OLAIR
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ko-r1-7b-v2.0.3

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 ---
 library_name: transformers
-tags: []
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 ---
 library_name: transformers
+license: mit
+datasets:
+- OLAIR/Open-R1-Ko-SFT-v2.0
+language:
+- ko
+base_model:
+- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
 ---
+# Model Card: OLAIR/ko-r1-7b-v2.0.3
+This document describes the OLAIR/ko-r1-7b-v2.0.3 model, including its training data, intended use, performance benchmarks, limitations, and ethical considerations.
+---
+## 1. Overview
+**Model Name:** OLAIR/ko-r1-7b-v2.0.3
+**Model Type:** Large Language Model (LLM) for Korean language understanding and reasoning
+**Version:** 2.0.3
+This model is designed to provide Korean language capabilities with a focus on reasoning tasks. It is the second version in its series, building upon previous iterations with improvements in training data and fine-tuning methodologies.
+## 2. Training Data
+The model was trained on the dataset provided by OLAIR, specifically the [Open-R1-Ko-SFT-v2.0](https://huggingface.co/datasets/OLAIR/Open-R1-Ko-SFT-v2.0) dataset. This dataset includes a curated collection of Korean language data, optimized for supervised fine-tuning (SFT) to enhance reasoning and natural language understanding capabilities in Korean.
+## 3. Benchmark Performance
+The model's performance has been evaluated using the HAE-RAE Reasoning Challenge (HRC), which measures reasoning abilities across various domains. Below are the benchmark results for several models, including OLAIR/ko-r1-7b-v2.0.3:
+| Model                                 | Chemistry | Math  | Physics | Physics Word Puzzles | Puzzles | Average |
+|---------------------------------------|-----------|-------|---------|----------------------|---------|---------|
+| o1-2024-12-17                         | 42.9      | 74.5  | 77.8    | 70.0                 | 30.8    | 59.2    |
+| o3-mini-high                          | 35.7      | 72.7  | 70.4    | 70.0                 | 23.1    | 54.4    |
+| o3-mini-2025-01-31                     | 35.7      | 74.5  | 74.1    | 60.0                 | 7.7     | 50.4    |
+| o1-mini-2024-09-12                     | 35.7      | 54.5  | 63.0    | 60.0                 | 0.0     | 42.6    |
+| Deepseek-R1                           | 35.7      | 52.7  | 51.9    | 60.0                 | 0.0     | 40.1    |
+| gpt-4o-2024-11-20                      | 28.6      | 21.8  | 37.0    | 50.0                 | 0.0     | 27.5    |
+| **Ko-R1-7B-v2.0.3**                   | **7.1**   | **56.4**  | **29.6**    | **40.0**                 | **0.0**     | **26.6**    |
+| Qwen2.5-72B-Instruct                  | 35.7      | 29.1  | 37.0    | 30.0                 | 0.0     | 26.4    |
+| Ko-R1-7B-v1                           | 0.0       | 60.0  | 22.2    | 40.0                 | 0.0     | 24.4    |
+| Exaone-3.5-32B-Instruct               | 28.6      | 27.3  | 22.2    | 40.0                 | 0.0     | 23.6    |
+| gpt-4o-mini-2024-07-18                 | 7.1       | 29.1  | 22.2    | 50.0                 | 0.0     | 21.7    |
+| UNIVA-Bllossom_DeepSeek-llama3.1-Bllossom-8B | 14.3      | 10.9  | 33.3    | 0.0                  | 0.0     | 11.7    |
+*Note:* The above table reflects performance across multiple reasoning domains. The metrics indicate that while OLAIR/ko-r1-7b-v2.0.3 shows competitive performance in certain areas (e.g., Math), there remain challenges, particularly in Chemistry and Physics-related tasks, compared to some higher-performing counterparts.
+## 4. Limitations
+- The model is still vulnerable to Korean-related inputs, leading to endless loops of thinking. We are working to fix it.
+## ETC
+How to Cite
+```
+To be added
+```
+Contact
+```
+spthsrbwls123@yonsei.ac.kr
+```