| ## 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 | |