EthioNLP
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Amharic_LLAMA_our_data

Text Generation

Amharic

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israel commited on May 30

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 pipeline_tag: text-generation
 ---
-# Model Card for Model ID
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-- PEFT 0.7.2.dev0

 pipeline_tag: text-generation
 ---
+# Walia Instruction Dataset for Amharic
+This repository contains instruction-tuning datasets used in [Walia-LLM](https://aclanthology.org/2024.findings-emnlp.25/), a fine-tuned LLaMA-2 model for the Amharic language. The dataset was carefully constructed by integrating task-specific and generative datasets, and it supports a variety of natural language processing tasks in Amharic.
+## Dataset Summary
+The Walia dataset is designed to enhance large language models for the Amharic language by:
+- Converting existing task-specific datasets (e.g., sentiment analysis, QA, NER) into instruction format.
+- Creating new generative datasets (e.g., poem generation, religious lyrics, story generation).
+- Translating English instruction datasets (e.g., Alpaca, Dolly) into Amharic for comparative studies.
+Each data point follows a structured instruction format with:
+- `"instruction"` – a natural language task description,
+- `"input"` – optional input text for the task,
+- `"output"` – the expected model output in Amharic.
+## Supported Tasks
+| Task                       | Source/Type       | Notes                      |
+|---------------------------|-------------------|----------------------------|
+| Sentiment Analysis        | AfriSenti         | 3-class sentiment          |
+| Named Entity Recognition  | MasakhaNER        | Personal name extraction   |
+| News Classification       | MasakhaNews       | Multilingual topic classes |
+| QA                        | AmharicQA         | Wikipedia-based            |
+| Summarization             | XL-Sum            | Amharic summaries          |
+| Machine Translation       | NLLB, WMT19       | Both directions supported  |
+| Poem/Lyrics/Story Gen     | Custom            | Sourced from web/telegram  |
+| Spelling Correction       | Synthetic         | Character perturbations    |
+## Dataset Structure
+```json
+{
+  "instruction": "Translate the following sentence to Amharic.",
+  "input": "Hello, how are you?",
+  "output": "ሰላም፣ እንዴት ነህ?"
+}
+```
+## Data Statistics
+- ~122,000 instruction samples for training
+- ~15,000 for validation and test
+- 16+ task types and instruction templates
+- All responses are in Amharic (except source text in MT)
+## How to Use
+You can load the dataset using the Hugging Face `datasets` library:
+```python
+from datasets import load_dataset
+dataset = load_dataset("EthioNLP/walia-amharic-instructions")
+print(dataset["train"][0])
+```
+## Applications
+- Supervised fine-tuning (SFT) of LLMs for Amharic
+- Cross-lingual instruction tuning experiments
+- Evaluation of generative capabilities in low-resource languages
+## Related Models
+The dataset is used to fine-tune:
+- [`EthioNLP/walia-llama-2`](https://huggingface.co/EthioNLP/walia-llama-2)
+- Other LLaMA variants for Amharic
+## Citation
+Please cite the following paper if you use this dataset:
+```bibtex
+@inproceedings{azime-etal-2024-walia,
+    title = "Walia-{LLM}: Enhancing {A}mharic-{LL}a{MA} by Integrating Task-Specific and Generative Datasets",
+    author = "Azime, Israel Abebe  and Tonja, Atnafu Lambebo  and Belay, Tadesse Destaw  and Fuge, Mitiku Yohannes  and Wassie, Aman Kassahun  and Jada, Eyasu Shiferaw  and Chanie, Yonas  and Sewunetie, Walelign Tewabe  and Yimam, Seid Muhie",
+    editor = "Al-Onaizan, Yaser  and Bansal, Mohit  and Chen, Yun-Nung",
+    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",
+    month = nov,
+    year = "2024",
+    address = "Miami, Florida, USA",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2024.findings-emnlp.25/",
+    doi = "10.18653/v1/2024.findings-emnlp.25",
+    pages = "432--444"
+}
+```