Create README.md

README.md

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+## Dataset Summary
+
+**MSMARCO-Fa** is a Persian (Farsi) dataset created for the **Retrieval** task, particularly focusing on **web search** and **document ranking**. It is a translated version of the original English **MS MARCO (Microsoft MAchine Reading COmprehension)** dataset and is a key part of the [FaMTEB (Farsi Massive Text Embedding Benchmark)](https://huggingface.co/spaces/mteb/leaderboard), under the **BEIR-Fa** collection.
+
+- **Language(s):** Persian (Farsi)  
+- **Task(s):** Retrieval (Web Search, Document Ranking)  
+- **Source:** Translated from the English MS MARCO dataset  
+- **Part of FaMTEB:** Yes — under BEIR-Fa
+
+## Supported Tasks and Leaderboards
+
+This dataset is used to evaluate the effectiveness of **text embedding models** in **ranking web documents** based on relevance to user queries, simulating real-world search engine applications. Benchmarking is available via the **Persian MTEB Leaderboard** (language: Persian).
+
+## Construction
+
+The dataset was built by:
+
+- **Translating** the original English MS MARCO dataset to Persian using the **Google Translate API**
+- Preserving original relevance annotations, where some passages are **human-judged** as relevant to each query
+
+As described in the *FaMTEB* paper:
+
+- Translation quality was evaluated by **BM25 retrieval score comparison** with the English dataset  
+- Further validation was done using **LLM-based assessments (GEMBA-DA framework)**  
+- This dataset is similar in structure to mMARCO, but focused solely on the **Persian language**
+
+## Data Splits
+
+Based on FaMTEB paper (Table 5):
+
+- **Train:** 9,374,574 samples  
+- **Dev:** 0 samples  
+- **Test:** 8,845,925 samples  
+
+**Total:** ~9.9 million examples