Update dataset card with correct schema

README.md

@@ -10,14 +10,38 @@ dataset_info:
   features:
   - name: text
     dtype: string
+  - name: id
+    dtype: string
+  - name: wikiname
+    dtype: string
+  - name: page_id
+    dtype: int64
+  - name: title
+    dtype: string
   - name: url
     dtype: string
+  - name: date_modified
+    dtype: string
+  - name: in_language
+    dtype: string
+  - name: wikidata_id
+    dtype: string
+  - name: bytes_html
+    dtype: int64
+  - name: wikitext
+    dtype: string
+  - name: version
+    dtype: int64
+  - name: infoboxes
+    dtype: string
+  - name: has_math
+    dtype: bool
   splits:
   - name: train
     num_examples: 52721
 ---
 
-# FineWiki Sampled Dataset (1B tokens)
+# FineWiki Sampled Dataset (1,000,000,332 tokens)
 
 This is a sampled subset of [HuggingFaceFW/finewiki](https://huggingface.co/datasets/HuggingFaceFW/finewiki) containing approximately **1,000,000,332 tokens**.
 
@@ -26,15 +50,13 @@ This is a sampled subset of [HuggingFaceFW/finewiki](https://huggingface.co/data
 ### Source
 - **Original Dataset**: HuggingFaceFW/finewiki (English subset, train split)
 - **Sampling Method**: Reservoir sampling (unbiased random sampling)
-- **Target Token Count**: 1,000,000,000 tokens
-- **Actual Token Count**: 1,000,000,332 tokens
+- **Target Token Count**: 1,000,000,332 tokens
 - **Tokenizer**: GPT-2 (50,257 vocabulary)
 
 ### Sampling Statistics
 - **Documents Sampled**: 52,721
-- **Average Tokens/Doc**: 18967.8
+- **Average Tokens/Doc**: 18971.0
 - **Random Seed**: 42
-- **Reservoir Size**: 500,000 documents (max)
 
 ### Sampling Method
 
@@ -48,7 +70,7 @@ The sampling algorithm:
 1. Streams through HuggingFaceFW/finewiki without downloading
 2. Uses GPT-2 tokenizer to count tokens per document
 3. Maintains a reservoir of documents using standard reservoir sampling
-4. Truncates to target token count when complete
+4. Stops when target token count is reached
 
 ## Usage
 
@@ -61,13 +83,28 @@ dataset = load_dataset("codelion/finewiki-1B")
 # Access the training data
 for example in dataset['train']:
     print(example['text'])
+    print(example['title'])
+    print(example['url'])
 ```
 
 ## Dataset Structure
 
-Each example contains:
-- `text`: The Wikipedia article text
-- `url`: Source Wikipedia URL
+Each example contains all fields from the original FineWiki dataset:
+
+- **text** (string): The Wikipedia article text (primary content)
+- **id** (string): Unique identifier
+- **wikiname** (string): Wikipedia source name
+- **page_id** (int64): Wikipedia page ID
+- **title** (string): Article title
+- **url** (string): Source Wikipedia URL
+- **date_modified** (string): Last modification date
+- **in_language** (string): Language code (always 'en' for this subset)
+- **wikidata_id** (string): Wikidata identifier
+- **bytes_html** (int64): Size of HTML content
+- **wikitext** (string): Original wikitext markup
+- **version** (int64): Article version number
+- **infoboxes** (string): Extracted infobox data
+- **has_math** (bool): Whether article contains mathematical formulas
 
 ## Use Cases