Parallel_7B MathOctopus Open-Source Model - Supports 10 languages, Free to Solve Various Math Problems

Parallel 7B

Developed by Mathoctopus

MathOctopus is a multilingual mathematical reasoning large language model based on the LLaMA 2 architecture, supporting 10 languages and specializing in solving mathematical problems.

Large Language Model

Transformers

Supports Multiple LanguagesOpen Source License:Apache-2.0 #Multilingual Mathematical Reasoning #Cross-lingual Transfer Learning #Mathematical Problem Solving

Downloads 14

Release Time : 10/13/2023

Model Overview

The MathOctopus series of open-source large language models is specifically designed for multilingual mathematical problem solving, trained on the MGSM8KInstruct dataset covering ten different languages. This model significantly outperforms traditional open-source large language models and surpasses ChatGPT's performance in few-shot scenarios.

Model Features

Multilingual Mathematical Reasoning

Supports mathematical problem solving in 10 languages, breaking language barriers

Parallel Training Strategy

Employs parallel training methods to enhance model performance

Rejection Sampling Optimization

Further optimizes model performance through xRFT (multilingual rejection sampling)

Surpassing ChatGPT

Outperforms ChatGPT in few-shot scenarios

Model Capabilities

Multilingual Mathematical Problem Solving

Mathematical Reasoning

Multilingual Text Understanding

Step-by-step Solution for Complex Problems

Use Cases

Education

Multilingual Math Tutoring

Provides math problem solutions for students with different language backgrounds

Achieves an overall accuracy of 40.0% on the MGSM test set

Online Education Platforms

Integrated into educational software to provide multilingual math support

Research

Multilingual NLP Research

Used to study the performance of multilingual models in the mathematical domain

🚀 🐙 Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and Observations

This project introduces 🐙 MathOctopus, a series of open - source large language models tailored for multilingual math problem - solving, which outperforms conventional models in many scenarios.

🚀 Quick Start

Project Page: https://mathoctopus.github.io/
Paper: https://arxiv.org/abs/2310.20246.pdf
Code: https://github.com/microsoft/MathOctopus

✨ Features

We introduce 🐙 MathOctopus, a series of open - source large language models (LLMs) specifically tailored for multilingual math problem - solving. The MathOctopus models are trained on 🤗 MGSM8KInstruct Dataset, encompassing ten distinct languages. MathOctopus notably outperforms conventional open - source LLMs and exhibits superiority over ChatGPT in few - shot scenarios.

📦 Datasets

MGSM8KInstruct

Training Dataset	En	Sw	Zh	Bn	De	Es	Fr	Ja	Ru	Th	Overall
MGSM8KInstruct	7473	7472	7466	6539	7466	7470	7469	7471	7361	7473	73.6K

MSVAMP

Test Dataset	En	Sw	Zh	Bn	De	Es	Fr	Ja	Ru	Th	Overall
MSVAMP	1000	1000	1000	1000	1000	1000	1000	1000	1000	1000	10K

Usage

Our dataset and models are all available at Huggingface.

📚 Models

Base Model: LLama	Parallel - Training	Cross - Training
7B - LLaMA 2	🐙 MathOctopus - Parallel - 7B	🐙 MathOctopus - Cross - 7B
	🐙MathOctopus - Parallel - xRFT - 7B	🐙MathOctopus - Cross - xRFT - 7B
13B - LLaMA 2	🐙 MathOctopus - Parallel - 13B	🐙 MathOctopus - Cross - 13B
	🐙MathOctopus - Parallel - xRFT - 13B	🐙[MathOctopus - Cross - xRFT - 13B]
33B - LLaMA 1	🐙 MathOctopus - Parallel - 33B	🐙 [MathOctopus - Cross - 33B]
70B - LLaMA 2	Coming soon!	Coming Soon!

*-Parallel refers to our model trained with the parallel - training strategy. *-Cross refers to our model trained with cross - training strategy. *-xRFT means we train the model with multilingual rejection sampling.

Overall Results on MGSM

7B Model	En	Sw	Zh	Bn	De	Es	Fr	Ja	Ru	Th	Overall
MathOctopus^C	52.0	23.6	31.6	18.8	38.0	39.2	36.4	27.2	33.6	21.6	32.2
xRFT - MathOctopus^C	51.2	24.0	33.2	18.8	36.0	41.2	37.6	29.6	36.4	25.2	33.3
MathOctopus^P - LoRA	30.4	15.2	23.6	10.4	22.8	24.8	26.4	18.0	22.0	14.8	20.8
MathOctopus^P	52.4	39.2	38.4	28.8	44.8	42.4	43.6	36.0	39.6	34.4	40.0
xRFT - MathOctopus^P	54.8	38.4	45.2	33.2	43.6	45.2	38.0	35.6	48.4	36.4	41.9

13B Model	En	Sw	Zh	Bn	De	Es	Fr	Ja	Ru	Th	Overall
MathOctopus^C	56.4	27.2	39.2	24.0	47.6	49.6	47.6	40.4	42.0	24.8	39.9
xRFT - MathOctopus^C	53.6	28.0	45.2	21.2	48.0	46.4	46.0	35.2	45.6	28.8	39.8
MathOctopus^P	53.2	42.8	48.8	35.2	44.4	48.0	48.4	43.2	47.6	46.8	45.8
xRFT - MathOctopus^P	51.6	46.0	51.2	42.0	49.2	53.2	49.6	39.6	47.6	46.0	47.6

30 - 34B Model	En	Sw	Zh	Bn	De	Es	Fr	Ja	Ru	Th	Overall
MathOctopus^C	55.6	24.4	36.0	19.2	40.4	51.2	44.4	27.2	37.2	21.6	35.7
xRFT - MathOctopus^C	53.6	27.6	34.4	19.2	47.2	47.6	44.8	30.8	38.8	22.8	36.7
MathOctopus^P	56.4	46.8	52.0	35.2	47.2	53.2	48.0	39.2	45.6	41.2	46.5
xRFT - MathOctopus^P	51.6	47.2	52.4	37.6	51.2	52.8	44.4	41.6	50.0	47.6	47.6

Overall Results on MSVAMP

7B Model	En	Sw	Zh	Bn	De	Es	Fr	Ja	Ru	Th	Overall
MathOctopus^C	49.2	36.6	43.6	30.2	48.6	46.8	46.4	42.5	46.7	34.0	42.5
xRFT - MathOctopus^C	49.9	37.7	43.3	32.9	46.5	47.6	47.3	42.7	46.6	36.2	43.1
MathOctopus^P - LoRA	30.4	15.2	23.6	10.4	22.8	24.8	26.4	18.0	22.0	14.8	20.8
MathOctopus^P	46.5	40.1	42.5	29.1	43.5	45.4	46.0	42.5	45.4	35.7	41.7
xRFT - MathOctopus^P	46.8	42.3	43.2	32.8	43.1	44.5	45.3	43.2	42.1	40.5	42.4

13B Model	En	Sw	Zh	Bn	De	Es	Fr	Ja	Ru	Th	Overall
MathOctopus^C	56.6	40.4	49.0	30.3	50.9	54.2	54.7	46.3	52.4	35.7	47.1
xRFT - MathOctopus^C	52.9	41.9	49.2	34.1	50.5	52.8	51.5	45.8	50.2	35.7	46.5
MathOctopus^P	50.7	43.4	42.6	31.8	48.4	49.4	50.6	41.1	46.9	39.3	44.4
xRFT - MathOctopus^P	44.6	43.4	46.4	34.2	47.7	48.2	49.9	43.1	48.2	39.5	44.5

30 - 34B Model	En	Sw	Zh	Bn	De	Es	Fr	Ja	Ru	Th	Overall
MathOctopus^C	51.5	42.1	46.2	23.2	50.5	52.1	52.9	42.2	50.5	33.4	44.5
xRFT - MathOctopus^C	48.1	42.8	43.6	23.3	48.7	50.0	48.9	43.4	44.6	35.5	42.9
MathOctopus^P	56.4	46.8	52.0	35.2	47.2	53.2	48.0	39.2	45.6	41.2	46.5
xRFT - MathOctopus^P	48.0	42.3	46.1	36.2	47.5	48.5	48.3	45.8	47.2	41.2	45.1

MathOctopus in English

Models	GSM8K	SVAMP
LLaMA 2 - 7B	42.4	38.3
MathOctopus^P - 7B	49.3	46.8
MathOctopus^C - 7B	50.8	49.3
LLaMA 2 - 13B	51.0	50.9
MathOctopus^P - 13B	55.5	52.1
MathOctopus^C - 13B	56.6	56.6
LLaMA 1 - 33B	50.0	49.0
MathOctopus^P - 33B	56.0	52.5
MathOctopus^C - 33B	53.7	51.5

📚 Intended Uses

These models are trained for research purposes. They are designed to solve multilingual math problems. They can be used in educational software, tutoring systems, or any application where a solution to a math problem is needed.

📄 License

The project uses the Apache - 2.0 license.

📚 Citation

Please cite our paper if you use our data, model or code. Please also kindly cite the original dataset papers.

@misc{chen2023breaking,
      title={Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and Observations}, 
      author={Nuo Chen and Zinan Zheng and Ning Wu and Linjun Shou and Ming Gong and Yangqiu Song and Dongmei Zhang and Jia Li},
      year={2023},
      eprint={2310.20246},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

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