| ag_news: | |
| class_names: | |
| - World | |
| - Sports | |
| - Business | |
| - Technology | |
| description: News categorization with 4 classes, known for similar content across | |
| categories | |
| name: AG News Classification | |
| num_classes: 4 | |
| original_test_samples: 7600 | |
| original_train_samples: 120000 | |
| quality_issues: | |
| - redundancy | |
| - similar_content | |
| - topic_overlap | |
| target_column: label | |
| task_type: multi_classification | |
| test_samples: 7600 | |
| text_columns: | |
| - text | |
| total_samples: 127600 | |
| train_samples: 90000 | |
| validation_samples: 30000 | |
| amazon_polarity: | |
| class_names: | |
| - negative | |
| - positive | |
| description: Amazon reviews with noisy sentiment labels | |
| name: Amazon Product Reviews | |
| num_classes: 2 | |
| original_test_samples: 400000 | |
| original_train_samples: 3600000 | |
| quality_issues: | |
| - label_noise | |
| - rating_inconsistency | |
| target_column: label | |
| task_type: binary_classification | |
| test_samples: 400000 | |
| text_columns: | |
| - text | |
| total_samples: 4000000 | |
| train_samples: 2700000 | |
| validation_samples: 900000 | |
| emotion: | |
| class_names: | |
| - sadness | |
| - joy | |
| - love | |
| - anger | |
| - fear | |
| - surprise | |
| description: Twitter emotion classification with text length outliers | |
| name: Emotion Classification | |
| num_classes: 6 | |
| original_test_samples: 41681 | |
| original_train_samples: 333447 | |
| quality_issues: | |
| - length_outliers | |
| - text_anomalies | |
| target_column: label | |
| task_type: multi_classification | |
| test_samples: 41681 | |
| text_columns: | |
| - text | |
| total_samples: 375128 | |
| train_samples: 250085 | |
| validation_samples: 83362 | |
| imdb: | |
| class_names: | |
| - negative | |
| - positive | |
| description: Movie reviews with subjective sentiment labels and borderline cases | |
| name: IMDB Movie Reviews | |
| num_classes: 2 | |
| original_test_samples: 25000 | |
| original_train_samples: 25000 | |
| quality_issues: | |
| - label_noise | |
| - subjective_labels | |
| - borderline_cases | |
| target_column: label | |
| task_type: binary_classification | |
| test_samples: 25000 | |
| text_columns: | |
| - text | |
| total_samples: 50000 | |
| train_samples: 18750 | |
| validation_samples: 6250 | |
| twenty_newsgroups: | |
| class_names: | |
| - alt.atheism | |
| - comp.graphics | |
| - comp.os.ms-windows.misc | |
| - comp.sys.ibm.pc.hardware | |
| - comp.sys.mac.hardware | |
| - comp.windows.x | |
| - misc.forsale | |
| - rec.autos | |
| - rec.motorcycles | |
| - rec.sport.baseball | |
| - rec.sport.hockey | |
| - sci.crypt | |
| - sci.electronics | |
| - sci.med | |
| - sci.space | |
| - soc.religion.christian | |
| - talk.politics.guns | |
| - talk.politics.mideast | |
| - talk.politics.misc | |
| - talk.religion.misc | |
| description: Newsgroup posts with overlapping topics and cross-posting | |
| name: 20 Newsgroups | |
| num_classes: 20 | |
| original_test_samples: 7532 | |
| original_train_samples: 11314 | |
| quality_issues: | |
| - redundancy | |
| - cross_posting | |
| - similar_topics | |
| target_column: label | |
| task_type: multi_classification | |
| test_samples: 7532 | |
| text_columns: | |
| - text | |
| total_samples: 18846 | |
| train_samples: 8485 | |
| validation_samples: 2829 | |
| yelp_polarity: | |
| class_names: | |
| - negative | |
| - positive | |
| description: Yelp reviews with positive/negative sentiment, naturally imbalanced | |
| name: Yelp Review Polarity | |
| num_classes: 2 | |
| original_test_samples: 38000 | |
| original_train_samples: 560000 | |
| quality_issues: | |
| - moderate_imbalance | |
| - rating_bias | |
| target_column: label | |
| task_type: binary_classification | |
| test_samples: 38000 | |
| text_columns: | |
| - text | |
| total_samples: 598000 | |
| train_samples: 420000 | |
| validation_samples: 140000 | |