Update README.md

README.md

@@ -21,7 +21,7 @@ BlueLM 是由 vivo AI 全球研究院自主研发的大规模预训练语言模
 
 BlueLM is a large-scale open-source language model independently developed by the vivo AI Lab. This release includes 2K and 32K context length versions for both Base and Chat models.
 
-- **High-quality Data**: BlueLM is trained on a high-quality data with 2.6 trillion tokens. Our train corpus contains Chinese, English, Japanese and Korean data.
+- **High-quality Data**: BlueLM is trained on a high-quality data with 2.6 trillion tokens. Our train corpus mainly consists of Chinese and English data, with a small amount of Japanese and Korean data.
 - **Stronger Performance**: BlueLM-7B-Chat achieves a strong competitive performance in C-Eval and CMMLU benchmarks of the same size.
 - **Longer Context**: We have extended the context length of both BlueLM-7B-Base-32K and BlueLM-7B-Chat-32K models from 2K to 32K. The models can support longer context understanding while maintaining the same basic capabilities.
 - **Model License**: BlueLM weights are open for academic research and commercial use. 
@@ -37,7 +37,7 @@ The release versions and hugging face download links are listed in the table bel
 
 ## 评测结果/Benchmark Results
 
-为了保证模型评测的一致性，我们采用 [opencompass](https://opencompass.org.cn/leaderboard-llm) 进行相关榜单的评测。我们分别在 C-Eval、MMLU、CMMLU、GaoKao、AGIEval、BBH、GSM8K、MATH 和 HumanEval 榜单对 BlueLM 的通用能力、数学能力和代码能力进行了测试。
+为了保证模型评测的一致性，我们采用 [OpenCompass](https://opencompass.org.cn/leaderboard-llm) 进行相关榜单的评测。我们分别在 C-Eval、MMLU、CMMLU、GaoKao、AGIEval、BBH、GSM8K、MATH 和 HumanEval 榜单对 BlueLM 的通用能力、数学能力和代码能力进行了测试。
 
 To ensure the consistency of model evaluation, we use [OpenCompass](https://opencompass.org.cn/leaderboard-llm) to evaluate the performance on relevant leaderboards. We conducted extensive tests on C-Eval, MMLU, CMMLU, GaoKao, AGIEval, BBH, GSM8K, MATH and HumanEval datasets across general ability, mathematical ability and coding ability.