Qwen2-1.5B
Qwen2-1.5B is an AI model published by 阿里巴巴, released on 2024-06-07, for 基础大模型, with 15.0B parameters, and 32K tokens context length, requiring about 3.09GB storage, under the Apache 2.0 license.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
阿里巴巴开源的15亿参数规模的大语言模型，是小规模参数语言模型中表现最强的一个。与其它小规模参数模型相比，该模型在不同评测结果上都取得了非常好的结果。下图是该模型与其它模型的对比结果：
| Datasets | Phi-2 | Gemma-2B | MiniCPM | Qwen1.5-1.8B | Qwen2-0.5B | Qwen2-1.5B |
|---|---|---|---|---|---|---|
| #Non-Emb Params | 2.5B | 2.0B | 2.4B | 1.3B | 0.35B | 1.3B |
| MMLU | 52.7 | 42.3 | 53.5 | 46.8 | 45.4 | 56.5 |
| MMLU-Pro | - | 15.9 | - | - | 14.7 | 21.8 |
| Theorem QA | - | - | - | - | 8.9 | 15.0 |
| HumanEval | 47.6 | 22.0 | 50.0 | 20.1 | 22.0 | 31.1 |
| MBPP | 55.0 | 29.2 | 47.3 | 18.0 | 22.0 | 37.4 |
| GSM8K | 57.2 | 17.7 | 53.8 | 38.4 | 36.5 | 58.5 |
| MATH | 3.5 | 11.8 | 10.2 | 10.1 | 10.7 | 21.7 |
| BBH | 43.4 | 35.2 | 36.9 | 24.2 | 28.4 | 37.2 |
| HellaSwag | 73.1 | 71.4 | 68.3 | 61.4 | 49.3 | 66.6 |
| Winogrande | 74.4 | 66.8 | - | 60.3 | 56.8 | 66.2 |
| ARC-C | 61.1 | 48.5 | - | 37.9 | 31.5 | 43.9 |
| TruthfulQA | 44.5 | 33.1 | - | 39.4 | 39.7 | 45.9 |
| C-Eval | 23.4 | 28.0 | 51.1 | 59.7 | 58.2 | 70.6 |
| CMMLU | 24.2 | - | 51.1 | 57.8 | 55.1 | 70.3 |
欢迎关注 DataLearner 官方微信，获得最新 AI 技术推送
