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README.md

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+---
+license: apache-2.0
+language:
+- ar
+base_model: Qwen/Qwen2.5-7B-Instruct
+datasets:
+- HassanB4/sawb-arabic-hallucination-dataset
+tags:
+- text-generation
+- arabic
+- hallucination-detection
+- cultural-hallucination
+- lora
+- sft
+- peft
+- icaire
+pipeline_tag: text-generation
+library_name: peft
+---
+
+# Sawb — Qwen2.5-7B-Instruct (LoRA SFT)
+
+## Overview
+
+**Sawb — Qwen2.5-7B-Instruct (LoRA SFT)** is an Arabic-language generative model for detecting and *explaining* cultural hallucinations in LLM outputs. A cultural hallucination occurs when an LLM produces a response that is factually or culturally incorrect within Arab/Islamic contexts.
+
+This model is a LoRA adapter fine-tuned from [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) (7B parameters) using supervised fine-tuning (SFT) on the [Sawb Arabic Cultural Hallucination Dataset](https://huggingface.co/datasets/HassanB4/sawb-arabic-hallucination-dataset).
+
+Qwen2.5-7B-Instruct fine-tuned with LoRA for Arabic cultural hallucination detection and explanation. Produces structured JSON output with hallucination label, category, and Arabic explanation.
+
+## Model Architecture
+
+| Property | Value |
+|---|---|
+| Base model | `Qwen/Qwen2.5-7B-Instruct` |
+| Fine-tuning method | LoRA (Low-Rank Adaptation) |
+| LoRA rank (r) | 8 |
+| LoRA alpha (α) | 8 |
+| LoRA dropout | 0.05 |
+| Target modules | `q_proj`, `k_proj`, `v_proj`, `o_proj`, `gate_proj`, `up_proj`, `down_proj` |
+| Task type | `CAUSAL_LM` |
+| Parameters (base) | 7B |
+
+## Training
+
+| Hyperparameter | Value |
+|---|---|
+| Training examples | 1,828 |
+| Method | Supervised Fine-Tuning (SFT) |
+| Framework | PEFT 0.19.1 + TRL 0.24.0 |
+| Transformers version | 5.5.0 |
+| PyTorch | 2.4.1+cu124 |
+
+## Output Format
+
+The model is trained to produce structured JSON output:
+
+```json
+{
+  "is_hallucination": true,
+  "category": "dialectal_confusion",
+  "explanation_ar": "النموذج أجاب بالفصحى بينما طُلب منه اللهجة النجدية، وهذا يمثّل ارتباكاً لهجياً واضحاً.",
+  "confidence": 0.9
+}
+```
+
+## Usage
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+base_model = "Qwen/Qwen2.5-7B-Instruct"
+adapter = "HassanB4/sawb-qwen25"
+
+tokenizer = AutoTokenizer.from_pretrained(base_model)
+model = AutoModelForCausalLM.from_pretrained(base_model, torch_dtype="auto", device_map="auto")
+model = PeftModel.from_pretrained(model, adapter)
+
+system_prompt = (
+    "أنت نظام متخصص في اكتشاف الهلوسة الثقافية في مخرجات نماذج اللغة العربية. "
+    "مهمتك: تحليل زوج (سؤال، إجابة) وتحديد ما إذا كانت الإجابة تحتوي على هلوسة ثقافية. "
+    "أخرج إجابتك بتنسيق JSON فقط."
+)
+
+question = "اشرح مفهوم النموذج اللغوي باللهجة النجدية"
+answer = "النموذج اللغوي هو نظام يستخدم الذكاء الاصطناعي لفهم اللغة..."
+
+user_msg = f"السؤال: {question}\n\nإجابة النموذج: {answer}"
+
+messages = [
+    {"role": "system", "content": system_prompt},
+    {"role": "user", "content": user_msg},
+]
+
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device)
+outputs = model.generate(inputs, max_new_tokens=256, temperature=0.1, do_sample=True)
+response = tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True)
+print(response)
+```
+
+## Dataset
+
+Trained on [HassanB4/sawb-arabic-hallucination-dataset](https://huggingface.co/datasets/HassanB4/sawb-arabic-hallucination-dataset).
+
+The dataset covers 6 hallucination categories:
+- `ethical_framework_mismatch`
+- `religious_misrepresentation`
+- `historical_inaccuracy`
+- `social_norms_violation`
+- `dialectal_confusion`
+- `regional_context_errors`
+
+## Collection
+
+Part of the [Sawb Arabic Cultural Hallucination Detection](https://huggingface.co/collections/HassanB4/sawb-arabic-cultural-hallucination-detection) collection.

adapter_config.json

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+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen2.5-7B-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 8,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj",
+    "up_proj",
+    "o_proj",
+    "down_proj",
+    "k_proj",
+    "gate_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+oid sha256:91a752a8163be2fc1b4de6b02b5bfb03451ba94c60df799eb74437f6f0fade61
+size 80792096