LLaMA-Pro-Ko-8B Model Card
Model Description
LLaMA-Pro is an advanced iteration of the original LLaMA model, augmented with additional Transformer blocks. Unlike its predecessor, Llama-pro, which was specialized for programming and mathematics, Llama-Pro-Ko is tailored to the language domain, undergoing post-training for enhanced performance.
Development and Training
The NLP & AI Lab at Korea University developed LLaMA-Pro-Ko, a model boasting 8 billion parameters. This model extends LLaMA2-7B by incorporating Korean tokens via vocabulary extension and was further refined by training on a Korean corpus of 10 billion tokens, exclusively without the inclusion of English data.
Language Specialization and Transfer
While previous models like Llama-ko and Llama-2-ko experienced diminished English capabilities as they learned Korean, Llama-Pro's language transfer approach aims to bolster Korean language performance with minimal impact on its English proficiency.
Bilingual Performance Evaluation
LLaMA-Pro-Ko's performance is evaluated on two fronts: its proficiency in English and its mastery of Korean, showcasing its capabilities as a bilingual model.
Korean Evaluation
Open Ko LLM Benchmark
| Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 | AVG | |
|---|---|---|---|---|---|---|
| Llama-2-7b | 31.91 | 41.68 | 34.11 | 48.49 | 30.34 | 37.31 |
| beomi/open-llama-2-ko-7b | 40.02 | 50.27 | 27.60 | 38.67 | 42.15 | 39.74 |
| llama-pro-ko-8b | 40.19 | 51.26 | 36.80 | 40.24 | 43.8 | 42.46 |
English Evaluation
Open LLM Benchmark
| ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | AVG | diff | |
|---|---|---|---|---|---|---|---|
| meta-llama/Llama-2-7b | 53.07 | 78.59 | 46.87 | 38.76 | 74.03 | 58.26 | 0 |
| beomi/llama-2-ko-7b | 48.46 | 75.28 | 39.56 | 34.49 | 72.14 | 53.99 | -4.28 |
| beomi/open-llama-2-ko-7b | 46.84 | 69.48 | 29.86 | 35.35 | 66.30 | 49.57 | -8.70 |
| llama-pro-ko-8b | 53.24 | 77.93 | 47.06 | 38.32 | 72.22 | 57.75 | -0.51 |