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---
license: mit
datasets:
- Slim205/Barka_data_2B
language:
- ar
base_model:
- google/gemma-2-2b-it
---

![Alt text](photo.png)

Welcome to Slim205/Barka-2b-it : The best 2B Arabic LLM. Feel free to use it and give me feedbacks on it. 

# Motivation : 

The goal of the project was to adapt large language models for the Arabic language and create a new state-of-the-art Arabic LLM. Due to the scarcity of Arabic instruction fine-tuning data, not many LLMs have been trained specifically in Arabic, which is surprising given the large number of Arabic speakers.  
Our final model was trained on a high-quality instruction fine-tuning (IFT) dataset, generated synthetically and then evaluated using the Hugging Face Arabic leaderboard.

# Training : 
This model is the 2B version. It was trained for 2 days on 1 A100 GPU using LoRA with a rank of 128, a learning rate of 1e-4, and a cosine learning rate schedule.

# Evaluation :

| Metric               | Slim205/Barka-2b-it |
|----------------------|---------------------|
| Average              | 46.98               |
| ACVA                 | 39.5                |
| AlGhafa              | 46.5                |
| MMLU                 | 37.06               |
| EXAMS                | 38.73               |
| ARC Challenge        | 35.78               |
| ARC Easy             | 36.97               |
| BOOLQ                | 73.77               |
| COPA                 | 50                  |
| HELLAWSWAG           | 28.98               |
| OPENBOOK QA          | 43.84               |
| PIQA                 | 56.36               |
| RACE                 | 36.19               |
| SCIQ                 | 55.78               |
| TOXIGEN              | 78.29               |

Please refer to https://github.com/Slim205/Arabicllm/ for more details.