update dataset readme

README.md

@@ -17,3 +17,77 @@ configs:
   - split: train
     path: data/train-*
 ---
+
+
+# Dataset Card for "wikipedia-bookscorpus-en-preprocessed"
+
+## Dataset Summary
+
+A preprocessed and normalized combination of English Wikipedia and BookCorpus datasets, optimized for BERT pretraining. The dataset is chunked into segments of ~820 characters to accommodate typical transformer architectures.
+
+## Dataset Details
+
+- **Number of Examples:** 29.4 million
+- **Download Size:** 12.2 GB
+- **Dataset Size:** 19.0 GB
+
+### Features:
+```python
+{
+    'text': string,       # The preprocessed text chunk
+    'is_filtered_out': bool  # Filtering flag for data quality
+}
+```
+
+## Processing Pipeline
+
+1. **Language Filtering:**
+   - Retains only English language samples
+   - Uses langdetect for language detection
+
+2. **Text Chunking:**
+   - Chunks of ~820 characters (targeting ~128 tokens)
+   - Preserves sentence boundaries where possible
+   - Splits on sentence endings (., !, ?) or spaces
+
+3. **Normalization:**
+   - Converts to lowercase
+   - Removes accents and non-English characters
+   - Filters out chunks < 200 characters
+   - Removes special characters
+
+4. **Data Organization:**
+   - Shuffled for efficient training
+   - Distributed across multiple JSONL files
+   - No need for additional dataset.shuffle() during training
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("shahrukhx01/wikipedia-bookscorpus-en-preprocessed")
+```
+
+## Preprocessing Details
+
+For detailed information about the preprocessing pipeline, see the [preprocessing documentation](https://github.com/shahrukhx01/minions/tree/main/scripts/data/bert_pretraining_data/README.md).
+
+## Limitations
+
+- Some tokens may be lost due to chunk truncation
+- Very long sentences might be split
+- Some contextual information across chunk boundaries is lost
+
+## Citation
+
+If you use this dataset, please cite:
+```
+@misc{wikipedia-bookscorpus-en-preprocessed,
+  author = {Shahrukh Khan},
+  title = {Preprocessed Wikipedia and BookCorpus Dataset for Language Model Training},
+  year = {2024},
+  publisher = {GitHub & Hugging Face},
+  howpublished = {\url{https://huggingface.co/datasets/shahrukhx01/wikipedia-bookscorpus-en-preprocessed}}
+}
+```