---
license: cc-by-nc-sa-4.0
task_categories:
  - text-classification
language:
  - hi
tags:
  - Social Media
  - News Media
  - Sentiment
  - Stance
  - Emotion
pretty_name: "LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Content -- Hindi"
size_categories:
  - 10K<n<100K
dataset_info:
  - config_name: Sentiment Analysis
    splits:
      - name: train
        num_examples: 10039
      - name: dev
        num_examples: 1258
      - name: test
        num_examples: 1259
  - config_name: MC_Hinglish1
    splits:
      - name: train
        num_examples: 5177
      - name: dev
        num_examples: 2219
      - name: test
        num_examples: 1000
  - config_name: Offensive Speech Detection
    splits:
      - name: train
        num_examples: 2172
      - name: dev
        num_examples: 318
      - name: test
        num_examples: 636
  - config_name: xlsum
    splits:
      - name: train
        num_examples: 70754
      - name: dev
        num_examples: 8847
      - name: test
        num_examples: 8847
  - config_name: Hindi-Hostility-Detection-CONSTRAINT-2021
    splits:
      - name: train
        num_examples: 5718
      - name: dev
        num_examples: 811
      - name: test
        num_examples: 1651
  - config_name: hate-speech-detection
    splits:
      - name: train
        num_examples: 3327
      - name: dev
        num_examples: 476
      - name: test
        num_examples: 951
  - config_name: fake-news
    splits:
      - name: train
        num_examples: 8393
      - name: dev
        num_examples: 1417
      - name: test
        num_examples: 2743
  - config_name: Natural Language Inference
    splits:
      - name: train
        num_examples: 1251
      - name: dev
        num_examples: 537
      - name: test
        num_examples: 447
configs:
  - config_name: Sentiment Analysis
    data_files:
      - split: test
        path: Sentiment Analysis/test.json
      - split: dev
        path: Sentiment Analysis/dev.json
      - split: train
        path: Sentiment Analysis/train.json
  - config_name: MC_Hinglish1
    data_files:
      - split: test
        path: MC_Hinglish1/test.json
      - split: dev
        path: MC_Hinglish1/dev.json
      - split: train
        path: MC_Hinglish1/train.json
  - config_name: Offensive Speech Detection
    data_files:
      - split: test
        path: Offensive Speech Detection/test.json
      - split: dev
        path: Offensive Speech Detection/dev.json
      - split: train
        path: Offensive Speech Detection/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: Hindi-Hostility-Detection-CONSTRAINT-2021
    data_files:
      - split: test
        path: Hindi-Hostility-Detection-CONSTRAINT-2021/test.json
      - split: dev
        path: Hindi-Hostility-Detection-CONSTRAINT-2021/dev.json
      - split: train
        path: Hindi-Hostility-Detection-CONSTRAINT-2021/train.json
  - config_name: hate-speech-detection
    data_files:
      - split: test
        path: hate-speech-detection/test.json
      - split: dev
        path: hate-speech-detection/dev.json
      - split: train
        path: hate-speech-detection/train.json
  - config_name: fake-news
    data_files:
      - split: test
        path: fake-news/test.json
      - split: dev
        path: fake-news/dev.json
      - split: train
        path: fake-news/train.json
  - config_name: Natural Language Inference
    data_files:
      - split: test
        path: Natural Language Inference/test.json
      - split: dev
        path: Natural Language Inference/dev.json
      - split: train
        path: Natural Language Inference/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="https://huggingface.co/datasets/QCRI/LlamaLens-Arabic/resolve/main/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

### Hindi Datasets

| **Task**                   | **Dataset**                               | **# Labels** | **# Train** | **# Test** | **# Dev** |
| -------------------------- | ----------------------------------------- | ------------ | ----------- | ---------- | --------- |
| Cyberbullying              | MC-Hinglish1.0                            | 7            | 7,400       | 1,000      | 2,119     |
| Factuality                 | fake-news                                 | 2            | 8,393       | 2,743      | 1,417     |
| Hate Speech                | hate-speech-detection                     | 2            | 3,327       | 951        | 476       |
| Hate Speech                | Hindi-Hostility-Detection-CONSTRAINT-2021 | 15           | 5,718       | 1,651      | 811       |
| Natural Language Inference | Natural Language Inference                | 2            | 1,251       | 447        | 537       |
| Summarization              | xlsum                                     | --           | 70,754      | 8,847      | 8,847     |
| Offensive Speech           | Offensive Speech Detection                | 3            | 2,172       | 636        | 318       |
| Sentiment                  | Sentiment Analysis                        | 3            | 10,039      | 1,259      | 1,258     |

---

## 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": "2b1878df-5a4f-4f74-bcd8-e38e1c3c7cf6",
        "original_id": null,
        "input": "sub गंदा है पर धंधा है ये . .",
        "output": "neutral",
        "dataset": "Sentiment Analysis",
        "task": "Sentiment",
        "lang": "hi",
        "instruction": "Identify the sentiment in the text and label it as positive, negative, or neutral. Return only the label without any explanation, justification or additional 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}
}
```