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@@ -93,7 +93,7 @@ It is trained by jointly train SeaLLM's multilingual text-only datasets along wi
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  ### Multilingual Text-only World Knowledge
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- We evaluate models on 3 benchmarks following the recommended default setups: 5-shot MMLU for En, 3-shot [M3Exam](https://arxiv.org/pdf/2306.05179.pdf) (M3e) for En, Zh, Vi, Id, Th, and zero-shot [VMLU](https://vmlu.ai/) for Vi.
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  On text-only benchmarks, [SeaLMMM-7B-v0.1](https://huggingface.co/SeaLLMs/SeaLMMM-7B-v0.1) is generally on-par with [SeaLLM-7B-v2](https://huggingface.co/SeaLLMs/SeaLLM-7B-v2) - its base LLM model. This demonstrates that our multimodal training regime does not vastly degrade text-only performance.
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  ### Multilingual Text-only World Knowledge
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+ We evaluate models on 3 benchmarks following the recommended default setups: 5-shot MMLU for En, 3-shot [M3Exam](https://arxiv.org/pdf/2306.05179.pdf) (M3e) for En, Zh, Vi, Id, Th.
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  On text-only benchmarks, [SeaLMMM-7B-v0.1](https://huggingface.co/SeaLLMs/SeaLMMM-7B-v0.1) is generally on-par with [SeaLLM-7B-v2](https://huggingface.co/SeaLLMs/SeaLLM-7B-v2) - its base LLM model. This demonstrates that our multimodal training regime does not vastly degrade text-only performance.
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