Update README.md

README.md

@@ -1,3 +1,114 @@
----
-license: cc-by-nc-4.0
----
+---
+license: cc-by-nc-4.0
+task_categories:
+  - question-answering
+language:
+  - en
+tags:
+  - finance
+  - indian-finance
+  - benchmark
+  - financial-qa
+  - llm-evaluation
+pretty_name: IndFin-Bench
+size_categories:
+  - n<1K
+---
+
+# IndFin-Bench: A Benchmark Grounded in Indian Financial Filings
+
+**IndFin-Bench** is a benchmark of 100 hand-curated questions sourced from the corporate filings of Indian listed companies. It is designed to evaluate how accurately LLMs can retrieve and reason over India-specific financial data.
+
+Existing financial benchmarks like [FinBen](https://github.com/The-FinAI/PIXIU) and [FinQA](https://github.com/czyssrs/FinQA) are built on US market data — SEC filings, 10-K reports, and earnings calls from American corporations. **IndFin-Bench fills this gap for the Indian market**, covering the Ind AS accounting landscape, SEBI disclosure formats, and cross-company reasoning over BSE/NSE-listed equities.
+
+---
+
+## Dataset Summary
+
+| | |
+|---|---|
+| **Questions** | 100 |
+| **Companies** | 100+ Indian listed firms |
+| **Coverage** | FY23 - FY26 |
+| **Source** | Annual reports, quarterly filings, investor presentations, BSE/NSE disclosures |
+| **License** | CC-BY-NC 4.0 (with additional restrictions; see below) |
+
+---
+
+## Schema
+
+| Field | Description |
+|---|---|
+| `Question_Num` | Unique identifier for the question |
+| `Question` | Natural-language financial query grounded in official filings |
+| `Complexity_Category` | 4-tier taxonomy from single-company single-fact to multi-company multi-fact |
+| `Atomic_Fact` | Verified ground truth answer, sourced directly from official filings |
+
+---
+
+## Complexity Levels
+
+| Category | Questions | What it tests |
+|---|---|---|
+| Single-Company, Single Fact | 38 | Retrieve one specific figure from one company's filing |
+| Single-Company, Multiple Facts | 33 | Retrieve and synthesise multiple data points from a single company |
+| Multi-Company, Multiple Facts | 20 | Compare or derive metrics across multiple companies |
+| Multi-Company, Single Fact | 9 | Retrieve comparable figures across companies and perform comparison |
+
+---
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("CompoundingAI/IndFin-Bench")
+```
+---
+
+## Ground Truth
+
+Each question has a corresponding **Atomic Fact** — a precise, minimal statement of the correct answer derived directly from official company filings. Every atomic fact has been manually verified against primary filings.
+
+## Intended Use & Restrictions
+
+This dataset is released under the **Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0)** license.
+
+**IndFin-Bench is strictly intended for evaluation and benchmarking of language models on Indian financial data.**
+
+Typical allowed use cases include:
+- Evaluating LLM performance on financial question answering
+- Benchmarking retrieval-augmented generation (RAG) systems
+- Comparing model accuracy across different complexity tiers
+
+**Use of this dataset implies agreement with the following restrictions:**
+
+- The dataset **must not be used for training, fine-tuning, or improving** any machine learning or AI models.
+- This includes (but is not limited to):
+  - Supervised training  
+  - Fine-tuning or instruction tuning  
+  - Reinforcement learning (RL / RLHF)  
+  - Retrieval-augmented training pipelines  
+  - Synthetic data generation derived from this dataset  
+
+- The dataset must be used **only for evaluation purposes and not as a training corpus**.
+
+---
+## Citation
+
+If you use IndFin-Bench in your work, please cite:
+
+```
+@dataset{compoundingai2026indfinbench,
+  title={IndFin-Bench: A Pioneering Benchmark Grounded in Indian Financial Filings},
+  author={CompoundingAI},
+  year={2026},
+  url={https://huggingface.co/datasets/CompoundingAI/IndFin-Bench},
+  license={CC-BY-NC-4.0}
+}
+```
+
+## Links
+
+- [Blog Post](https://compoundingai.in/blog/indfin-bench)
+- [CompoundingAI](https://compoundingai.in)