metadata
language:
- zh
- en
license: apache-2.0
datasets:
- wenbopan/Fusang-v1
- wenbopan/OpenOrca-zh-20k
Faro-Yi-9B
Faro-Yi-9B is an improved Yi-9B-200K with extensive instruction tuning on Fusang-V1. Compared to Yi-9B-200K, Faro-Yi-9B has gained greater capability in various downstream tasks and long-context modeling thanks to the large-scale synthetic data in Fusang-V1.
Performance
Faro-Yi-9B enhances its ability compared to Yi-9B-200K in most dimensions, especially in long-range modeling and bilingual (English, Chinese) understanding. Fi is competitive among all open-sourced models at around 9B parameters. Fi-9B is good at both factual tasks and preferred by LLM-judges.
Fact-based Evaluation (Open LLM Leaderboard)
| Metric | MMLU | GSM8K | HellaSwag | TruthfulQA | Arc | Winogrande |
|---|---|---|---|---|---|---|
| Yi-9B-200K | 65.73 | 50.49 | 56.72 | 33.80 | 69.25 | 71.67 |
| Faro-Yi-9B | 68.80 | 63.08 | 57.28 | 40.86 | 72.58 | 71.11 |
Long-context Modeling (LongBench)
| Name | Average_zh | Average_en | Code Completion |
|---|---|---|---|
| Yi-9B-200K | 30.288 | 36.7071 | 72.2 |
| Faro-Yi-9B | 41.092 | 40.9536 | 46.0 |
Score breakdown
| Name | Few-shot Learning_en | Synthetic Tasks_en | Single-Doc QA_en | Multi-Doc QA_en | Summarization_en | Few-shot Learning_zh | Synthetic Tasks_zh | Single-Doc QA_zh | Multi-Doc QA_zh | Summarization_zh |
|---|---|---|---|---|---|---|---|---|---|---|
| Yi-9B-200K | 60.6 | 22.8 | 30.9 | 38.9 | 25.8 | 46.5 | 28.0 | 49.6 | 17.7 | 9.7 |
| Faro-Yi-9B | 63.8 | 40.2 | 36.2 | 38.0 | 26.3 | 30.0 | 75.1 | 55.6 | 30.7 | 14.1 |
Bilingual Ability (CMMLU & MMLU)
| Name | MMLU | CMMLU |
|---|---|---|
| Yi-9B-200K | 65.73 | 71.97 |
| Faro-Yi-9B | 68.80 | 73.28 |