Rabbit
Collection
5 items
โข
Updated
๋ณธ ๋ชจ๋ธ์ ๋ค์๊ณผ ๊ฐ์ ์ฃผ์ ํ๋ จ ๋จ๊ณ๋ฅผ ๊ฑฐ์ณค์ต๋๋ค:
SFT (Supervised Fine-Tuning)
DPO (Direct Preference Optimization)
๋ชจ๋ธ ๊ฐ๋ฐ ๊ณผ์ ์์ ์ค๋ฆฌ์ ๊ณ ๋ ค์ฌํญ์ ์ต๋ํ ๋ฐ์ํ์์ผ๋, ์ฌ์ฉ์๋ ํญ์ ๊ฒฐ๊ณผ๋ฅผ ๋นํ์ ์ผ๋ก ๊ฒํ ํด์ผ ํฉ๋๋ค.
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("CarrotAI/Llama-3.2-Rabbit-Ko-3B-Instruct-2412")
tokenizer = AutoTokenizer.from_pretrained("CarrotAI/Llama-3.2-Rabbit-Ko-3B-Instruct-2412")
LogicKor
Category | Single turn | Multi turn |
---|---|---|
์ํ(Math) | 5.86 | 5.14 |
๋ฌธ๋ฒ(Grammar) | 4.71 | 1.29 |
์ดํด(Understanding) | 4.00 | 4.43 |
์ถ๋ก (Reasoning) | 5.14 | 6.71 |
์ฝ๋ฉ(Coding) | 7.43 | 7.57 |
๊ธ์ฐ๊ธฐ(Writing) | 8.43 | 8.00 |
Total | 5.93 | 5.52 |
Overall | 5.73 |
Tasks | Version | Filter | n-shot | Metric | Value | Stderr | ||
---|---|---|---|---|---|---|---|---|
gsm8k | 3 | flexible-extract | 5 | exact_match | โ | 0.7013 | ยฑ | 0.0126 |
strict-match | 5 | exact_match | โ | 0.2418 | ยฑ | 0.0118 | ||
gsm8k-ko | 1 | flexible-extract | 5 | exact_match | โ | 0.4466 | ยฑ | 0.0137 |
strict-match | 5 | exact_match | โ | 0.4420 | ยฑ | 0.0137 | ||
ifeval | 4 | none | 0 | inst_level_loose_acc | โ | 0.8549 | ยฑ | N/A |
none | 0 | inst_level_strict_acc | โ | 0.8225 | ยฑ | N/A | ||
none | 0 | prompt_level_loose_acc | โ | 0.7874 | ยฑ | 0.0176 | ||
none | 0 | prompt_level_strict_acc | โ | 0.7468 | ยฑ | 0.0187 |
Task | Score | shot |
---|---|---|
haerae | 43.26 | 5 |
@article{Llama3.2RabbitKo3BInstruct,
title={CarrotAI/Llama-3.2-Rabbit-Ko-3B-Instruct-2412 Card},
author={CarrotAI (L, GEUN)},
year={2024},
url = {https://huggingface.co/CarrotAI/Llama-3.2-Rabbit-Ko-3B-Instruct-2412}
}
Base model
meta-llama/Llama-3.2-3B-Instruct