added details for downloading the dev and test sets

README.md

@@ -33,8 +33,14 @@ dataset_info:
   - name: train
     num_bytes: 2551273
     num_examples: 10070
-  download_size: 2490852
-  dataset_size: 2551273
+    download_size: 2490852
+  - name: dev
+    num_examples: 3397
+    download_size: 849789
+  - name: test
+    num_examples: 6633
+    download_size: 1865593
+
 ---
 
 # Dataset Card for MENYO-20k
@@ -66,8 +72,8 @@ dataset_info:
 ## Dataset Description
 
 - **Homepage:** [Homepage for Menyo-20k](https://zenodo.org/record/4297448#.X81G7s0zZPY)
-- **Repository:**[Github Repo](https://github.com/dadelani/menyo-20k_MT)
-- **Paper:**
+- **Repository:**[Github Repo](https://github.com/uds-lsv/menyo-20k_MT/)
+- **Paper:** [African NLP 2021](https://www.lsv.uni-saarland.de/wp-content/uploads/2022/06/africanlp2021_EACL_menyo20k.pdf)
 - **Leaderboard:**
 - **Point of Contact:**
 
@@ -90,7 +96,7 @@ Languages are English and YOruba
 The data consists of tab seperated entries
 
 ```
-{'translation': 
+{'translation':
   {'en': 'Unit 1: What is Creative Commons?',
   'yo': 'Ìdá 1: Kín ni Creative Commons?'
   }
@@ -106,7 +112,7 @@ The data consists of tab seperated entries
 
 ### Data Splits
 
-Only training dataset available
+Training, Validation and Test datasets are available.
 
 ## Dataset Creation
 
@@ -171,7 +177,7 @@ The dataset is open but for non-commercial use because some of the data sources
                   Adesina Ayeni and
                   Mofe Adeyemi and
                   Ayodele Awokoya},
-  title        = {{MENYO-20k: A Multi-domain English - Yorùbá Corpus 
+  title        = {{MENYO-20k: A Multi-domain English - Yorùbá Corpus
                    for Machine Translation}},
   month        = nov,
   year         = 2020,
@@ -183,4 +189,4 @@ The dataset is open but for non-commercial use because some of the data sources
 ```
 ### Contributions
 
-Thanks to [@yvonnegitau](https://github.com/yvonnegitau) for adding this dataset.
+Thanks to [@yvonnegitau](https://github.com/yvonnegitau) for adding this dataset.

dataset_infos.json

@@ -1 +1 @@
-{"menyo20k_mt": {"description": "MENYO-20k is a multi-domain parallel dataset with texts obtained from news articles, ted talks, movie transcripts, radio transcripts, science and technology texts, and other short articles curated from the web and professional translators. The dataset has 20,100 parallel sentences split into 10,070 training sentences, 3,397 development sentences, and 6,633 test sentences (3,419 multi-domain, 1,714 news domain, and 1,500 ted talks speech transcript domain). The development and test sets are available upon request.\n", "citation": "@dataset{david_ifeoluwa_adelani_2020_4297448,\n  author       = {David Ifeoluwa Adelani and\n                  Jesujoba O. Alabi and\n                  Damilola Adebonojo and\n                  Adesina Ayeni and\n                  Mofe Adeyemi and\n                  Ayodele Awokoya},\n  title        = {MENYO-20k: A Multi-domain English - Yor\u00f9b\u00e1 Corpus\n                  for Machine Translation},\n  month        = nov,\n  year         = 2020,\n  publisher    = {Zenodo},\n  version      = {1.0},\n  doi          = {10.5281/zenodo.4297448},\n  url          = {https://doi.org/10.5281/zenodo.4297448}\n}\n", "homepage": "https://zenodo.org/record/4297448#.X81G7s0zZPY", "license": "For non-commercial use because some of the data sources like Ted talks and JW news requires permission for commercial use.", "features": {"translation": {"languages": ["en", "yo"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "menyo20k_mt", "config_name": "menyo20k_mt", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2551273, "num_examples": 10070, "dataset_name": "menyo20k_mt"}}, "download_checksums": {"https://raw.githubusercontent.com/uds-lsv/menyo-20k_MT/master/data/train.tsv": {"num_bytes": 2490852, "checksum": "3c152119d4dc1fba12ee9424f1e7fd11648acfa8e2ea7f6464a37a18e69d9a06"}}, "download_size": 2490852, "post_processing_size": null, "dataset_size": 2551273, "size_in_bytes": 5042125}}
+{"menyo20k_mt": {"description": "MENYO-20k is a multi-domain parallel dataset with texts obtained from news articles, ted talks, movie transcripts, radio transcripts, science and technology texts, and other short articles curated from the web and professional translators. The dataset has 20,100 parallel sentences split into 10,070 training sentences, 3,397 development sentences, and 6,633 test sentences (3,419 multi-domain, 1,714 news domain, and 1,500 ted talks speech transcript domain). The development and test sets are available upon request.\n", "citation": "@dataset{david_ifeoluwa_adelani_2020_4297448,\n  author       = {David Ifeoluwa Adelani and\n                  Jesujoba O. Alabi and\n                  Damilola Adebonojo and\n                  Adesina Ayeni and\n                  Mofe Adeyemi and\n                  Ayodele Awokoya},\n  title        = {MENYO-20k: A Multi-domain English - Yor\u00f9b\u00e1 Corpus\n                  for Machine Translation},\n  month        = nov,\n  year         = 2020,\n  publisher    = {Zenodo},\n  version      = {1.0},\n  doi          = {10.5281/zenodo.4297448},\n  url          = {https://doi.org/10.5281/zenodo.4297448}\n}\n", "homepage": "https://zenodo.org/record/4297448#.X81G7s0zZPY", "license": "For non-commercial use because some of the data sources like Ted talks and JW news requires permission for commercial use.", "features": {"translation": {"languages": ["en", "yo"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "menyo20k_mt", "config_name": "menyo20k_mt", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2551273, "num_examples": 10070, "dataset_name": "menyo20k_mt"},"dev": {"name": "dev", "num_bytes": 849789, "num_examples": 3397, "dataset_name": "menyo20k_mt"},"test": {"name": "test", "num_bytes": 1865593, "num_examples": 6633, "dataset_name": "menyo20k_mt"} }, "download_checksums": {"https://raw.githubusercontent.com/uds-lsv/menyo-20k_MT/master/data/train.tsv": {"num_bytes": 2490852, "checksum": "3c152119d4dc1fba12ee9424f1e7fd11648acfa8e2ea7f6464a37a18e69d9a06"}}, "download_size": 2490852, "post_processing_size": null, "dataset_size": 2551273, "size_in_bytes": 5042125}}

menyo20k_mt.py

@@ -55,13 +55,19 @@ _LICENSE = "For non-commercial use because some of the data sources like Ted tal
 
 # The HuggingFace dataset library don't host the datasets but only point to the original files
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URL = "https://raw.githubusercontent.com/uds-lsv/menyo-20k_MT/master/data/train.tsv"
+_URLS = {
+        "train": "https://raw.githubusercontent.com/uds-lsv/menyo-20k_MT/master/data/train.tsv",
+        "dev": "https://raw.githubusercontent.com/uds-lsv/menyo-20k_MT/master/data/dev.tsv",
+        "test": "https://raw.githubusercontent.com/uds-lsv/menyo-20k_MT/master/data/test.tsv",
+    }
+
+
 
 
 class Menyo20kMt(datasets.GeneratorBasedBuilder):
     """MENYO-20k: A Multi-domain English - Yorùbá Corpus for Machine Translations"""
 
-    VERSION = datasets.Version("1.0.0")
+    VERSION = datasets.Version("1.1.0")
 
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(
@@ -89,10 +95,11 @@ class Menyo20kMt(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
-        train_path = dl_manager.download_and_extract(_URL)
-
+        data_files = dl_manager.download(_URLs)
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_files["test"]}),
         ]
 
     def _generate_examples(self, filepath):