Enhance README.md with detailed dataset information and usage guidelines

README.md

@@ -1,10 +1,86 @@
 ---
 license: apache-2.0
-task_categories:
-- feature-extraction
 language:
 - ps
-pretty_name: Pashto
 size_categories:
 - 10K<n<100K
----
+task_categories:
+- text-classification
+- text-generation
+- question-answering
+---
+
+# ZamAI Pashto Dataset (Cleaned)
+
+## Dataset Summary
+
+This repository hosts a cleaned and QC'ed slice of the ZamAI Pashto corpus. The release contains 28,650 Pashto-language articles and prompts that have been deduplicated, normalised, and aligned for instruction-style training as well as prompt/completion workflows.
+
+## Dataset Details
+
+- **Curated by:** ZamAI Team
+- **Language(s):** Pashto (ps)
+- **License:** Apache-2.0
+- **Version:** v1.0 (2025-06-23)
+- **Sources:** BBC Pashto, Radio Azadi, community-contributed Pashto corpora
+- **Processing Pipeline:** [ZamAI Pashto Data Processing Pipeline](https://github.com/ZamAI-Pashto/ZamAI-Pashto-Data-Processing-Pipeline)
+
+## Dataset Structure
+
+- **CSV splits:** `pashto_cleaned_train.csv`, `pashto_cleaned_val.csv`, `pashto_cleaned_full_dataset.csv`
+- **Instruction JSONL:** `pashto_train_instruction.jsonl`, `pashto_val_instruction.jsonl`
+- **Prompt/Completion JSONL:** `pashto_train_prompt_completion.jsonl`, `pashto_val_prompt_completion.jsonl`
+
+### Fields
+
+| Field | Description |
+| --- | --- |
+| `title` | Source headline or generated title |
+| `text` | Cleaned Pashto article body |
+| `source` | Origin of the example (news outlet / pipeline tag) |
+| `prompt` | Instruction-style prompt derived from the article |
+| `completion` | Expected model output/completion |
+| `instruction` | (JSONL) Instruction text for instruction-tuning |
+| `input` | (JSONL) Optional input/context paired with the instruction |
+| `output` | (JSONL) Target response |
+
+### Splits
+
+- `train`: 25,785 examples
+- `validation`: 2,865 examples
+- `full`: 28,650 examples (union of train + validation)
+
+## Accessing the Data
+
+Files are tracked with Git LFS. After cloning, run `git lfs pull` in the repository to download the actual CSV/JSONL payloads.
+
+## Cleaning & Normalisation
+
+1. Dropped rows with empty title/text
+2. Removed duplicate content hashes
+3. Normalised whitespace and Unicode (NFKC)
+4. Filtered samples shorter than 10 characters
+5. Generated aligned prompts, completions, and instruction templates
+
+## Intended Uses
+
+- Fine-tuning Pashto T5/mT5 style models
+- Instruction-tuning chat assistants for Pashto
+- Building evaluation sets for Pashto summarisation and QA
+
+## Limitations
+
+- Dominated by news-domain writing; colloquial data is limited
+- Automatically generated prompts/completions may include occasional artefacts—consider manual review before deployment
+- Despite cleaning, residual duplicated facts may remain due to mirrored reporting across sources
+
+## Citation
+
+```bibtex
+@misc{tasal2025_zamai_pashto_cleaned,
+  title = {ZamAI Pashto Dataset (Cleaned)},
+  author = {Yaqoob Tasal and the ZamAI Team},
+  year = {2025},
+  howpublished = {\url{https://huggingface.co/datasets/tasal9/ZamAI-Pashto-Dataset-Cleaned}}
+}
+```