metadata
language:
- ar
license: llama3
base_model: meta-llama/Llama-3.1-8B
tags:
- arabic
- medical
- question-answering
- fine-tuned
- full
Omaratef3221/llama-3.1-8b-s1-full-s2-lora-medarabench
Base model: meta-llama/Llama-3.1-8B
Training stage: Stage 2 — Task Fine-tuning (MedAraBench)
Stage 1 method: full
Stage 2 method: lora
Paper
LoRA vs. Full Fine-Tuning for Arabic Medical Question Answering: A Systematic Comparison Across General-Purpose and Arabic-Centric Large Language Models
Training data
| Stage | Dataset | Samples |
|---|---|---|
| Stage 1 | AraMed (open-ended Arabic medical QA) | ~110K |
| Stage 2 | MedAraBench (Arabic MCQ) | ~17.6K (cleaned) |
Evaluation
Evaluated on MedAraBench test set (4,959 MCQ samples) using log-probability selection. Metrics: Accuracy and Macro F1 across answer classes A–E.
Experiment metadata
{
"model_name": "meta-llama/Llama-3.1-8B",
"stage1_method": "full",
"stage2_method": "lora",
"stage": "task_specific",
"num_epochs": 3,
"config_path": "/home/oelgendy/arabic-medical-llm/script/configs/lora.yaml",
"stage1_checkpoint": "outputs/exp04_llama_full_lora/stage1",
"train_samples": 16756,
"val_samples": 882
}