Create README.md

README.md

@@ -0,0 +1,37 @@
+## Dataset Summary
+
+**CQADupstack-webmasters-Fa** is a Persian (Farsi) dataset created for the **Retrieval** task, focusing on identifying **duplicate or semantically similar questions** within community question-answering (CQA) platforms. It is a **translated version** of the *Webmasters StackExchange* data from the English **CQADupstack** dataset and is part of the [FaMTEB (Farsi Massive Text Embedding Benchmark)](https://huggingface.co/spaces/mteb/leaderboard).
+
+* **Language(s):** Persian (Farsi)  
+* **Task(s):** Retrieval (Duplicate Question Retrieval)  
+* **Source:** Translated from CQADupstack-Webmasters (BEIR benchmark) using Google Translate  
+* **Part of FaMTEB:** Yes — as part of the BEIR-Fa collection
+
+## Supported Tasks and Leaderboards
+
+The dataset is designed to test **text embedding models' performance** in retrieving **duplicate or semantically equivalent questions** in a technical domain (SEO, webmastering, site performance). It is benchmarked on the **Persian MTEB Leaderboard** (language: Persian).
+
+## Construction
+
+This dataset was constructed via:
+
+- Extracting data from the **Webmasters** subforum of StackExchange (from the English CQADupstack dataset)
+- Translating the data into Persian using the **Google Translate API**
+- Retaining the original query-relevant pairs for Retrieval evaluation
+
+As discussed in the *FaMTEB* paper, the entire **BEIR-Fa collection** (including this dataset) was evaluated using:
+
+- **BM25 retrieval score comparison**
+- **GEMBA-DA framework** leveraging LLMs to validate translation quality
+
+These assessments indicate good fidelity in Persian translations.
+
+## Data Splits
+
+The full CQADupstack-Fa collection has the following evaluation split:
+
+- **Train:** 0 samples  
+- **Dev:** 0 samples  
+- **Test:** 480,902 samples (across all domains)
+
+The **Webmasters-specific subset** contains approximately **19.3k examples**, though **individual splits are not separately provided** in the FaMTEB paper. For detailed splits, consult the dataset provider or Hugging Face dataset card.