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--- |
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license: apache-2.0 |
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language: |
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- en |
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metrics: |
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- accuracy |
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base_model: |
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- meta-llama/Llama-3.1-8B-Instruct |
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pipeline_tag: visual-question-answering |
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--- |
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# MMEvol Model Card |
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## Model Details |
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Here are the pretrained weights and instruction tuning weights |
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| Model | Pretrained Projector | Base LLM | PT Data | IT Data | Download | |
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| ---------------- | -------------------- | --------- | ------------------------------------------------------------ | ------- | -------- | |
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| MMEvol-LLaMA3-8B | [mm_projector](https://huggingface.co/Tongyi-ConvAI/MMEvol/tree/main/llama3) | LLaMA3-8B | [LLaVA-Pretrain](https://huggingface.co/datasets/liuhaotian/LLaVA-Pretrain) | MMEvol | [ckpt](https://huggingface.co/Tongyi-ConvAI/MMEvol/tree/main/llama3)| |
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## Performance |
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### VLMEvalKit Support (OpenCompass) |
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| Model | MME_C | MMStar | HallBench | MathVista_mini | MMMU_val | AI2D | POPE | BLINK | RWQA | |
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| ---------------- | ----- | ------ | --------- | -------------- | -------- | ---- | ---- | ----- | ---- | |
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| MMEvol-LLaMA3-8B | 47.8 | 50.1 | 62.3 | 50.0 | 40.8 | 73.9 | 86.8 | 46.4 | 62.6 | |
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### VLMEvalKit Not Support (VQADataSet) |
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| Model | VQA_v2 | GQA | MIA | MMSInst | |
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| ---------------- | ------ | ---- | ---- | ------- | |
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| MMEvol-LLaMA3-8B | 83.4 | 65.0 | 78.8 | 32.3 | |
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## Paper or resources for more information |
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- Page: https://mmevol.github.io/ |
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- arXiv: https://arxiv.org/pdf/2409.05840 |
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## License |
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Llama 3 is licensed under the LLAMA 3 Community License, |
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Copyright (c) Meta Platforms, Inc. All Rights Reserved. |
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## Contact us if you have any questions |
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- Run Luo — r.luo@siat.ac.cn |
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- Haonan Zhang — zchiowal@gmail.com |
