| ## Dataset Summary |
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| **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. |
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| * **Language(s):** Persian (Farsi) |
| * **Task(s):** Classification (Document Classification, Topic Classification) |
| * **Source:** Collected from SID (sid.ir) |
| * **Part of FaMTEB:** Yes |
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| ## Supported Tasks and Leaderboards |
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| 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). |
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| ## Construction |
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| The dataset was built by: |
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| - 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 |
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| 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. |
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| ## Data Splits |
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| As reported in the *FaMTEB* paper (Table 5): |
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| * **Train:** 8,712 samples |
| * **Development (Dev):** 0 samples |
| * **Test:** 3,735 samples |
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