • We evaluate MMBench without circular mode. You should set circular=False in the file vlmeval/dataset/image_mcq.py
  • We use the official evaluation of MM-Vet with GPT-4 evaluator.

wuchengyue added 2 commits October 23, 2024 11:25

Verified

This commit was created on github.com and signed with GitHub’s verified signature. The key has expired.
@kennymckormick kennymckormick merged commit f4646f7 into open-compass:main Oct 23, 2024
1 check passed
kennymckormick added a commit to white2018/VLMEvalKit that referenced this pull request Nov 1, 2024
* add janus eval

* update

* [Fix] Fix Lint

---------

Co-authored-by: wuchengyue <hillwu@deepseek.com>
Co-authored-by: kennymckormick <dhd.efz@gmail.com>
kushal-tri pushed a commit to kushal-tri/VLMEvalKit that referenced this pull request Nov 22, 2024
* add janus eval

* update

* [Fix] Fix Lint

---------

Co-authored-by: wuchengyue <hillwu@deepseek.com>
Co-authored-by: kennymckormick <dhd.efz@gmail.com>
@wusize
Copy link

wusize commented Feb 11, 2025

We add Janus-1.3B model to reproduce the results in paper.

MME MMB
(w/o circular) SEED MMMU_DEV_VAL MM-Vet POPE
VLMEvalkit (Reproduce) 1342.4 69.8 63.8 31.2 36.8 85.5 (overall)
87.1 (random)
Paper 1338.0 69.4 63.7 30.5 34.3 87 (random)
You can run the evaluation with the following code:

torchrun --nproc-per-node=8 run.py --data POPE MMMU_DEV_VAL MMBench_DEV_EN MME SEEDBench_IMG MMVet --model janus_1.3b --verbose

Note:

  • We evaluate MMBench without circular mode. You should set circular=False in the file vlmeval/dataset/image_mcq.py
  • We use the official evaluation of MM-Vet with GPT-4 evaluator.

Hi! There are two splits in MMMU_DEV_VAL, i.e., dev and validation. May I know which one the numbers in the table correspond to?

@charlesCXK
Copy link

We add Janus-1.3B model to reproduce the results in paper.
MME MMB
(w/o circular) SEED MMMU_DEV_VAL MM-Vet POPE
VLMEvalkit (Reproduce) 1342.4 69.8 63.8 31.2 36.8 85.5 (overall)
87.1 (random)
Paper 1338.0 69.4 63.7 30.5 34.3 87 (random)
You can run the evaluation with the following code:

torchrun --nproc-per-node=8 run.py --data POPE MMMU_DEV_VAL MMBench_DEV_EN MME SEEDBench_IMG MMVet --model janus_1.3b --verbose

Note:

  • We evaluate MMBench without circular mode. You should set circular=False in the file vlmeval/dataset/image_mcq.py
  • We use the official evaluation of MM-Vet with GPT-4 evaluator.

Hi! There are two splits in MMMU_DEV_VAL, i.e., dev and validation. May I know which one the numbers in the table correspond to?

Hi, it was VAL set~

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.

4 participants