Add dataset README for sentiment corpus

README.md

@@ -1,24 +1,98 @@
 ---
-dataset_info:
-  features:
-  - name: Lingala
-    dtype: string
-  - name: sentiment
-    dtype: string
-  - name: __index_level_0__
-    dtype: int64
-  splits:
-  - name: train
-    num_bytes: 28833901
-    num_examples: 427979
-  download_size: 17709218
-  dataset_size: 28833901
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: mit
+task_categories:
+- text-classification
+language:
+- lin
+tags:
+- sentiment
+- african-languages
+- nlp
+- text-classification
+- binary-classification
+size_categories:
+- 100K<n<1M
 ---
-# Dataset Card for "lingala-sentiments-corpus"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+# Lingala Sentiment Corpus
+
+## Dataset Description
+
+This dataset contains sentiment-labeled text data in Lingala for binary sentiment classification (Positive/Negative). Sentiments are extracted and processed from the English meanings of the sentences using DistilBERT for sentiment classification. The dataset is part of a larger collection of African language sentiment analysis resources.
+
+## Dataset Statistics
+
+- **Total samples**: 427,979
+- **Positive sentiment**: 251923 (58.9%)
+- **Negative sentiment**: 176056 (41.1%)
+
+## Dataset Structure
+
+### Data Fields
+
+- **Text Column**: Contains the original text in Lingala
+- **sentiment**: Sentiment label (Positive or Negative only)
+
+### Data Splits
+
+This dataset contains a single split with all the processed data.
+
+## Data Processing
+
+The sentiment labels were generated using:
+- Model: `distilbert-base-uncased-finetuned-sst-2-english`
+- Processing: Batch processing with optimization for efficiency
+- Deduplication: Duplicate entries were removed based on text content
+- **Filtering**: Only Positive and Negative sentiments retained for binary classification
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+dataset = load_dataset("michsethowusu/lingala-sentiments-corpus")
+
+# Access the data
+print(dataset['train'][0])
+
+# Check sentiment distribution
+from collections import Counter
+sentiments = [item['sentiment'] for item in dataset['train']]
+print(Counter(sentiments))
+```
+
+## Use Cases
+
+This dataset is ideal for:
+- Binary sentiment classification tasks
+- Training sentiment analysis models for Lingala
+- Cross-lingual sentiment analysis research
+- African language NLP model development
+
+## Citation
+
+If you use this dataset in your research, please cite:
+
+```bibtex
+@dataset{lingala_sentiments_corpus,
+  title={Lingala Sentiment Corpus},
+  author={Mich-Seth Owusu},
+  year={2025},
+  url={https://huggingface.co/datasets/michsethowusu/lingala-sentiments-corpus}
+}
+```
+
+## License
+
+This dataset is released under the MIT License.
+
+## Contact
+
+For questions or issues regarding this dataset, please open an issue on the dataset repository.
+
+## Dataset Creation
+
+**Date**: 2025-07-02
+**Processing Pipeline**: Automated sentiment analysis using HuggingFace Transformers
+**Quality Control**: Deduplication, batch processing optimizations, and binary sentiment filtering applied