Gemma 2 9B
Gemma 2 9B IT is an instruction-tuned version of Google's Gemma 2 9B base model. It was trained on 8 trillion tokens of web data, code, and math content. The model features sliding window attention, logit soft-capping, and knowledge distillation techniques. It's optimized for dialogue applications through supervised fine-tuning, distillation, RLHF, and model merging using WARP.
Benchmark results
| Benchmark | Score | Tags | Source |
|---|---|---|---|
| AGIEval | 52.8% | self-reported llm-stats | link → |
| ARC-C | 68.4% | self-reported llm-stats | link → |
| ARC-E | 88.0% | self-reported llm-stats | link → |
| BIG-Bench | 68.2% | self-reported llm-stats | link → |
| BoolQ | 84.2% | self-reported llm-stats | link → |
| GSM8k | 68.6% | self-reported llm-stats | link → |
| HellaSwag | 81.9% | self-reported llm-stats | link → |
| HumanEval | 40.2% | self-reported llm-stats | link → |
| MATH | 36.6% | self-reported llm-stats | link → |
| MBPP | 52.4% | self-reported llm-stats | link → |
| MMLU | 71.3% | self-reported llm-stats | link → |
| Natural Questions | 29.2% | self-reported llm-stats | link → |
| PIQA | 81.7% | self-reported llm-stats | link → |
| Social IQa | 53.4% | self-reported llm-stats | link → |
| TriviaQA | 76.6% | self-reported llm-stats | link → |
| Winogrande | 80.6% | self-reported llm-stats | link → |