44 lines
5.0 KiB
Markdown
44 lines
5.0 KiB
Markdown
# MMLU
|
||
|
||
> 这是一项大规模的多任务测试，包含来自多个知识领域的选择题。该测试涵盖人文学科、社会科学、硬科学以及其他一些人们学习的重要领域，共涉及57个任务，包括基础数学、美国历史、计算机科学、法律等。要在此测试中获得高准确率，模型必须具备广泛的世界知识和问题解决能力。[数据集链接](https://modelscope.cn/datasets/modelscope/mmlu/summary)
|
||
|
||
## 实验设置
|
||
|
||
- Split: test
|
||
- Total num: 13985
|
||
- 0-shot
|
||
|
||
## 实验结果
|
||
| Model | Revision | Precision | Humanities | STEM | SocialScience | Other | WeightedAvg | Target | Delta |
|
||
|--------------------------------------------------------------------------------------------------|----------|-----------|-------------|------------|---------------|---------|-------------|-------------|--------|
|
||
| [Baichuan2-7B-Base](https://modelscope.cn/models/baichuan-inc/Baichuan2-7B-Base/summary) | v1.0.2 | fp16 | 0.4111 | 0.3807 | 0.5233 | 0.504 | 0.4506 | - | |
|
||
| [Baichuan2-7B-Chat](https://modelscope.cn/models/baichuan-inc/Baichuan2-7B-chat/summary) | v1.0.4 | fp16 | 0.4439 | 0.374 | 0.5524 | 0.5458 | 0.4762 | - | |
|
||
| [chatglm2-6b](https://modelscope.cn/models/ZhipuAI/chatglm2-6b/summary) | v1.0.12 | fp16 | 0.3834 | 0.3413 | 0.4708 | 0.4445 | 0.4077 | 0.4546(CoT) | -4.69% |
|
||
| [chatglm3-6b-base](https://modelscope.cn/models/ZhipuAI/chatglm3-6b-base/summary) | v1.0.1 | fp16 | 0.5435 | 0.5087 | 0.7227 | 0.6471 | 0.5992 | 0.614 | -1.48% |
|
||
| [internlm-chat-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-chat-7b/summary) | v1.0.1 | fp16 | 0.4005 | 0.3547 | 0.4953 | 0.4796 | 0.4297 | - | |
|
||
| [Llama-2-13b-ms](https://modelscope.cn/models/modelscope/Llama-2-13b-ms/summary) | v1.0.2 | fp16 | 0.4371 | 0.3887 | 0.5579 | 0.5437 | 0.4778 | - | |
|
||
| [Llama-2-7b-ms](https://modelscope.cn/models/modelscope/Llama-2-7b-ms/summary) | v1.0.2 | fp16 | 0.3146 | 0.3037 | 0.4134 | 0.3885 | 0.3509 | - | |
|
||
| [Qwen-14B-Chat](https://modelscope.cn/models/qwen/Qwen-14B-Chat/summary) | v1.0.6 | bf16 | 0.5326 | 0.5397 | 0.7184 | 0.6859 | 0.6102 | - | |
|
||
| [Qwen-7B](https://modelscope.cn/models/qwen/Qwen-7B/summary) | v1.1.6 | bf16 | 0.387 | 0.4 | 0.5403 | 0.5139 | 0.4527 | - | |
|
||
| [Qwen-7B-Chat-Int8](https://modelscope.cn/models/qwen/Qwen-7B-Chat-Int8/summary) | v1.1.6 | int8 | 0.4322 | 0.4277 | 0.6088 | 0.5778 | 0.5035 | - | |
|
||
|
||
- 目标 (Target) -- 模型在数据集上的官方声明得分
|
||
- 差值 (Delta) -- 加权平均得分与目标得分之间的差异
|
||
|
||
|
||
### Settings: (Split: test, Total num: 13985, 5-shot)
|
||
|
||
| Model | Revision | Precision | Humanities | STEM | SocialScience | Other | WeightedAvg | Avg | Target | Delta |
|
||
|---------------------|----------|-----------|------------|--------|---------------|--------|-------------|--------|--------------------|---------|
|
||
| Baichuan2-7B-Base | v1.0.2 | fp16 | 0.4295 | 0.398 | 0.5736 | 0.5325 | 0.4781 | 0.4918 | 0.5416 (official) | -4.98% |
|
||
| Baichuan2-7B-Chat | v1.0.4 | fp16 | 0.4344 | 0.3937 | 0.5814 | 0.5462 | 0.4837 | 0.5029 | 0.5293 (official) | -2.64% |
|
||
| chatglm2-6b | v1.0.12 | fp16 | 0.3941 | 0.376 | 0.4897 | 0.4706 | 0.4288 | 0.4442 | - | - |
|
||
| chatglm3-6b-base | v1.0.1 | fp16 | 0.5356 | 0.4847 | 0.7175 | 0.6273 | 0.5857 | 0.5995 | - | - |
|
||
| internlm-chat-7b | v1.0.1 | fp16 | 0.4171 | 0.3903 | 0.5772 | 0.5493 | 0.4769 | 0.4876 | - | - |
|
||
| Llama-2-13b-ms | v1.0.2 | fp16 | 0.484 | 0.4133 | 0.6157 | 0.5809 | 0.5201 | 0.5327 | 0.548 (official) | -1.53% |
|
||
| Llama-2-7b-ms | v1.0.2 | fp16 | 0.3747 | 0.3363 | 0.4372 | 0.4514 | 0.3979 | 0.4089 | 0.453 (official) | -4.41% |
|
||
| Qwen-14B-Chat | v1.0.6 | bf16 | 0.574 | 0.553 | 0.7403 | 0.684 | 0.6313 | 0.6414 | 0.646 (official) | -0.46% |
|
||
| Qwen-7B | v1.1.6 | bf16 | 0.4587 | 0.426 | 0.6078 | 0.5629 | 0.5084 | 0.5151 | 0.567 (official) | -5.2% |
|
||
| Qwen-7B-Chat-Int8 | v1.1.6 | int8 | 0.4697 | 0.4383 | 0.6284 | 0.5967 | 0.5271 | 0.5347 | 0.554 (official) | -1.93% |
|
||
|