## Dataset Summary

**SID Classification** is a Persian (Farsi) dataset designed for the **Classification** task, specifically targeting **document classification** of academic articles. It is a component of the [FaMTEB (Farsi Massive Text Embedding Benchmark)](https://huggingface.co/spaces/mteb/leaderboard). The dataset was constructed by collecting academic texts from **SID (Scientific Information Database – sid.ir)**, one of Iran’s major platforms for scientific publications. Each document—formed by concatenating an article’s title and abstract—is labeled with one of 8 predefined scientific disciplines from the SID website.

* **Language(s):** Persian (Farsi)  
* **Task(s):** Classification (Document Classification, Topic Classification)  
* **Source:** Collected from SID (sid.ir)  
* **Part of FaMTEB:** Yes

## Supported Tasks and Leaderboards

This dataset is used to evaluate the performance of text embedding models on the **Classification** task—measuring their ability to assign academic documents to appropriate scientific categories. Results are benchmarked on the **Persian MTEB Leaderboard** on Hugging Face Spaces (filtered by language: Persian).

## Construction

The dataset was built by:

- Crawling the **SID** academic repository (sid.ir)
- Extracting the **title** and **abstract** of each academic article
- Concatenating the title and abstract to form a single input text
- Using the site's predefined 8-category taxonomy to assign a label to each document

This dataset complements the [SID Clustering dataset](https://huggingface.co/datasets/MCINext/sid-clustering), sharing the same underlying texts but serving a **supervised** classification task.

## Data Splits

As reported in the *FaMTEB* paper (Table 5):

* **Train:** 8,712 samples  
* **Development (Dev):** 0 samples  
* **Test:** 3,735 samples