Update README.md

README.md

@@ -122,6 +122,31 @@ For deployment, we recommend using vLLM. You can enable the long-context capabil
 
 **Note**: Presently, vLLM only supports static YARN, which means the scaling factor remains constant regardless of input length, **potentially impacting performance on shorter texts**. We advise adding the `rope_scaling` configuration only when processing long contexts is required.
 
+## Evaluation
+
+We briefly compare Qwen2-7B-Instruct with similiar-sized instruction-tuned LLMs, including Qwen1.5-7B-Chat. The results are shown below:
+
+| Datasets | Llama-3-8B-Instruct | Yi-1.5-9B-Chat | GLM-4-9B-Chat | Qwen1.5-7B-Chat | Qwen2-7B-Instruct |
+| :--- | :---: | :---: | :---: | :---: | :---: |
+| _**English**_ |  |  |  |  |  |
+| MMLU | 68.4 | 69.5 | **72.4** | 59.5 | 70.5 |
+| MMLU-Pro | 41.0 | - | - | 29.1 | **44.1** |
+| GPQA | **34.2** | - | **-** | 27.8 | 25.3 |
+| TheroemQA | 23.0 | - | - | 14.1 | **25.3** |
+| MT-Bench | 8.05 | 8.20 | 8.35 | 7.60 | **8.41** |
+| _**Coding**_ |  |  |  |  |  |
+| Humaneval | 62.2 | 66.5 | 71.8 | 46.3 | **79.9** |
+| MBPP | **67.9** | - | - | 48.9 | 67.2 |
+| MultiPL-E | 48.5 | - | - | 27.2 | **59.1** |
+| Evalplus | 60.9 | - | - | 44.8 | **70.3** |
+| LiveCodeBench | 17.3 | - | - | 6.0 | **26.6** |
+| _**Mathematics**_ |  |  |  |  |  |
+| GSM8K | 79.6 | **84.8** | 79.6 | 60.3 | 82.3 |
+| MATH | 30.0 | 47.7 | **50.6** | 23.2 | 49.6 |
+| _**Chinese**_ |  |  |  |  |  |
+| C-Eval | 45.9 | - | 75.6 | 67.3 | **77.2** |
+| AlignBench | 6.20 | 6.90 | 7.01 | 6.20 | **7.21** |
+
 ## Citation
 
 If you find our work helpful, feel free to give us a cite.