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readme_hindi.md

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+---
+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}
+}
+```

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