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--- |
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library_name: transformers |
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tags: [] |
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--- |
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# HumanF-MarkrAI/Gukbap-Gemma2-9B-VL🍚 |
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## Model Details🍚 |
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### Model Description |
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- **Developed by:** HumanF-MarkrAI |
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- **Model type:** Korean-VL-Gemma2-9B |
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- **Language(s):** Korean + English |
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- **Context Length:** 2048 |
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- **License:** cc-by-nc-4.0 |
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- **Finetuned from model:** [AIDC-AI/Ovis1.6-Gemma2-9B](https://huggingface.co/AIDC-AI/Ovis1.6-Gemma2-9B). |
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### Model Sources |
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When training, we used `H100 80GB GPU`x4. |
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### Implications🍚 |
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If you want to know our model's details, please see [🔥Gukbap-LMM Blog🔥](coming_soon). |
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And also, we provided the Korean-LMM training code based Ovis!! [🔥Github🔥](coming_soon). Please star⭐⭐!! |
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### Training Method (SFT)🧐 |
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The following papers contain the foundational methodologies for the dataset and training methods we are currently proceeding. |
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- [LIMA](https://arxiv.org/abs/2305.11206). |
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- [Ovis](https://arxiv.org/abs/2405.20797). |
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### SFT Text-Datasets (Private) |
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When we made the `Open-Source based dataset`, we use `microsoft/WizardLM-2-8x22B` through [DeepInfra](https://deepinfra.com/). |
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Our datasets are made by `Evolving system`, which is propsed by [WizardLM](https://wizardlm.github.io/WizardLM2/). |
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In training, we used 1849 training dataset, and 200 validation dataset. |
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- **Wizard-Korea-Datasets:** [MarkrAI/Markr_WizardLM_train_ver4](https://huggingface.co/datasets/MarkrAI/Markr_WizardLM_train_ver4). |
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> Learning rate: 1e-5; Epoch: 2 |
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## Benchmakrs🤗 |
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### Global MM Benchmark Score (Zero-shot) |
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We internally evaluated [VLMEvalKit](https://github.com/open-compass/VLMEvalKit?tab=readme-ov-file). |
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We utilized **chatgpt-0125**, **gpt-4o-mini** and **gpt-4-turbo** in `MMBench`, `MathVista` and `MMVet`, respectively. |
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| Model | MMStar | MathVista | HallusionBench | AI2D | OCRBench | MMVet | MMBench_V11 | AVG | |
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|:---------:|:-----:|:------:|:-----:|:-----:|:----:|:-----:|:-----:|:-----:| |
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| Step-1o (closed model) | 69.3 | **74.7** | **89.1** | 55.8 | **92.6** | **82.8** | 87.3 | **78.8** | |
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| InternVL2.5-78B-MPO (Open) | **72.1** | 76.6 | 58.1 | **89.2** | 90.9 | 73.5 | **87.8** | 78.3 | |
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| InternVL2.5-38B-MPO (Open) | 70.1 | 73.6 | 59.7 | 87.9 | 89.4 | 72.6 | 85.4 | 77.0 | |
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| Ovis1.6-Gemma2-27B (Open) | 63.5 | 70.1 | 54.1 | 86.6 | 85.6 | 68.0 | 82.2 | 72.9 | |
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| Gemini-2.0-Flash | 69.4 | 70.4 | 58.0 | 83.1 | 82.5 | 73.6 | 71.0 | 72.6 | |
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| GPT-4o-20241120 | 65.1 | 59.9 | 56.2 | 84.9 | 80.6 | 74.5 | 84.3 | 72.2 | |
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| **Ovis1.6-Gemma2-9B (Open)** | 62.00 | 67.10 | 84.42 | 51.96 | 82.60 | 64.68 | 82.20 | 70.71 | |
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|:---------:|:-----:|:------:|:-----:|:-----:|:----:|:-----:|:-----:|:-----:| |
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| **Gukbap-Gemma2-9B-VL🍚** | 62.13 | 66.00 | 84.49 | 53.01 | 82.80 | 63.90 | 82.20 | **70.65** | |
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|:---------:|:-----:|:------:|:-----:|:-----:|:----:|:-----:|:-----:|:-----:| |
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| LLaVA-OneVision-72B | 65.8 | 68.4 | 47.9 | 86.2 | 74.1| 60.6 | 84.5 | 69.6 | |
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| VARCO-VISION-14B (NCSoft) | 64.1 | 67.6 | 46.8 | 83.9 | 81.5 | 53.0 | 81.2 | 68.3 | |
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| GPT-4o-mini-20240718 | 54.8 | 52.4 | 46.1 | 77.8 | 78.5 | 66.9 | 76.0 | 64.6 | |
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> HallusionBench score: (aAcc + fAcc + qAcc) / 3 |
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### Korean MM Benchmark Score (Zero-shot) |
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We internally evaluated [our code](coming_soon). |
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We utilized **gpt-4o-2024-08-06** in `K-LLAVA-W` evaluation. |
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| Model | K-MMBench | K-MMStar | K-DTCBench | K-LLAVA-W | AVG | |
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|:---------:|:-----:|:------:|:-----:|:-----:|:----:| |
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| GPT-4o-20241120 | NaN | NaN | NaN | **85.50** | NaN | |
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|:---------:|:-----:|:------:|:-----:|:-----:|:----:| |
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| **Gukbap-Gemma2-9B-VL🍚** | 80.16 | 54.20 | 52.92 | **63.83** | 62.78 | |
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| **Ovis1.6-Gemma2-9B** | 52.46 | 50.40 | 47.08 | 55.67 | 51.40 | |
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| VARCO-VISION-14B | **87.16** | **58.13** | **85.42** | 51.17 | **70.47** | |
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| llama-3.2-Korean-Bllossom-AICA-5B | 26.01 | 21.60 | 17.08 | 45.33 | 27.51 | |
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### MM Benchmarks |
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- Global MM Bench dataset: [OpenCampass MM leaderboard](https://rank.opencompass.org.cn/leaderboard-multimodal) |
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- Korean MM Bench dataset: [NCSOFT](https://huggingface.co/NCSOFT). |
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## Chat Prompt😶🌫️ |
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```yaml |
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<start_of_turn>user<image> |
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Hello! My favorite food is Gukbap🍚!<end_of_turn> |
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<start_of_turn>model |
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(model answer) |
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``` |
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## Gukbap-VL Series models🍚🍚 |
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- [HumanF-MarkrAI/Gukbap-Qwen2.5-34B-VL](https://huggingface.co/HumanF-MarkrAI/Gukbap-Qwen2.5-34B-VL) |
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## BibTeX |
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``` |
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@article{HumanF-MarkrAI, |
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title={Gukbap-Gemma2-9B-VL}, |
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author={MarkrAI}, |
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year={2025}, |
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url={https://huggingface.co/HumanF-MarkrAI} |
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} |
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``` |
