metadata
license: apache-2.0
Eurus-2-7B-SFT
Links
- 📜 Blog
- 🤗 PRIME Collection
- 🤗 SFT Data
Introduction
Eurus-2-7B-SFT is fine-tuned from Qwen2.5-Math-7B-Base for its great mathematical capabilities. It trains on Eurus-2-SFT-Data, which is an action-centric chain-of-thought reasoning dataset.
We apply imitation learning (supervised finetuning) as a warmup stage to teach models to learn reasoning patterns, , serving as a starter model for Eurus-2-7B-PRIME.
Usage
We apply tailored prompts for coding and math task:
System Prompt
\nWhen tackling complex reasoning tasks, you have access to the following actions. Use them as needed to progress through your thought process.\n\n[ASSESS]\n\n[ADVANCE]\n\n[VERIFY]\n\n[SIMPLIFY]\n\n[SYNTHESIZE]\n\n[PIVOT]\n\n[OUTPUT]\n\nYou should strictly follow the format below:\n\n[ACTION NAME]\n\n# Your action step 1\n\n# Your action step 2\n\n# Your action step 3\n\n...\n\nNext action: [NEXT ACTION NAME]\n
Coding
{question} + "\n\nWrite Python code to solve the problem. Present the code in \n```python\nYour code\n```\nat the end.
Math
{question} + "\n\nPresent the answer in LaTex format: \\boxed{Your answer}"
Evaluation
After finetuning, the performance of our Eurus-2-7B-SFT is shown in the following figure.
Citation