fix: Add namaa MrTydi reranking dataset (#1573)

* Add dataset class and file requirements

* pass tests

* make lint changes

* adjust meta data and remove load_data

---------

Co-authored-by: Omar Elshehy <omarelshehy@Omars-MacBook-Pro.local>

mteb/tasks/Reranking/__init__.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from .ara.NamaaMrTydiReranking import *
 from .eng.AskUbuntuDupQuestions import *
 from .eng.MindSmallReranking import *
 from .eng.SciDocsReranking import *

mteb/tasks/Reranking/ara/NamaaMrTydiReranking.py

@@ -0,0 +1,39 @@
+from __future__ import annotations
+
+from mteb.abstasks.TaskMetadata import TaskMetadata
+
+from ....abstasks.AbsTaskReranking import AbsTaskReranking
+
+
+class NamaaMrTydiReranking(AbsTaskReranking):
+    metadata = TaskMetadata(
+        name="NamaaMrTydiReranking",
+        description="Mr. TyDi is a multi-lingual benchmark dataset built on TyDi, covering eleven typologically diverse languages. It is designed for monolingual retrieval, specifically to evaluate ranking with learned dense representations. This dataset adapts the arabic test split for Reranking evaluation purposes by the addition of multiple (Hard) Negatives to each query and positive",
+        reference="https://huggingface.co/NAMAA-Space",
+        dataset={
+            "path": "NAMAA-Space/mteb-eval-mrtydi",
+            "revision": "502637220a7ad0ecc5c39ff5518d7508d2624af8",
+        },
+        type="Reranking",
+        category="s2s",
+        modalities=["text"],
+        eval_splits=["test"],
+        eval_langs=["ara-Arab"],
+        main_score="map",
+        date=("2023-11-01", "2024-05-15"),
+        domains=["Encyclopaedic", "Written"],
+        task_subtypes=[],
+        license="cc-by-sa-3.0",
+        annotations_creators="human-annotated",
+        dialect=[],
+        sample_creation="found",
+        bibtex_citation="""@article{muennighoff2022mteb,
+  doi = {10.48550/ARXIV.2210.07316},
+  url = {https://arxiv.org/abs/2210.07316},
+  author = {Muennighoff, Niklas and Tazi, Nouamane and Magne, Lo{\"\i}c and Reimers, Nils},
+  title = {MTEB: Massive Text Embedding Benchmark},
+  publisher = {arXiv},
+  journal={arXiv preprint arXiv:2210.07316},  
+  year = {2022}
+}""",
+    )