Add dataset card

README.md

@@ -1,43 +1,91 @@
 ---
-dataset_info:
-  features:
-  - name: text
-    dtype: string
-  - name: mean_ocr
-    dtype: float64
-  - name: std_ocr
-    dtype: float64
-  - name: title
-    dtype: string
-  - name: date
-    dtype: string
-  - name: language
-    list: string
-  - name: item_iiif_url
-    dtype: string
-  - name: multi_language
-    dtype: bool
-  - name: issue_uri
-    dtype: string
-  - name: id
-    dtype: string
-  - name: image
-    dtype: image
-  - name: download_status
-    dtype: string
-  - name: download_retries
-    dtype: int64
-  - name: download_url
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 284338094
-    num_examples: 2000
-  download_size: 278241602
-  dataset_size: 284338094
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+task_categories:
+- image-to-text
+- text-extraction
+- document-understanding
+language:
+- multilingual
+tags:
+- newspapers
+- historical-documents
+- ocr
+- iiif
+- europeana
+size_categories:
+- n<1K
+source_datasets:
+- biglam/europeana_newspapers
 ---
+
+# Europeana Newspapers Sample Dataset
+
+## Dataset Description
+
+This is a curated sample from the Europeana newspapers dataset, prepared for Vision-Language Model (VLM) experiments, particularly for testing structured metadata extraction from historical newspaper pages.
+
+### Dataset Sources
+
+- **Original Dataset:** [biglam/europeana_newspapers](https://huggingface.co/datasets/biglam/europeana_newspapers)
+- **Source:** Europeana digital library
+- **License:** See original dataset
+
+## Dataset Structure
+
+Each sample contains a newspaper page image downloaded via IIIF along with associated metadata.
+
+### Data Fields
+
+- `image`: The newspaper page image (PIL Image)
+- `date`: Publication date (ground truth for extraction tasks)
+- `title`: Newspaper title
+- `issue`: Issue number
+- `iiif_url`: Original IIIF image URL
+- `text`: OCR text content
+- `mean_ocr`: OCR quality score (0-1)
+- `language`: Document language
+- `issue_uri`: Unique identifier
+- `download_status`: Status of image download
+- `download_retries`: Number of retry attempts needed
+
+## Use Cases
+
+This dataset is ideal for:
+- Testing VLM metadata extraction capabilities
+- Training models with GRPO for structured information extraction
+- Evaluating OCR and document understanding models
+- Benchmarking on historical newspaper understanding
+
+## Example Usage
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+dataset = load_dataset("your-username/europeana-newspapers-sample")
+
+# Access a sample
+sample = dataset['train'][0]
+image = sample['image']  # PIL Image
+date = sample['date']     # Ground truth date
+title = sample['title']   # Ground truth title
+```
+
+## Processing Notes
+
+- Images were downloaded using IIIF protocol with automatic fallback to lower resolutions
+- Failed downloads were excluded from the final dataset
+- All images are converted to RGB format
+- Dataset was created using async downloading for efficiency
+
+## Citation
+
+If you use this dataset, please cite the original Europeana newspapers dataset:
+
+```bibtex
+@dataset{europeana_newspapers,
+  title={Europeana Newspapers Dataset},
+  author={BigLAM},
+  year={2024},
+  publisher={Hugging Face}
+}
+```