Update README.md

README.md

@@ -36,6 +36,55 @@ KeyError: 'qwen2'
 We do not advise you to use base language models for text generation. Instead, you can apply post-training, e.g., SFT, RLHF, continued pretraining, etc., on this model.
 
 
+## Performance
+
+The evaluation of base models mainly focuses on the model performance of natural language understanding, general question answering, coding, mathematics, scientific knowledge, reasoning, multilingual capability, etc. 
+
+The datasets for evaluation include: 
+ 
+**English Tasks**: MMLU (5-shot), MMLU-Pro (5-shot), GPQA (5shot), Theorem QA (5-shot), BBH (3-shot), HellaSwag (10-shot), Winogrande (5-shot), TruthfulQA (0-shot), ARC-C (25-shot)
+ 
+**Coding Tasks**: EvalPlus (0-shot) (HumanEval, MBPP, HumanEval+, MBPP+), MultiPL-E (0-shot) (Python, C++, JAVA, PHP, TypeScript, C#, Bash, JavaScript)
+  
+**Math Tasks**: GSM8K (4-shot), MATH (4-shot)
+ 
+**Chinese Tasks**: C-Eval (5-shot), CMMLU (5-shot)
+ 
+**Multilingual Tasks**: Multi-Exam (M3Exam 5-shot, IndoMMLU 3-shot, ruMMLU 5-shot, mMMLU 5-shot), Multi-Understanding (BELEBELE 5-shot, XCOPA 5-shot, XWinograd 5-shot, XStoryCloze 0-shot, PAWS-X 5-shot), Multi-Mathematics (MGSM 8-shot), Multi-Translation (Flores-101 5-shot)
+ 
+#### Qwen2-72B performance
+|  Datasets  | DeepSeek-V2 | Mixtral-8x22B   |   Llama-3-70B  |   Qwen1.5-72B  |   Qwen1.5-110B  |  **Qwen2-72B**  |
+| :--------| :---------: | :------------: | :------------: | :------------: | :------------: |:------------: |
+|Architecture | MoE | MoE | Dense | Dense | Dense | Dense |
+|#Activated Params | 21B | 39B | 70B | 72B | 110B | 72B |
+|#Params | 236B | 140B | 70B | 72B | 110B   | 72B|
+|   ***English***  |    |    |   |    |	    |	    |
+|MMLU |78.5 | 77.8  | 79.5 | 77.5 | 80.4 |  **84.2**  |
+|MMLU-Pro | - | 49.5  | 52.8 | 45.8 | 49.4 |  **55.6**  |
+|GPQA | -| 34.3  | 36.3 | 36.3 | 35.9 |  **37.9**  |
+|Theorem QA | -| 35.9  | 32.3 | 29.3 | 34.9 |  **43.1**  |
+|BBH  | 78.9 |78.9   | 81.0 | 65.5 | 74.8 |  **82.4**  |
+|HellaSwag  | 87.8 | **88.7**   | 88.0 |  86.0 | 87.5 | 87.6 |
+|WindoGrande  | 84.8|85.0  |  **85.3**  |  83.0 | 83.5 |  85.1 |
+|ARC-C  | 70.0| **70.7**   | 68.8 | 65.9 | 69.6 |  68.9 |
+|TruthfulQA  | 42.2 | 51.0  | 45.6 |  **59.6**  | 49.6 | 54.8 |
+|   ***Coding***  |    |    |   |    |	    |	    |
+|HumanEval | 45.7 | 46.3  | 48.2 | 46.3 | 54.3 |  **64.6**   |
+|MBPP |73.9 | 71.7  | 70.4 | 66.9 | 70.9 |  **76.9**   |
+|EvalPlus | 55.0 | 54.1  | 54.8 | 52.9 | 57.7 |  **65.4**   |
+|MultiPL-E |44.4 | 46.7  | 46.3 | 41.8 | 52.7 |  **59.6**   |
+|   ***Mathematics***  |    |    |   |    |	    |	    |
+|GSM8K | 79.2 | 83.7   | 83.0 | 79.5 | 85.4 |  **89.5**  |
+|MATH  | 43.6 | 41.7  | 42.5 | 34.1 | 49.6 |  **51.1**  |
+|   ***Chinese***  |    |    |   |    |	    |	    |
+|C-Eval | 81.7 | 54.6    |  65.2 |  84.1 | 89.1 |   **91.0**  |
+|CMMLU   | 84.0 | 53.4  | 67.2 | 83.5 | 88.3 |  **90.1**  |
+|   ***Multilingual***  |    |    |   |    |	    |	    |
+|Mulit-Exam   | 67.5 | 63.5 |   70.0    |  66.4 |  75.6 |   **76.6**  |
+|Multi-Understanding | 77.0 |  77.7    |  79.9 |  78.2 | 78.2 |   **80.7**  |
+|Multi-Mathematics |  58.8 | 62.9    |  67.1 |  61.7 | 64.4 |   **76.0**  |
+|Multi-Translation |   36.0 | 23.3    |   **38.0**  |  35.6 | 36.2 |  37.8 |
+
 ## Citation
 
 If you find our work helpful, feel free to give us a cite.