Add paper link and Github link

README.md

@@ -1,601 +1,503 @@
 ---
+language:
+- ar
 license: cc-by-nc-sa-4.0
+size_categories:
+- 10K<n<100K
 task_categories:
-  - text-classification
-language:
-  - ar
-tags:
-  - Social Media
-  - News Media
-  - Sentiment
-  - Stance
-  - Emotion
+- text-classification
 pretty_name: 'LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Content -- Arabic'
-size_categories:
-  - 10K<n<100K
+tags:
+- Social Media
+- News Media
+- Sentiment
+- Stance
+- Emotion
 dataset_info:
 - config_name: SANADAkhbarona-news-categorization
   splits:
-    - name: train
-      num_examples: 62210
-    - name: dev
-      num_examples: 7824
-    - name: test
-      num_examples: 7824
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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
+  - 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 18 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)
-- 18 NLP tasks with 52 datasets
-- Optimized for news and social media content analysis
-
-## 📂 Dataset Overview
+# LlamaLens: Specialized Multilingual LLM Dataset for Analyzing News and Social Media Content
 
-### Arabic Datasets
+This dataset was used in the paper [LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Content](https://huggingface.co/papers/2410.15308).  It contains 52 datasets across Arabic, English, and Hindi, covering 18 NLP tasks related to news and social media analysis.  The tasks include sentiment analysis, stance detection, hate speech detection, and more.
 
-| **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       |
+**Key Features:**
 
+* **Multilingual:**  Arabic, English, and Hindi.
+* **Diverse Tasks:**  Sentiment analysis, stance detection, hate speech detection, news categorization, and more.
+* **Large Scale:**  Contains over 1 million examples across all datasets.
 
-## Results
+**Data Format:**  Each dataset is provided as a JSONL file.  Details on the schema are available in the original paper.
 
-Below, we present  the performance of **L-Lens: LlamaLens** , where *"Eng"* refers to the English-instructed model and *"Native"* refers to the model trained with native language instructions. The results are compared against the SOTA (where available) and the Base: **Llama-Instruct 3.1 baseline**. The **Δ** (Delta) column indicates the difference between LlamaLens and the SOTA performance, calculated as (LlamaLens – SOTA).
+**Code:** [LlamaLens Github Repository](https://github.com/firojalam/LlamaLens)
 
+**Model:** [LlamaLens on Hugging Face](https://huggingface.co/QCRI/LlamaLens)
 
 ---
 
-|              **Task**              |                  **Dataset**                 | **Metric** | **SOTA** | **Base** | **L-Lens-Eng** | **L-Lens-Native** | **Δ (L-Lens (Eng) - SOTA)** |
-|:----------------------------------:|:--------------------------------------------:|:----------:|:--------:|:---------------------:|:---------------------:|:--------------------:|:------------------------:|
-|    Attentionworthiness Detection   |              CT22Attentionworthy             |    W-F1    |   0.412  |         0.158         |         0.425         |         0.454        |           0.013          |
-|      Checkworthiness Detection     |               CT24_checkworthy               |   F1_Pos   |   0.569  |         0.610         |         0.502         |         0.509        |          -0.067          |
-|           Claim Detection          |                   CT22Claim                  |     Acc    |   0.703  |         0.581         |         0.734         |         0.756        |           0.031          |
-|       Cyberbullying Detection      |                   ArCyc_CB                   |     Acc    |   0.863  |         0.766         |         0.870         |         0.833        |           0.007          |
-|          Emotion Detection         |                Emotional-Tone                |    W-F1    |   0.658  |         0.358         |         0.705         |         0.736        |           0.047          |
-|          Emotion Detection         |                 NewsHeadline                 |     Acc    |   1.000  |         0.406         |         0.480         |         0.458        |          -0.520          |
-|             Factuality             |                   Arafacts                   |    Mi-F1   |   0.850  |         0.210         |         0.771         |         0.738        |          -0.079          |
-|             Factuality             |               COVID19Factuality              |    W-F1    |   0.831  |         0.492         |         0.800         |         0.840        |          -0.031          |
-|        Harmfulness Detection       |                  CT22Harmful                 |   F1_Pos   |   0.557  |         0.507         |         0.523         |         0.535        |          -0.034          |
-|        Hate Speech Detection       |        annotated-hatetweets-4-classes        |    W-F1    |   0.630  |         0.257         |         0.526         |         0.517        |          -0.104          |
-|        Hate Speech Detection       |                OSACT4SubtaskB                |    Mi-F1   |   0.950  |         0.819         |         0.955         |         0.955        |           0.005          |
-|         News Categorization        |                     ASND                     |    Ma-F1   |   0.770  |         0.587         |         0.919         |         0.929        |           0.149          |
-|         News Categorization        |      SANADAkhbarona-news-categorization      |     Acc    |   0.940  |         0.784         |         0.954         |         0.953        |           0.014          |
-|         News Categorization        |      SANADAlArabiya-news-categorization      |     Acc    |   0.974  |         0.893         |         0.987         |         0.985        |           0.013          |
-|         News Categorization        |      SANADAlkhaleej-news-categorization      |     Acc    |   0.986  |         0.865         |         0.984         |         0.982        |          -0.002          |
-|         News Categorization        |                UltimateDataset               |    Ma-F1   |   0.970  |         0.376         |         0.865         |         0.880        |          -0.105          |
-|          News Credibility          |            NewsCredibilityDataset            |     Acc    |   0.899  |         0.455         |         0.935         |         0.933        |           0.036          |
-|         News Summarization         |                     xlsum                    |     R-2    |   0.137  |         0.034         |         0.129         |         0.130        |          -0.009          |
-|    Offensive Language Detection    |                   ArCyc_OFF                  |    Ma-F1   |   0.878  |         0.489         |         0.877         |         0.879        |          -0.001          |
-|    Offensive Language Detection    |                OSACT4SubtaskA                |    Ma-F1   |   0.905  |         0.782         |         0.896         |         0.882        |          -0.009          |
-|        Propaganda Detection        |                     ArPro                    |    Mi-F1   |   0.767  |         0.597         |         0.747         |         0.731        |          -0.020          |
-|          Sarcasm Detection         |                 ArSarcasm-v2                 |   F1_Pos   |   0.584  |         0.477         |         0.520         |         0.542        |          -0.064          |
-|      Sentiment Classification      |                ar_reviews_100k               |   F1_Pos   |    --    |         0.681         |         0.785         |         0.779        |            --            |
-|      Sentiment Classification      |                     ArSAS                    |     Acc    |   0.920  |         0.603         |         0.800         |         0.804        |          -0.120          |
-|          Stance Detection          |                    stance                    |    Ma-F1   |   0.767  |         0.608         |         0.926         |         0.881        |           0.159          |
-|          Stance Detection          |           Mawqif-Arabic-Stance-main          |    Ma-F1   |   0.789  |         0.764         |         0.853         |         0.826        |           0.065          |
-|       Subjectivity Detection       |                    ThatiAR                   |   f1_pos   |   0.800  |         0.562         |         0.441         |         0.383        |          -0.359          |
+**(Dataset Statistics -  A subset is shown below for brevity;  see the metadata for the complete list)**
 
----
-
-## File Format
-
-Each JSONL file in the dataset follows a structured format with the following fields:
+| Task                     | Dataset                     | # Labels | # Train | # Test | # Dev |
+|--------------------------|-----------------------------|----------|---------|--------|-------|
+| News Genre Categorization | SANADAkhbarona-news-categorization | 7        | 62210   | 7824   | 7824  |
+| Hate Speech              | annotated-hatetweets-4-classes | 4        | 210525  | 100564 | 90543 |
+| Sentiment                | ar_reviews_100k              | 3        | 69998   | 20000  | 10000 |
+| ...                      | ...                          | ...      | ...     | ...    | ...   |
 
-- `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.
 
+---
 
-**Example entry in JSONL file:**
-
-```
-{
-    "id": "c64503bb-9253-4f58-aef8-9b244c088b15",
-    "original_id": "1,722,643,241,323,950,300",
-    "input": "يريدون توريط السلطة الفلسطينية في الضفة ودق آخر مسمار في نعش ما تبقى من هويتنا الفلسطينية، كما تم توريط غزة. يريدون إعلان كفاح مسلح من طرف الأجهزة الأمنية الفلسطينية علناً! لكن ما يعلمونه وما يرونه ولا يريدون التحدث به، أن أبناء الأجهزة الأمنية في النهار يكونون عسكريين... https://t.co/qF2Fjh24hV https://t.co/1UicLkDd52",
-    "output": "checkworthy",
-    "dataset": "Checkworthiness",
-    "task": "Checkworthiness",
-    "lang": "ar",
-    "instructions": "Identify if the given factual claim is 'checkworthy' or 'not-checkworthy'. Return only the label without any explanation, justification, or additional text."
-}
-
-
-```
-## Model  
-[**LlamaLens on Hugging Face**](https://huggingface.co/QCRI/LlamaLens)  
-
-## Replication Scripts  
-[**LlamaLens GitHub Repository**](https://github.com/firojalam/LlamaLens)
-
-## 📢 Citation
-
-If you use this dataset, please cite our [paper](https://arxiv.org/pdf/2410.15308):
+**Citation:**
 
-```
+```bibtex
 @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},
@@ -609,4 +511,4 @@ If you use this dataset, please cite our [paper](https://arxiv.org/pdf/2410.1530
   archivePrefix={arXiv},
   primaryClass={cs.CL}
 }
-```
+```