---
license: cc-by-2.0
language:
- ar
- en
pipeline_tag: text-generation
tags:
- Infectious Diseases
- AceGPT-7B-Chat
---
# InfectA-Chat
To prevent adversial effects of infectious diseases, clear and accessible communication, tracking infectious diseases regularly is crucial. InfectA-Chat is a generative model specifically designed to address this need. Built upon the powerful AceGPT-7B-Chat pre-trained model, InfectA-Chat is fine-tuned to track infectious diseases outbreaks in the infectious diseases domain. This makes it a valuable tool for facilitating communication in both Arabic and English, potentially bridging language barriers and fostering a deeper understanding of infectious diseases.

# Model Details
In the fight against infectious diseases in the Middle East, clear and effective communication is paramount. We're excited to announce the release of InfectA-Chat, a generative text model fine-tuned on the AceGPT-7B-Chat model. Designed specifically for the Arabic and English languages, InfectA-Chat excels at following instructions related to infectious disease topics. Notably, our models outperform existing Arabic and state-of-the-art LLMs on Q&A task involving infectious disease instructions while competing with GPT-4. This advancement has the potential to significantly improve communication and disease tracking efforts in the specific region.

- **Developed by:** Korea Institute of Science and Technology
- **Language(s) (NLP):** Arabic, English
- **License:** Creative Commons Attribution 2.0
- **Finetuned from model [optional]:** AceGPT-7B-Chat
- **Repository:** KISTI-AI/InfectA-Chat

# Training Details

## Training Data
InfectA-Chat was instruction fine-tuned with 55,400 infectious diseases-related instruction-following data.

## Training Procedure
This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure.

## Training Hyperparameters

- **Training regime:** fp32 <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

# Evaluation

## Evaluation Results on Infectious Diseases-related Instruction-Following Dataset
Experiments on infectious diseases-related instruction-following data and Arabic MMLU benchmark dataset. ‘STEM’, ‘Humanities’, ‘Social Sciences’, ‘Others’ belong to Arabic MMLU.

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6516795fb84fb7bc6cc34fd9/CQnUnZUWNqlJIM2F77mde.png)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6516795fb84fb7bc6cc34fd9/xpVldjeKc3zWIWAMAjPlS.png)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6516795fb84fb7bc6cc34fd9/r32DDr7iqG-6WY21bwfPO.png)

## Evaluation Results on Arabic MMLU Benchmark Dataset

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6516795fb84fb7bc6cc34fd9/ZbNQ83BkyngiSewxXvik_.png)