Fix URL for the validation split (#4)

- The URL for the validation set was previously pointed toward to the training set. Fixed to correct URL. (563edc818b5f855ea451913ac4a2b92cc0162bb4)
- Update checksums and sizes for the new files (d22e4f7c16dad1ab83621aab87ffe7f81e5c2023)
- Bump versions (85f680a6c074232322808a2b71ddca61fd98bf34)
- Update README.md according to validation split (706b69e1efe01f8bf55feb8e2b6bf531f7ed99ae)


Co-authored-by: Or Sharir <orsharir@users.noreply.huggingface.co>

README.md

@@ -65,8 +65,8 @@ dataset_info:
     num_bytes: 2805711609
     num_examples: 600000
   - name: validation
-    num_bytes: 2805711609
-    num_examples: 600000
+    num_bytes: 960356598
+    num_examples: 150000
   download_size: 1003195420
   dataset_size: 5611423218
 ---
@@ -198,7 +198,7 @@ The data fields are the same among all splits.
 
 |           |train |validation|
 |-----------|-----:|---------:|
-|bypublisher|600000|    600000|
+|bypublisher|600000|    150000|
 
 ## Dataset Creation
 

dataset_infos.json

@@ -1 +1 @@
-{"byarticle": {"description": "Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4.\nGiven a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.\n\nThere are 2 parts:\n- byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed.\n- bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.\n", "citation": "@article{kiesel2019data,\n  title={Data for pan at semeval 2019 task 4: Hyperpartisan news detection},\n  author={Kiesel, Johannes and Mestre, Maria and Shukla, Rishabh and Vincent, Emmanuel and Corney, David and Adineh, Payam and Stein, Benno and Potthast, Martin},\n  year={2019}\n}\n", "homepage": "https://pan.webis.de/semeval19/semeval19-web/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "hyperpartisan": {"dtype": "bool", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "published_at": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": {"features": null, "resources_checksums": {"train": {}}}, "supervised_keys": {"input": "text", "output": "label"}, "builder_name": "hyperpartisan_news_detection", "config_name": "byarticle", "version": {"version_str": "1.0.0", "description": "Version Training and validation v1", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2803943, "num_examples": 645, "dataset_name": "hyperpartisan_news_detection"}}, "download_checksums": {"https://zenodo.org/record/1489920/files/articles-training-byarticle-20181122.zip?download=1": {"num_bytes": 971841, "checksum": "62b4a71275ef2724faddc74d6ff3d782ee9898c732cd66119c7976f6f5168990"}, "https://zenodo.org/record/1489920/files/ground-truth-training-byarticle-20181122.zip?download=1": {"num_bytes": 28511, "checksum": "0c02f4c33317287758e6fbbc976cbfd7a0978923899ddf30cb9dd2cd740af43c"}}, "download_size": 1000352, "post_processing_size": 0, "dataset_size": 2803943, "size_in_bytes": 3804295}, "bypublisher": {"description": "Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4.\nGiven a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.\n\nThere are 2 parts:\n- byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed.\n- bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.\n", "citation": "@article{kiesel2019data,\n  title={Data for pan at semeval 2019 task 4: Hyperpartisan news detection},\n  author={Kiesel, Johannes and Mestre, Maria and Shukla, Rishabh and Vincent, Emmanuel and Corney, David and Adineh, Payam and Stein, Benno and Potthast, Martin},\n  year={2019}\n}\n", "homepage": "https://pan.webis.de/semeval19/semeval19-web/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "hyperpartisan": {"dtype": "bool", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "published_at": {"dtype": "string", "id": null, "_type": "Value"}, "bias": {"num_classes": 5, "names": ["right", "right-center", "least", "left-center", "left"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": {"features": null, "resources_checksums": {"train": {}, "validation": {}}}, "supervised_keys": {"input": "text", "output": "label"}, "builder_name": "hyperpartisan_news_detection", "config_name": "bypublisher", "version": {"version_str": "1.0.0", "description": "Version Training and validation v1", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2805711609, "num_examples": 600000, "dataset_name": "hyperpartisan_news_detection"}, "validation": {"name": "validation", "num_bytes": 2805711609, "num_examples": 600000, "dataset_name": "hyperpartisan_news_detection"}}, "download_checksums": {"https://zenodo.org/record/1489920/files/articles-training-bypublisher-20181122.zip?download=1": {"num_bytes": 980769009, "checksum": "e5816b0c9fecd1a38f6cba8eb4f6f77d04637b5c6209e714b7ab32dc3bc24e28"}, "https://zenodo.org/record/1489920/files/ground-truth-training-bypublisher-20181122.zip?download=1": {"num_bytes": 22426411, "checksum": "f1c0494af86ff1e961479a63d432d649ccda875d302888f4d080dbec0382b1ef"}}, "download_size": 1003195420, "post_processing_size": 0, "dataset_size": 5611423218, "size_in_bytes": 6614618638}}
+{"byarticle": {"description": "Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4.\nGiven a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.\n\nThere are 2 parts:\n- byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed.\n- bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.\n", "citation": "@article{kiesel2019data,\n  title={Data for pan at semeval 2019 task 4: Hyperpartisan news detection},\n  author={Kiesel, Johannes and Mestre, Maria and Shukla, Rishabh and Vincent, Emmanuel and Corney, David and Adineh, Payam and Stein, Benno and Potthast, Martin},\n  year={2019}\n}\n", "homepage": "https://pan.webis.de/semeval19/semeval19-web/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "hyperpartisan": {"dtype": "bool", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "published_at": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": {"features": null, "resources_checksums": {"train": {}}}, "supervised_keys": {"input": "text", "output": "label"}, "builder_name": "hyperpartisan_news_detection", "config_name": "byarticle", "version": {"version_str": "1.0.0", "description": "Version Training and validation v1", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2803943, "num_examples": 645, "dataset_name": "hyperpartisan_news_detection"}}, "download_checksums": {"https://zenodo.org/record/1489920/files/articles-training-byarticle-20181122.zip?download=1": {"num_bytes": 971841, "checksum": "62b4a71275ef2724faddc74d6ff3d782ee9898c732cd66119c7976f6f5168990"}, "https://zenodo.org/record/1489920/files/ground-truth-training-byarticle-20181122.zip?download=1": {"num_bytes": 28511, "checksum": "0c02f4c33317287758e6fbbc976cbfd7a0978923899ddf30cb9dd2cd740af43c"}}, "download_size": 1000352, "post_processing_size": 0, "dataset_size": 2803943, "size_in_bytes": 3804295}, "bypublisher": {"description": "Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4.\nGiven a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.\n\nThere are 2 parts:\n- byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed.\n- bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.\n", "citation": "@article{kiesel2019data,\n  title={Data for pan at semeval 2019 task 4: Hyperpartisan news detection},\n  author={Kiesel, Johannes and Mestre, Maria and Shukla, Rishabh and Vincent, Emmanuel and Corney, David and Adineh, Payam and Stein, Benno and Potthast, Martin},\n  year={2019}\n}\n", "homepage": "https://pan.webis.de/semeval19/semeval19-web/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "hyperpartisan": {"dtype": "bool", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "published_at": {"dtype": "string", "id": null, "_type": "Value"}, "bias": {"num_classes": 5, "names": ["right", "right-center", "least", "left-center", "left"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": {"features": null, "resources_checksums": {"train": {}, "validation": {}}}, "supervised_keys": {"input": "text", "output": "label"}, "builder_name": "hyperpartisan_news_detection", "config_name": "bypublisher", "version": {"version_str": "1.0.1", "description": "Version Training and validation v1", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 1}, "splits": {"train": {"name": "train", "num_bytes": 2805711609, "num_examples": 600000, "dataset_name": "hyperpartisan_news_detection"}, "validation": {"name": "validation", "num_bytes": 960356598, "num_examples": 150000, "dataset_name": "hyperpartisan_news_detection"}}, "download_checksums": {"https://zenodo.org/record/1489920/files/articles-training-bypublisher-20181122.zip?download=1": {"num_bytes": 980769009, "checksum": "e5816b0c9fecd1a38f6cba8eb4f6f77d04637b5c6209e714b7ab32dc3bc24e28"}, "https://zenodo.org/record/1489920/files/ground-truth-training-bypublisher-20181122.zip?download=1": {"num_bytes": 22426411, "checksum": "f1c0494af86ff1e961479a63d432d649ccda875d302888f4d080dbec0382b1ef"}, "https://zenodo.org/record/1489920/files/articles-validation-bypublisher-20181122.zip?download=1": {"num_bytes": 337386275, "checksum": "dd1cd3d7f34d7f35564ba2b7002cad796877507bec503cc1dd02076dc289ae34"}, "https://zenodo.org/record/1489920/files/ground-truth-validation-bypublisher-20181122.zip?download=1": {"num_bytes": 5239324, "checksum": "23f7cd8b410a91193e2b6548ba274d7da1061ea7c86083e9b5ced4cac9bb34e7"}}, "download_size": 1345821019, "post_processing_size": 0, "dataset_size": 3766068207, "size_in_bytes": 6614618638}}

hyperpartisan_news_detection.py

@@ -46,7 +46,7 @@ _URL_BASE = "https://zenodo.org/record/1489920/files/"
 class HyperpartisanNewsDetection(datasets.GeneratorBasedBuilder):
     """Hyperpartisan News Detection Dataset."""
 
-    VERSION = datasets.Version("1.0.0")
+    VERSION = datasets.Version("1.0.1")
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(
             name="byarticle",
@@ -62,7 +62,7 @@ class HyperpartisanNewsDetection(datasets.GeneratorBasedBuilder):
         ),
         datasets.BuilderConfig(
             name="bypublisher",
-            version=datasets.Version("1.0.0", "Version Training and validation v1"),
+            version=datasets.Version("1.0.1", "Version Training and validation v1"),
             description=textwrap.dedent(
                 """
                     This part of the data (filename contains "bypublisher") is labeled by the overall bias of the publisher as provided
@@ -107,8 +107,8 @@ class HyperpartisanNewsDetection(datasets.GeneratorBasedBuilder):
         }
         if self.config.name == "bypublisher":
             urls[datasets.Split.VALIDATION] = {
-                "articles_file": _URL_BASE + "articles-training-" + self.config.name + "-20181122.zip?download=1",
-                "labels_file": _URL_BASE + "ground-truth-training-" + self.config.name + "-20181122.zip?download=1",
+                "articles_file": _URL_BASE + "articles-validation-" + self.config.name + "-20181122.zip?download=1",
+                "labels_file": _URL_BASE + "ground-truth-validation-" + self.config.name + "-20181122.zip?download=1",
             }
 
         data_dir = {}