Transfer dataset from KoseiUemura

README.md

@@ -0,0 +1,632 @@
+---
+annotations_creators:
+- human-annotated
+language:
+- amh
+- arq
+- ary
+- gaz
+- hau
+- ibo
+- kin
+- pcm
+- som
+- swh
+- tir
+- twi
+- xho
+- yor
+- zul
+license: cc-by-4.0
+multilinguality: multilingual
+source_datasets:
+- afrihate/afrihate
+task_categories:
+- text-classification
+task_ids:
+- sentiment-analysis
+- sentiment-scoring
+- sentiment-classification
+- hate-speech-detection
+dataset_info:
+- config_name: amh
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
+  - name: train
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+    num_examples: 3460
+  - name: validation
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+    num_examples: 743
+  - name: test
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+    num_examples: 744
+  download_size: 606981
+  dataset_size: 1102936
+- config_name: arq
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
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+  - name: validation
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+    num_examples: 210
+  - name: test
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+    num_examples: 321
+  download_size: 135225
+  dataset_size: 240886
+- config_name: ary
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
+  - name: train
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+    num_examples: 654
+  - name: test
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+    num_examples: 666
+  download_size: 539429
+  dataset_size: 860349
+- config_name: hau
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
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+    num_examples: 1029
+  - name: test
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+    num_examples: 1049
+  download_size: 531604
+  dataset_size: 800341
+- config_name: ibo
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
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+    num_examples: 626
+  - name: test
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+    num_examples: 668
+  download_size: 277727
+  dataset_size: 451527
+- config_name: kin
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
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+    num_examples: 684
+  - name: test
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+    num_examples: 692
+  download_size: 485541
+  dataset_size: 711142
+- config_name: orm
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
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+  - name: test
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+    num_examples: 759
+  download_size: 643951
+  dataset_size: 970983
+- config_name: pcm
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
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+  - name: test
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+    num_examples: 1394
+  download_size: 895620
+  dataset_size: 1350393
+- config_name: som
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
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+  - name: test
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+    num_examples: 745
+  download_size: 690194
+  dataset_size: 1006414
+- config_name: swa
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
+  - name: train
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+    num_examples: 2778
+  - name: test
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+    num_examples: 2735
+  download_size: 1210099
+  dataset_size: 1912336
+- config_name: tir
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
+  - name: train
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+    num_examples: 759
+  - name: test
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+    num_examples: 765
+  download_size: 606532
+  dataset_size: 1095325
+- config_name: twi
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
+  - name: train
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+    num_examples: 2537
+  - name: validation
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+    num_examples: 629
+  - name: test
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+    num_examples: 690
+  download_size: 265544
+  dataset_size: 376348
+- config_name: xho
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
+  - name: train
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+    num_examples: 2454
+  - name: validation
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+    num_examples: 543
+  - name: test
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+    num_examples: 594
+  download_size: 212117
+  dataset_size: 319755
+- config_name: yor
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
+  - name: train
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+    num_examples: 716
+  - name: test
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+    num_examples: 815
+  download_size: 456300
+  dataset_size: 676284
+- config_name: zul
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype: int64
+  splits:
+  - name: train
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+    num_examples: 2473
+  - name: validation
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+    num_examples: 410
+  - name: test
+    num_bytes: 44828
+    num_examples: 498
+  download_size: 198240
+  dataset_size: 306883
+configs:
+- config_name: amh
+  data_files:
+  - split: train
+    path: amh/train-*
+  - split: validation
+    path: amh/validation-*
+  - split: test
+    path: amh/test-*
+- config_name: arq
+  data_files:
+  - split: train
+    path: arq/train-*
+  - split: validation
+    path: arq/validation-*
+  - split: test
+    path: arq/test-*
+- config_name: ary
+  data_files:
+  - split: train
+    path: ary/train-*
+  - split: validation
+    path: ary/validation-*
+  - split: test
+    path: ary/test-*
+- config_name: hau
+  data_files:
+  - split: train
+    path: hau/train-*
+  - split: validation
+    path: hau/validation-*
+  - split: test
+    path: hau/test-*
+- config_name: ibo
+  data_files:
+  - split: train
+    path: ibo/train-*
+  - split: validation
+    path: ibo/validation-*
+  - split: test
+    path: ibo/test-*
+- config_name: kin
+  data_files:
+  - split: train
+    path: kin/train-*
+  - split: validation
+    path: kin/validation-*
+  - split: test
+    path: kin/test-*
+- config_name: orm
+  data_files:
+  - split: train
+    path: orm/train-*
+  - split: validation
+    path: orm/validation-*
+  - split: test
+    path: orm/test-*
+- config_name: pcm
+  data_files:
+  - split: train
+    path: pcm/train-*
+  - split: validation
+    path: pcm/validation-*
+  - split: test
+    path: pcm/test-*
+- config_name: som
+  data_files:
+  - split: train
+    path: som/train-*
+  - split: validation
+    path: som/validation-*
+  - split: test
+    path: som/test-*
+- config_name: swa
+  data_files:
+  - split: train
+    path: swa/train-*
+  - split: validation
+    path: swa/validation-*
+  - split: test
+    path: swa/test-*
+- config_name: tir
+  data_files:
+  - split: train
+    path: tir/train-*
+  - split: validation
+    path: tir/validation-*
+  - split: test
+    path: tir/test-*
+- config_name: twi
+  data_files:
+  - split: train
+    path: twi/train-*
+  - split: validation
+    path: twi/validation-*
+  - split: test
+    path: twi/test-*
+- config_name: xho
+  data_files:
+  - split: train
+    path: xho/train-*
+  - split: validation
+    path: xho/validation-*
+  - split: test
+    path: xho/test-*
+- config_name: yor
+  data_files:
+  - split: train
+    path: yor/train-*
+  - split: validation
+    path: yor/validation-*
+  - split: test
+    path: yor/test-*
+- config_name: zul
+  data_files:
+  - split: train
+    path: zul/train-*
+  - split: validation
+    path: zul/validation-*
+  - split: test
+    path: zul/test-*
+tags:
+- mteb
+- text
+---
+<!-- adapted from https://github.com/huggingface/huggingface_hub/blob/v0.30.2/src/huggingface_hub/templates/datasetcard_template.md -->
+
+<div align="center" style="padding: 40px 20px; background-color: white; border-radius: 12px; box-shadow: 0 2px 10px rgba(0, 0, 0, 0.05); max-width: 600px; margin: 0 auto;">
+  <h1 style="font-size: 3.5rem; color: #1a1a1a; margin: 0 0 20px 0; letter-spacing: 2px; font-weight: 700;">AfriHateClassification</h1>
+  <div style="font-size: 1.5rem; color: #4a4a4a; margin-bottom: 5px; font-weight: 300;">An <a href="https://github.com/embeddings-benchmark/mteb" style="color: #2c5282; font-weight: 600; text-decoration: none;" onmouseover="this.style.textDecoration='underline'" onmouseout="this.style.textDecoration='none'">MTEB</a> dataset</div>
+  <div style="font-size: 0.9rem; color: #2c5282; margin-top: 10px;">Massive Text Embedding Benchmark</div>
+</div>
+
+AfriHate is a multilingual collection of hate speech and abusive language datasets covering 15 African languages. Each example is a tweet annotated by native speakers with sociocultural understanding of the context and language, addressing the crucial need for localized and community-driven moderation resources.
+
+|               |                                             |
+|---------------|---------------------------------------------|
+| Task category | t2c                              |
+| Domains       | Social, Written                               |
+| Reference     | https://aclanthology.org/2025.naacl-long.92/ |
+
+Source datasets:
+- [afrihate/afrihate](https://huggingface.co/datasets/afrihate/afrihate)
+
+
+## Dataset Preparation in MTEB
+
+This repository is a staging copy of `afrihate/afrihate` for the `AfriHateClassification` task. The intended long-term canonical benchmark copy is `mteb/AfriHateClassification`.
+
+### Transformations
+- Renamed `tweet` to `text`
+- Mapped labels to integers: `Normal -> 0`, `Abuse -> 1`, `Hate -> 2`
+- Applied dataset cleaning before upload to reduce duplicates and train-test leakage in the benchmark copy
+
+### Label Schema
+- `0`: Normal
+- `1`: Abuse
+- `2`: Hate
+
+### Splits and subsets
+The multilingual subset structure from the source dataset is preserved. The uploaded copy contains the cleaned train/eval splits used by MTEB.
+
+## How to evaluate on this task
+
+You can evaluate an embedding model on this dataset using the following code:
+
+```python
+import mteb
+
+task = mteb.get_task("AfriHateClassification")
+evaluator = mteb.MTEB([task])
+
+model = mteb.get_model(YOUR_MODEL)
+evaluator.run(model)
+```
+
+<!-- Datasets want link to arxiv in readme to autolink dataset with paper -->
+To learn more about how to run models on `mteb` task check out the [GitHub repository](https://github.com/embeddings-benchmark/mteb).
+
+## Citation
+
+If you use this dataset, please cite the dataset as well as [mteb](https://github.com/embeddings-benchmark/mteb), as this dataset likely includes additional processing as a part of the [MMTEB Contribution](https://github.com/embeddings-benchmark/mteb/tree/main/docs/mmteb).
+
+```bibtex
+@inproceedings{muhammad-etal-2025-afrihate,
+  address = {Albuquerque, New Mexico},
+  author = {Muhammad, Shamsuddeen Hassan  and
+Abdulmumin, Idris  and
+Ayele, Abinew Ali  and
+Adelani, David Ifeoluwa  and
+Ahmad, Ibrahim Said  and
+Aliyu, Saminu Mohammad  and
+R{\"o}ttger, Paul  and
+Oppong, Abigail  and
+Bukula, Andiswa  and
+Chukwuneke, Chiamaka Ijeoma  and
+Jibril, Ebrahim Chekol  and
+Ismail, Elyas Abdi  and
+Alemneh, Esubalew  and
+Gebremichael, Hagos Tesfahun  and
+Aliyu, Lukman Jibril  and
+Beloucif, Meriem  and
+Hourrane, Oumaima  and
+Mabuya, Rooweither  and
+Osei, Salomey  and
+Rutunda, Samuel  and
+Belay, Tadesse Destaw  and
+Guge, Tadesse Kebede  and
+Asfaw, Tesfa Tegegne  and
+Wanzare, Lilian Diana Awuor  and
+Onyango, Nelson Odhiambo  and
+Yimam, Seid Muhie  and
+Ousidhoum, Nedjma},
+  booktitle = {Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)},
+  editor = {Chiruzzo, Luis  and
+Ritter, Alan  and
+Wang, Lu},
+  isbn = {979-8-89176-189-6},
+  month = apr,
+  pages = {1854--1871},
+  publisher = {Association for Computational Linguistics},
+  title = {{A}fri{H}ate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for {A}frican Languages},
+  url = {https://aclanthology.org/2025.naacl-long.92/},
+  year = {2025},
+}
+
+
+@article{enevoldsen2025mmtebmassivemultilingualtext,
+  title={MMTEB: Massive Multilingual Text Embedding Benchmark},
+  author={Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
+  publisher = {arXiv},
+  journal={arXiv preprint arXiv:2502.13595},
+  year={2025},
+  url={https://arxiv.org/abs/2502.13595},
+  doi = {10.48550/arXiv.2502.13595},
+}
+
+@article{muennighoff2022mteb,
+  author = {Muennighoff, Niklas and Tazi, Nouamane and Magne, Loïc and Reimers, Nils},
+  title = {MTEB: Massive Text Embedding Benchmark},
+  publisher = {arXiv},
+  journal={arXiv preprint arXiv:2210.07316},
+  year = {2022}
+  url = {https://arxiv.org/abs/2210.07316},
+  doi = {10.48550/ARXIV.2210.07316},
+}
+```
+
+# Dataset Statistics
+<details>
+  <summary> Dataset Statistics</summary>
+
+The following code contains the descriptive statistics from the task. These can also be obtained using:
+
+```python
+import mteb
+
+task = mteb.get_task("AfriHateClassification")
+
+desc_stats = task.metadata.descriptive_stats
+```
+
+```json
+{
+    "test": {
+        "num_samples": 14250,
+        "number_texts_intersect_with_train": 1026,
+        "text_statistics": {
+            "total_text_length": 1532087,
+            "min_text_length": 8,
+            "average_text_length": 107.51487719298245,
+            "max_text_length": 617,
+            "unique_texts": 14129
+        },
+        "image_statistics": null,
+        "audio_statistics": null,
+        "label_statistics": {
+            "min_labels_per_text": 1,
+            "average_label_per_text": 1.0,
+            "max_labels_per_text": 1,
+            "unique_labels": 3,
+            "labels": {
+                "2": {
+                    "count": 3017
+                },
+                "0": {
+                    "count": 5699
+                },
+                "1": {
+                    "count": 5534
+                }
+            }
+        }
+    },
+    "train": {
+        "num_samples": 62466,
+        "number_texts_intersect_with_train": null,
+        "text_statistics": {
+            "total_text_length": 6707920,
+            "min_text_length": 4,
+            "average_text_length": 107.38513751480805,
+            "max_text_length": 764,
+            "unique_texts": 60182
+        },
+        "image_statistics": null,
+        "audio_statistics": null,
+        "label_statistics": {
+            "min_labels_per_text": 1,
+            "average_label_per_text": 1.0,
+            "max_labels_per_text": 1,
+            "unique_labels": 3,
+            "labels": {
+                "0": {
+                    "count": 25703
+                },
+                "1": {
+                    "count": 25750
+                },
+                "2": {
+                    "count": 11013
+                }
+            }
+        }
+    }
+}
+```
+
+</details>
+
+---
+*This dataset card was automatically generated using [MTEB](https://github.com/embeddings-benchmark/mteb)*

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