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README.md
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datasets:
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- meta-math/MetaMathQA
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---
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arxiv.org/abs/2309.12284
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View the project page:
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https://meta-math.github.io/
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```bibtex
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@article{yu2023metamath,
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datasets:
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- meta-math/MetaMathQA
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---
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see our paper in https://arxiv.org/abs/2309.12284
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View the project page:
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https://meta-math.github.io/
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## Model Details
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MetaMath-Llemma-7B is fully fine-tuned on the MetaMathQA datasets and based on the powerful Llemma-7B model. It is glad to see using MetaMathQA datasets and change the base model from llama-2-7B to Llemma-7B can boost the MATH performance from 19.8 to **30.0**.
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## Installation
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```
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pip install transformers==4.35.0
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pip install torch==2.0.1
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pip install sentencepiece==0.1.99
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pip install tokenizers==0.13.3
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pip install accelerate==0.21.0
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pip install bitsandbytes==0.40.0
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pip install vllm
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pip install fraction
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pip install protobuf
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```
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## Model Usage
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prompting template:
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'''
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"Below is an instruction that describes a task. "
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"Write a response that appropriately completes the request.\n\n"
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"### Instruction:\n{instruction}\n\n### Response: Let's think step by step."
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'''
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where you need to use your query question to replace the {instruction}
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## Experiments
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| Model | GSM8k Pass@1 | MATH Pass@1 |
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|---------------------|--------------|-------------|
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| MPT-7B | 6.8 | 3.0 |
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| Falcon-7B | 6.8 | 2.3 |
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| LLaMA-1-7B | 11.0 | 2.9 |
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| LLaMA-2-7B | 14.6 | 2.5 |
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| MPT-30B | 15.2 | 3.1 |
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| LLaMA-1-13B | 17.8 | 3.9 |
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| GPT-Neo-2.7B | 19.5 | -- |
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| Falcon-40B | 19.6 | 2.5 |
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| Baichuan-chat-13B | 23.9 | -- |
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| Vicuna-v1.3-13B | 27.6 | -- |
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| LLaMA-2-13B | 28.7 | 3.9 |
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| InternLM-7B | 31.2 | -- |
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| ChatGLM-2-6B | 32.4 | -- |
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| GPT-J-6B | 34.9 | -- |
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| LLaMA-1-33B | 35.6 | 3.9 |
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| LLaMA-2-34B | 42.2 | 6.24 |
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| RFT-7B | 50.3 | -- |
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| LLaMA-1-65B | 50.9 | 10.6 |
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| Qwen-7B | 51.6 | -- |
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| WizardMath-7B | 54.9 | 10.7 |
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| LLaMA-2-70B | 56.8 | 13.5 |
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| WizardMath-13B | 63.9 | 14.0 |
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| MAmmoTH-7B (COT) | 50.5 | 10.4 |
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| MAmmoTH-7B (POT+COT)| 53.6 | 31.5 |
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| Arithmo-Mistral-7B | 74.7 | 25.3 |
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| MetaMath-7B | 66.5 | 19.8 |
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| MetaMath-13B | 72.3 | 22.4 |
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| 🔥 **MetaMath-Llemma-7B** | **69.2** | **30.0** |
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| 🔥 **MetaMath-Mistral-7B** | **77.7** | **28.2** |
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## Citation
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```bibtex
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@article{yu2023metamath,
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