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---
license: cc-by-nc-sa-4.0
task_categories:
- text-classification
language:
- ar
tags:
- Social Media
- News Media
- Sentiment
- Stance
- Emotion
pretty_name: 'LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Content -- Arabic'
size_categories:
- 10K<n<100K
dataset_info:
- config_name: SANADAkhbarona-news-categorization
splits:
- name: train
num_examples: 62210
- name: dev
num_examples: 7824
- name: test
num_examples: 7824
- config_name: CT22Harmful
splits:
- name: train
num_examples: 2484
- name: dev
num_examples: 1076
- name: test
num_examples: 1201
- config_name: Mawqif-Arabic-Stance-main
splits:
- name: train
num_examples: 3162
- name: dev
num_examples: 950
- name: test
num_examples: 560
- config_name: CT22Claim
splits:
- name: train
num_examples: 3513
- name: dev
num_examples: 339
- name: test
num_examples: 1248
- config_name: annotated-hatetweets-4-classes
splits:
- name: train
num_examples: 210525
- name: dev
num_examples: 90543
- name: test
num_examples: 100564
- config_name: ar_reviews_100k
splits:
- name: train
num_examples: 69998
- name: dev
num_examples: 10000
- name: test
num_examples: 20000
- config_name: Arafacts
splits:
- name: train
num_examples: 4354
- name: dev
num_examples: 623
- name: test
num_examples: 1245
- config_name: OSACT4SubtaskA
splits:
- name: train
num_examples: 4780
- name: dev
num_examples: 2047
- name: test
num_examples: 1827
- config_name: SANADAlArabiya-news-categorization
splits:
- name: train
num_examples: 56967
- name: dev
num_examples: 7120
- name: test
num_examples: 7123
- config_name: ArPro
splits:
- name: train
num_examples: 6002
- name: dev
num_examples: 672
- name: test
num_examples: 1326
- config_name: xlsum
splits:
- name: train
num_examples: 37425
- name: dev
num_examples: 4689
- name: test
num_examples: 4689
- config_name: ArSarcasm-v2
splits:
- name: train
num_examples: 8749
- name: dev
num_examples: 3761
- name: test
num_examples: 2996
- config_name: COVID19Factuality
splits:
- name: train
num_examples: 3513
- name: dev
num_examples: 339
- name: test
num_examples: 988
- config_name: Emotional-Tone
splits:
- name: train
num_examples: 7024
- name: dev
num_examples: 1005
- name: test
num_examples: 2009
- config_name: ans-claim
splits:
- name: train
num_examples: 3185
- name: dev
num_examples: 906
- name: test
num_examples: 456
- config_name: ArCyc_OFF
splits:
- name: train
num_examples: 3138
- name: dev
num_examples: 450
- name: test
num_examples: 900
- config_name: CT24_checkworthy
splits:
- name: train
num_examples: 7333
- name: dev
num_examples: 1093
- name: test
num_examples: 610
- config_name: stance
splits:
- name: train
num_examples: 2652
- name: dev
num_examples: 755
- name: test
num_examples: 379
- config_name: NewsHeadline
splits:
- name: train
num_examples: 939
- name: dev
num_examples: 160
- name: test
num_examples: 323
- config_name: NewsCredibilityDataset
splits:
- name: train
num_examples: 8671
- name: dev
num_examples: 1426
- name: test
num_examples: 2730
- config_name: UltimateDataset
splits:
- name: train
num_examples: 133036
- name: dev
num_examples: 19269
- name: test
num_examples: 38456
- config_name: ThatiAR
splits:
- name: train
num_examples: 2446
- name: dev
num_examples: 467
- name: test
num_examples: 748
- config_name: ArSAS
splits:
- name: train
num_examples: 13883
- name: dev
num_examples: 1987
- name: test
num_examples: 3976
- config_name: CT22Attentionworthy
splits:
- name: train
num_examples: 2479
- name: dev
num_examples: 1071
- name: test
num_examples: 1186
- config_name: ASND
splits:
- name: train
num_examples: 74496
- name: dev
num_examples: 11136
- name: test
num_examples: 21942
- config_name: OSACT4SubtaskB
splits:
- name: train
num_examples: 4778
- name: dev
num_examples: 2048
- name: test
num_examples: 1827
- config_name: ArCyc_CB
splits:
- name: train
num_examples: 3145
- name: dev
num_examples: 451
- name: test
num_examples: 900
- config_name: SANADAlkhaleej-news-categorization
splits:
- name: train
num_examples: 36391
- name: dev
num_examples: 4550
- name: test
num_examples: 4550
configs:
- config_name: SANADAkhbarona-news-categorization
data_files:
- split: test
path: SANADAkhbarona-news-categorization/test.json
- split: dev
path: SANADAkhbarona-news-categorization/dev.json
- split: train
path: SANADAkhbarona-news-categorization/train.json
- config_name: CT22Harmful
data_files:
- split: test
path: CT22Harmful/test.json
- split: dev
path: CT22Harmful/dev.json
- split: train
path: CT22Harmful/train.json
- config_name: Mawqif-Arabic-Stance-main
data_files:
- split: test
path: Mawqif-Arabic-Stance-main/test.json
- split: dev
path: Mawqif-Arabic-Stance-main/dev.json
- split: train
path: Mawqif-Arabic-Stance-main/train.json
- config_name: CT22Claim
data_files:
- split: test
path: CT22Claim/test.json
- split: dev
path: CT22Claim/dev.json
- split: train
path: CT22Claim/train.json
- config_name: annotated-hatetweets-4-classes
data_files:
- split: test
path: annotated-hatetweets-4-classes/test.json
- split: dev
path: annotated-hatetweets-4-classes/dev.json
- split: train
path: annotated-hatetweets-4-classes/train.json
- config_name: ar_reviews_100k
data_files:
- split: test
path: ar_reviews_100k/test.json
- split: dev
path: ar_reviews_100k/dev.json
- split: train
path: ar_reviews_100k/train.json
- config_name: Arafacts
data_files:
- split: test
path: Arafacts/test.json
- split: dev
path: Arafacts/dev.json
- split: train
path: Arafacts/train.json
- config_name: OSACT4SubtaskA
data_files:
- split: test
path: OSACT4SubtaskA/test.json
- split: dev
path: OSACT4SubtaskA/dev.json
- split: train
path: OSACT4SubtaskA/train.json
- config_name: SANADAlArabiya-news-categorization
data_files:
- split: test
path: SANADAlArabiya-news-categorization/test.json
- split: dev
path: SANADAlArabiya-news-categorization/dev.json
- split: train
path: SANADAlArabiya-news-categorization/train.json
- config_name: ArPro
data_files:
- split: test
path: ArPro/test.json
- split: dev
path: ArPro/dev.json
- split: train
path: ArPro/train.json
- config_name: xlsum
data_files:
- split: test
path: xlsum/test.json
- split: dev
path: xlsum/dev.json
- split: train
path: xlsum/train.json
- config_name: ArSarcasm-v2
data_files:
- split: test
path: ArSarcasm-v2/test.json
- split: dev
path: ArSarcasm-v2/dev.json
- split: train
path: ArSarcasm-v2/train.json
- config_name: COVID19Factuality
data_files:
- split: test
path: COVID19Factuality/test.json
- split: dev
path: COVID19Factuality/dev.json
- split: train
path: COVID19Factuality/train.json
- config_name: Emotional-Tone
data_files:
- split: test
path: Emotional-Tone/test.json
- split: dev
path: Emotional-Tone/dev.json
- split: train
path: Emotional-Tone/train.json
- config_name: ans-claim
data_files:
- split: test
path: ans-claim/test.json
- split: dev
path: ans-claim/dev.json
- split: train
path: ans-claim/train.json
- config_name: ArCyc_OFF
data_files:
- split: test
path: ArCyc_OFF/test.json
- split: dev
path: ArCyc_OFF/dev.json
- split: train
path: ArCyc_OFF/train.json
- config_name: CT24_checkworthy
data_files:
- split: test
path: CT24_checkworthy/test.json
- split: dev
path: CT24_checkworthy/dev.json
- split: train
path: CT24_checkworthy/train.json
- config_name: stance
data_files:
- split: test
path: stance/test.json
- split: dev
path: stance/dev.json
- split: train
path: stance/train.json
- config_name: NewsHeadline
data_files:
- split: test
path: NewsHeadline/test.json
- split: dev
path: NewsHeadline/dev.json
- split: train
path: NewsHeadline/train.json
- config_name: NewsCredibilityDataset
data_files:
- split: test
path: NewsCredibilityDataset/test.json
- split: dev
path: NewsCredibilityDataset/dev.json
- split: train
path: NewsCredibilityDataset/train.json
- config_name: UltimateDataset
data_files:
- split: test
path: UltimateDataset/test.json
- split: dev
path: UltimateDataset/dev.json
- split: train
path: UltimateDataset/train.json
- config_name: ThatiAR
data_files:
- split: test
path: ThatiAR/test.json
- split: dev
path: ThatiAR/dev.json
- split: train
path: ThatiAR/train.json
- config_name: ArSAS
data_files:
- split: test
path: ArSAS/test.json
- split: dev
path: ArSAS/dev.json
- split: train
path: ArSAS/train.json
- config_name: CT22Attentionworthy
data_files:
- split: test
path: CT22Attentionworthy/test.json
- split: dev
path: CT22Attentionworthy/dev.json
- split: train
path: CT22Attentionworthy/train.json
- config_name: ASND
data_files:
- split: test
path: ASND/test.json
- split: dev
path: ASND/dev.json
- split: train
path: ASND/train.json
- config_name: OSACT4SubtaskB
data_files:
- split: test
path: OSACT4SubtaskB/test.json
- split: dev
path: OSACT4SubtaskB/dev.json
- split: train
path: OSACT4SubtaskB/train.json
- config_name: ArCyc_CB
data_files:
- split: test
path: ArCyc_CB/test.json
- split: dev
path: ArCyc_CB/dev.json
- split: train
path: ArCyc_CB/train.json
- config_name: SANADAlkhaleej-news-categorization
data_files:
- split: test
path: SANADAlkhaleej-news-categorization/test.json
- split: dev
path: SANADAlkhaleej-news-categorization/dev.json
- split: train
path: SANADAlkhaleej-news-categorization/train.json
---
# LlamaLens: Specialized Multilingual LLM Dataset
## Overview
LlamaLens is a specialized multilingual LLM designed for analyzing news and social media content. It focuses on 19 NLP tasks, leveraging 52 datasets across Arabic, English, and Hindi.
<p align="center"> <img src="./capablities_tasks_datasets.png" style="width: 40%;" id="title-icon"> </p>
## LlamaLens
This repo includes scripts needed to run our full pipeline, including data preprocessing and sampling, instruction dataset creation, model fine-tuning, inference and evaluation.
### Features
- Multilingual support (Arabic, English, Hindi)
- 19 NLP tasks with 52 datasets
- Optimized for news and social media content analysis
## 📂 Dataset Overview
### Arabic Datasets
| **Task** | **Dataset** | **# Labels** | **# Train** | **# Test** | **# Dev** |
|---------------------------|------------------------------|--------------|-------------|------------|-----------|
| Attentionworthiness | CT22Attentionworthy | 9 | 2,470 | 1,186 | 1,071 |
| Checkworthiness | CT24_T1 | 2 | 22,403 | 500 | 1,093 |
| Claim | CT22Claim | 2 | 3,513 | 1,248 | 339 |
| Cyberbullying | ArCyc_CB | 2 | 3,145 | 900 | 451 |
| Emotion | Emotional-Tone | 8 | 7,024 | 2,009 | 1,005 |
| Emotion | NewsHeadline | 7 | 939 | 323 | 160 |
| Factuality | Arafacts | 5 | 4,354 | 1,245 | 623 |
| Factuality | COVID19Factuality | 2 | 3,513 | 988 | 339 |
| Harmful | CT22Harmful | 2 | 2,484 | 1,201 | 1,076 |
| Hate Speech | annotated-hatetweets-4-classes | 4 | 210,526 | 100,565 | 90,544 |
| Hate Speech | OSACT4SubtaskB | 2 | 4,778 | 1,827 | 2,048 |
| News Genre Categorization | ASND | 10 | 74,496 | 21,942 | 11,136 |
| News Genre Categorization | SANADAkhbarona | 7 | 62,210 | 7,824 | 7,824 |
| News Genre Categorization | SANADAlArabiya | 6 | 56,967 | 7,123 | 7,120 |
| News Genre Categorization | SANADAlkhaleej | 7 | 36,391 | 4,550 | 4,550 |
| News Genre Categorization | UltimateDataset | 10 | 133,036 | 38,456 | 19,269 |
| News Credibility | NewsCredibilityDataset | 2 | 8,671 | 2,730 | 1,426 |
| Summarization | xlsum | -- | 37,425 | 4,689 | 4,689 |
| Offensive Language | ArCyc_OFF | 2 | 3,138 | 900 | 450 |
| Offensive Language | OSACT4SubtaskA | 2 | 4,780 | 1,827 | 2,047 |
| Propaganda | ArPro | 2 | 6,002 | 1,326 | 672 |
| Sarcasm | ArSarcasm-v2 | 2 | 8,749 | 2,996 | 3,761 |
| Sentiment | ar_reviews_100k | 3 | 69,998 | 20,000 | 10,000 |
| Sentiment | ArSAS | 4 | 13,883 | 3,976 | 1,987 |
| Stance | Mawqif-Arabic-Stance-main | 2 | 3,162 | 560 | 950 |
| Stance | stance | 3 | 2,652 | 379 | 755 |
| Subjectivity | ThatiAR | 2 | 2,446 | 748 | 467 |
## File Format
Each JSONL file in the dataset follows a structured format with the following fields:
- `id`: Unique identifier for each data entry.
- `original_id`: Identifier from the original dataset, if available.
- `input`: The original text that needs to be analyzed.
- `output`: The label assigned to the text after analysis.
- `dataset`: Name of the dataset the entry belongs.
- `task`: The specific task type.
- `lang`: The language of the input text.
- `instructions`: A brief set of instructions describing how the text should be labeled.
- `text`: A formatted structure including instructions and response for the task in a conversation format between the system, user, and assistant, showing the decision process.
**Example entry in JSONL file:**
```
{
"id": "d1662e29-11cf-45cb-bf89-fa5cd993bc78",
"original_id": "nan",
"input": "الدفاع الجوي السوري يتصدى لهجوم صاروخي على قاعدة جوية في حمص",
"output": "not_claim",
"dataset": "ans-claim",
"task": "Claim detection",
"lang": "ar",
"instructions": "Analyze the given text and label it as 'claim' if it includes a factual statement that can be verified, or 'not_claim' if it's not a checkable assertion. Return only the label without any explanation, justification or additional text.",
"text": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are a social media expert providing accurate analysis and insights.<|eot_id|><|start_header_id|>user<|end_header_id|>Analyze the given text and label it as 'claim' if it includes a factual statement that can be verified, or 'not_claim' if it's not a checkable assertion. Return only the label without any explanation, justification or additional text.\ninput: الدفاع الجوي السوري يتصدى لهجوم صاروخي على قاعدة جوية في حمص\nlabel: <|eot_id|><|start_header_id|>assistant<|end_header_id|>not_claim<|eot_id|><|end_of_text|>"
}
```
## 📢 Citation
If you use this dataset, please cite our [paper](https://arxiv.org/pdf/2410.15308):
```
@article{kmainasi2024llamalensspecializedmultilingualllm,
title={LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Content},
author={Mohamed Bayan Kmainasi and Ali Ezzat Shahroor and Maram Hasanain and Sahinur Rahman Laskar and Naeemul Hassan and Firoj Alam},
year={2024},
journal={arXiv preprint arXiv:2410.15308},
volume={},
number={},
pages={},
url={https://arxiv.org/abs/2410.15308},
eprint={2410.15308},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
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