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Readme.md

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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 -- English'
-size_categories:
-  - 10K<n<100K
-dataset_info:
-- config_name: QProp
-  splits:
-    - name: train
-      num_examples: 35986
-    - name: dev
-      num_examples: 5125
-    - name: test
-      num_examples: 10159
-- config_name: Cyberbullying
-  splits:
-    - name: train
-      num_examples: 32551
-    - name: dev
-      num_examples: 4751
-    - name: test
-      num_examples: 9473
-- config_name: clef2024-checkthat-lab
-  splits:
-    - name: train
-      num_examples: 825
-    - name: dev
-      num_examples: 219
-    - name: test
-      num_examples: 484
-- config_name: SemEval23T3-subtask1
-  splits:
-    - name: train
-      num_examples: 302
-    - name: dev
-      num_examples: 130
-    - name: test
-      num_examples: 83
-- config_name: offensive_language_dataset
-  splits:
-    - name: train
-      num_examples: 29216
-    - name: dev
-      num_examples: 3653
-    - name: test
-      num_examples: 3653
-- config_name: xlsum
-  splits:
-    - name: train
-      num_examples: 306493
-    - name: dev
-      num_examples: 11535
-    - name: test
-      num_examples: 11535
-- config_name: claim-detection
-  splits:
-    - name: train
-      num_examples: 23224
-    - name: dev
-      num_examples: 5815
-    - name: test
-      num_examples: 7267
-- config_name: emotion
-  splits:
-    - name: train
-      num_examples: 280551
-    - name: dev
-      num_examples: 41429
-    - name: test
-      num_examples: 82454
-- config_name: Politifact
-  splits:
-    - name: train
-      num_examples: 14799
-    - name: dev
-      num_examples: 2116
-    - name: test
-      num_examples: 4230
-- config_name: News_dataset
-  splits:
-    - name: train
-      num_examples: 28147
-    - name: dev
-      num_examples: 4376
-    - name: test
-      num_examples: 8616
-- config_name: hate-offensive-speech
-  splits:
-    - name: train
-      num_examples: 48944
-    - name: dev
-      num_examples: 2802
-    - name: test
-      num_examples: 2799
-- config_name: CNN_News_Articles_2011-2022
-  splits:
-    - name: train
-      num_examples: 32193
-    - name: dev
-      num_examples: 9663
-    - name: test
-      num_examples: 5682
-- config_name: CT24_checkworthy
-  splits:
-    - name: train
-      num_examples: 22403
-    - name: dev
-      num_examples: 318
-    - name: test
-      num_examples: 1031
-- config_name: News_Category_Dataset
-  splits:
-    - name: train
-      num_examples: 145748
-    - name: dev
-      num_examples: 20899
-    - name: test
-      num_examples: 41740
-- config_name: NewsMTSC-dataset
-  splits:
-    - name: train
-      num_examples: 7739
-    - name: dev
-      num_examples: 320
-    - name: test
-      num_examples: 747
-- config_name: Offensive_Hateful_Dataset_New
-  splits:
-    - name: train
-      num_examples: 42000
-    - name: dev
-      num_examples: 5254
-    - name: test
-      num_examples: 5252
-- config_name: News-Headlines-Dataset-For-Sarcasm-Detection
-  splits:
-    - name: train
-      num_examples: 19965
-    - name: dev
-      num_examples: 2858
-    - name: test
-      num_examples: 5719
-configs:
-- config_name: QProp
-  data_files:
-    - split: test
-      path: QProp/test.json
-    - split: dev
-      path: QProp/dev.json
-    - split: train
-      path: QProp/train.json
-- config_name: Cyberbullying
-  data_files:
-    - split: test
-      path: Cyberbullying/test.json
-    - split: dev
-      path: Cyberbullying/dev.json
-    - split: train
-      path: Cyberbullying/train.json
-- config_name: clef2024-checkthat-lab
-  data_files:
-    - split: test
-      path: clef2024-checkthat-lab/test.json
-    - split: dev
-      path: clef2024-checkthat-lab/dev.json
-    - split: train
-      path: clef2024-checkthat-lab/train.json
-- config_name: SemEval23T3-subtask1
-  data_files:
-    - split: test
-      path: SemEval23T3-subtask1/test.json
-    - split: dev
-      path: SemEval23T3-subtask1/dev.json
-    - split: train
-      path: SemEval23T3-subtask1/train.json
-- config_name: offensive_language_dataset
-  data_files:
-    - split: test
-      path: offensive_language_dataset/test.json
-    - split: dev
-      path: offensive_language_dataset/dev.json
-    - split: train
-      path: offensive_language_dataset/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: claim-detection
-  data_files:
-    - split: test
-      path: claim-detection/test.json
-    - split: dev
-      path: claim-detection/dev.json
-    - split: train
-      path: claim-detection/train.json
-- config_name: emotion
-  data_files:
-    - split: test
-      path: emotion/test.json
-    - split: dev
-      path: emotion/dev.json
-    - split: train
-      path: emotion/train.json
-- config_name: Politifact
-  data_files:
-    - split: test
-      path: Politifact/test.json
-    - split: dev
-      path: Politifact/dev.json
-    - split: train
-      path: Politifact/train.json
-- config_name: News_dataset
-  data_files:
-    - split: test
-      path: News_dataset/test.json
-    - split: dev
-      path: News_dataset/dev.json
-    - split: train
-      path: News_dataset/train.json
-- config_name: hate-offensive-speech
-  data_files:
-    - split: test
-      path: hate-offensive-speech/test.json
-    - split: dev
-      path: hate-offensive-speech/dev.json
-    - split: train
-      path: hate-offensive-speech/train.json
-- config_name: CNN_News_Articles_2011-2022
-  data_files:
-    - split: test
-      path: CNN_News_Articles_2011-2022/test.json
-    - split: dev
-      path: CNN_News_Articles_2011-2022/dev.json
-    - split: train
-      path: CNN_News_Articles_2011-2022/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: News_Category_Dataset
-  data_files:
-    - split: test
-      path: News_Category_Dataset/test.json
-    - split: dev
-      path: News_Category_Dataset/dev.json
-    - split: train
-      path: News_Category_Dataset/train.json
-- config_name: NewsMTSC-dataset
-  data_files:
-    - split: test
-      path: NewsMTSC-dataset/test.json
-    - split: dev
-      path: NewsMTSC-dataset/dev.json
-    - split: train
-      path: NewsMTSC-dataset/train.json
-- config_name: Offensive_Hateful_Dataset_New
-  data_files:
-    - split: test
-      path: Offensive_Hateful_Dataset_New/test.json
-    - split: dev
-      path: Offensive_Hateful_Dataset_New/dev.json
-    - split: train
-      path: Offensive_Hateful_Dataset_New/train.json
-- config_name: News-Headlines-Dataset-For-Sarcasm-Detection
-  data_files:
-    - split: test
-      path: News-Headlines-Dataset-For-Sarcasm-Detection/test.json
-    - split: dev
-      path: News-Headlines-Dataset-For-Sarcasm-Detection/dev.json
-    - split: train
-      path: News-Headlines-Dataset-For-Sarcasm-Detection/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
-
-### English Datasets
-
-| **Task**                  | **Dataset**                  | **# Labels** | **# Train** | **# Test** | **# Dev** |
-|---------------------------|------------------------------|--------------|-------------|------------|-----------|
-| Checkworthiness           | CT24_T1                      | 2            | 22,403      | 1,031      | 318       |
-| Claim                    | claim-detection              | 2            | 23,224      | 7,267      | 5,815     |
-| Cyberbullying             | Cyberbullying                | 6            | 32,551      | 9,473      | 4,751     |
-| Emotion                  | emotion                     | 6            | 280,551     | 82,454     | 41,429    |
-| Factuality               | News_dataset                | 2            | 28,147      | 8,616      | 4,376     |
-| Factuality               | Politifact                  | 6            | 14,799      | 4,230      | 2,116     |
-| News Genre Categorization | CNN_News_Articles_2011-2022 | 6            | 32,193      | 5,682      | 9,663     |
-| News Genre Categorization | News_Category_Dataset       | 42           | 145,748     | 41,740     | 20,899    |
-| News Genre Categorization | SemEval23T3-subtask1        | 3            | 302         | 83         | 130       |
-| Summarization            | xlsum                       | --           | 306,493     | 11,535     | 11,535    |
-| Offensive Language       | Offensive_Hateful_Dataset_New | 2           | 42,000      | 5,252      | 5,254     |
-| Offensive Language       | offensive_language_dataset   | 2            | 29,216      | 3,653      | 3,653     |
-| Offensive/Hate-Speech    | hate-offensive-speech        | 3            | 48,944      | 2,799      | 2,802     |
-| Propaganda               | QProp                        | 2            | 35,986      | 10,159     | 5,125     |
-| Sarcasm                  | News-Headlines-Dataset-For-Sarcasm-Detection | 2 | 19,965 | 5,719 | 2,858 |
-| Sentiment                | NewsMTSC-dataset            | 3            | 7,739       | 747        | 320       |
-| Subjectivity             | clef2024-checkthat-lab       | 2            | 825         | 484        | 219       |
-
-
-## 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": "3fe3eb6a-843e-4a03-b38c-8333c052f4c4",
-    "original_id": "nan",
-    "input": "You know, I saw a movie - \"Crocodile Dundee.\"",
-    "output": "not_checkworthy",
-    "dataset": "CT24_checkworthy",
-    "task": "Checkworthiness",
-    "lang": "en",
-    "instructions": "Analyze the given text and label it as 'checkworthy' if it includes a factual statement that is significant or relevant to verify, or 'not_checkworthy' if it's not worth checking. 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 'checkworthy' if it includes a factual statement that is significant or relevant to verify, or 'not_checkworthy' if it's not worth checking. Return only the label without any explanation, justification or additional text.\ninput: You know, I saw a movie - \"Crocodile Dundee.\"\nlabel: <|eot_id|><|start_header_id|>assistant<|end_header_id|>not_checkworthy<|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}
-}
-```