Update README.md

README.md

@@ -32,4 +32,59 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- text-ranking
+- text-retrieval
+language:
+- am
+tags:
+- information-retrieval
+- amharic
+size_categories:
+- 10K<n<100K
 ---
+
+
+# Amharic Passage Retrieval Dataset with Negatives
+
+This dataset is a version of [amharic-news-category-classification](https://huggingface.co/datasets/rasyosef/amharic-news-category-classification) that has been filtered, deduplicated, and formatted for passage retrieval.
+
+This dataset can be used directly with Sentence Transformers to train Amharic Text embedding and Reranking models.
+
+#### Hard Negatives:
+The `negative_passages` column contains hard negative passages that were mined using the [roberta-amharic-text-embedding-medium](https://huggingface.co/rasyosef/roberta-amharic-text-embedding-medium) embedding model.
+
+### Source Datasets:
+
+- https://huggingface.co/datasets/rasyosef/amharic-news-category-classification
+
+### Models and Code
+The following Text Embedding and ColBERT late-interaction retrieval models were trained using this dataset as part of our **ACL 2025 Findings** paper: ***Optimized Text Embedding Models and Benchmarks for Amharic Passage Retrieval***.
+
+- Models Collection: https://huggingface.co/collections/rasyosef/amharic-text-embedding-models-679cb55eae1d498e3ac5bdc5
+- Code: https://github.com/kidist-amde/amharic-ir-benchmarks
+- Paper: https://arxiv.org/abs/2505.19356
+
+## Citation
+```
+@inproceedings{mekonnen2025amharic,
+  title={Optimized Text Embedding Models and Benchmarks for Amharic Passage Retrieval},
+  author={Kidist Amde Mekonnen, Yosef Worku Alemneh, Maarten de Rijke },
+  booktitle={Findings of ACL},
+  year={2025}
+}
+```
+
+```
+@misc{https://doi.org/10.48550/arxiv.2103.05639,
+  doi = {10.48550/ARXIV.2103.05639},
+  url = {https://arxiv.org/abs/2103.05639},
+  author = {Azime, Israel Abebe and Mohammed, Nebil},
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  title = {An Amharic News Text classification Dataset},
+  publisher = {arXiv},
+  year = {2021},
+  copyright = {arXiv.org perpetual, non-exclusive license}
+}
+```