---
model-index:
- name: EEVE-Math-10.8B
  results:
  - task:
      type: text-generation
    dataset:
      name: gsm8k-ko
      type: gsm8k
    metrics:
    - name: pass@1
      type: pass@1
      value: 0.539
      verified: false
base_model: yanolja/EEVE-Korean-10.8B-v1.0
license: cc-by-sa-4.0
language:
- ko
tags:
- math
datasets:
- kuotient/orca-math-word-problems-193k-korean
---
# EEVE-Math-10.8B

`EEVE-Math` 프로젝트는
- Orca-Math-200k 번역 ([Orca-Math: Unlocking the potential of SLMs in Grade School Math](https://arxiv.org/pdf/2402.14830.pdf))
- gsm8k 번역, lm_eval 활용
- Mergekit을 이용한 dare-ties 사용 ([DARE](https://arxiv.org/abs/2311.03099))

에 대한 내용을 포괄하고 있습니다.

> 이 모델은 orca-math-word-problems-193k-korean 데이터셋을 이용하여 학습되었습니다. 응답 중 일부는 LaTeX 형식을 이용하여 결과를 반환하지만, 완성된 형식이 아닐 수 있습니다. 현재 M1 stage까지 진행되었습니다.

| Model | gsm8k-ko(pass@1) |
|---|---|
| Base | 0.4049 |
| SFT(M1) | 0.508 |
| SFT(M1) -> SFT | **0.539** |
| SFT(M1) -> KTO(M2) | - |
| SFT -> KTO(M2) -> KTO(final) | - |


## Specifications
- SFT(M1) -> SFT 단계

## Base Model
[yanolja/EEVE-Korean-10.8B-v1.0](https://huggingface.co/yanolja/EEVE-Korean-10.8B-v1.0)

## Dataset
[orca-math-word-problems-193k-korean](https://huggingface.co/datasets/kuotient/orca-math-word-problems-193k-korean)

## Evaluation
[gsm8k-ko](https://huggingface.co/datasets/kuotient/gsm8k-ko), kobest
```
git clone https://github.com/kuotient/lm-evaluation-harness.git
cd lm-evaluation-harness
pip install -e .
```
```
lm_eval --model hf \
    --model_args pretrained=yanolja/EEVE-Korean-Instruct-2.8B-v1.0 \
    --tasks gsm8k-ko \
    --device cuda:0 \
    --batch_size auto:4
```

| Model | gsm8k(pass@1) | boolq(acc) | copa(acc) | hellaswag(acc) | Overall |
|---|---|---|---|---|---|
| yanolja/EEVE-Korean-10.8B-v1.0 | 0.4049 | - | - | - | - | - |
| yanolja/EEVE-Korean-Instruct-10.8B-v1.0 | 0.4511 | **0.8668** | **0.7450** | 0.4940 | 0.6392 |
| **EEVE-Math-10.8B** | **0.5390** | 0.8027 | 0.7260 | 0.4760 | 0.6359 |
| [**EEVE-Instruct-Math-10.8B**](https://huggingface.co/kuotient/EEVE-Instruct-Math-10.8B) | 0.4845 | 0.8519 | 0.7410 | **0.4980** | **0.6439** |