Update README.md

README.md

@@ -164,8 +164,26 @@ dataset = load_dataset("MothMalone/data-preprocessing-automl-benchmarks", "trec"
 
 Below are the details for each dataset configuration available in this repository.
 
+Of course. Here are the completed descriptions for your dataset card.
+
+### imdb
+- Description: A large movie review dataset for binary sentiment classification, containing 25,000 highly polarized movie reviews for training and 25,000 for testing.
+- Data Quality Issue: N/A
+- Classes: 2
+- Training Samples: 18750
+- Validation Samples: 6250
+- Test Samples: 25000
+
+### twenty_newsgroups
+- Description: A collection of approximately 20,000 newsgroup documents, partitioned evenly across 20 different newsgroups, making it a classic benchmark for text classification.
+- Data Quality Issue: N/A
+- Classes: 20
+- Training Samples: 8485
+- Validation Samples: 2829
+- Test Samples: 7532
+
 ### banking77
-- Description: N/A
+- Description: A fine-grained dataset of 13,083 customer service queries from the banking domain, annotated with 77 distinct intents.
 - Data Quality Issue: N/A
 - Classes: 77
 - Training Samples: 7502
@@ -173,7 +191,7 @@ Below are the details for each dataset configuration available in this repositor
 - Test Samples: 3080
 
 ### trec
-- Description: The Text REtrieval Conference (TREC) Question Classification dataset contains 5500 labeled questions in training set and another 500 for test set.
+- Description:  The Text REtrieval Conference (TREC) question classification dataset, containing questions categorized by their answer type (e.g., Person, Location, Number).
 - Data Quality Issue: N/A
 - Classes: 6
 - Training Samples: 4089
@@ -181,14 +199,15 @@ Below are the details for each dataset configuration available in this repositor
 - Test Samples: 500
 
 ### financial_phrasebank
-- Description: The key arguments for the low utilization of statistical techniques in
+- Description:  A collection of sentences from English financial news, annotated for sentiment (positive, negative, or neutral) by financial experts.
 - Data Quality Issue: N/A
 - Classes: 3
 - Training Samples: 1358
 - Validation Samples: 453
 - Test Samples: 453
+- 
 ### MASSIVE
-- Description: 
+- Description: A multilingual dataset of 1 million utterances for intent classification and slot filling, covering 52 languages. The en-US configuration is used here.
 - Data Quality Issue: N/A
 - Classes: 60
 - Training Samples: 11514