Nanbeige
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Nanbeige2-16B-Chat

Question Answering

text-generation

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ZekeWang commited on Jun 1

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@@ -27,7 +27,7 @@ During the alignment phase, we initially trained our model using 1 million sampl
 We have evaluated Nanbeige2-8B-Chat's general question-answering capabilities and human preference alignments on several popular benchmark datasets. The model has achieved notable results in single-turn English QA ([AlpacaEval 2.0](https://tatsu-lab.github.io/alpaca_eval/)), single-turn Chinese QA ([AlignBench](https://github.com/THUDM/AlignBench)), and multi-turn English QA ([MT-Bench](https://arxiv.org/abs/2306.05685)).
-| AlpacaEval 2.0 | AlignBench | MT-Bench |
 |:--------------:|:----------:|:--------:|
 |   43.0%/40.4%  |   7.62     |   8.60   |

 We have evaluated Nanbeige2-8B-Chat's general question-answering capabilities and human preference alignments on several popular benchmark datasets. The model has achieved notable results in single-turn English QA ([AlpacaEval 2.0](https://tatsu-lab.github.io/alpaca_eval/)), single-turn Chinese QA ([AlignBench](https://github.com/THUDM/AlignBench)), and multi-turn English QA ([MT-Bench](https://arxiv.org/abs/2306.05685)).
+| AlpacaEval 2.0(LC Win Rate/ Win Rate) | AlignBench | MT-Bench |
 |:--------------:|:----------:|:--------:|
 |   43.0%/40.4%  |   7.62     |   8.60   |