---
license: mit
datasets:
- nesemenpolkov/bookMeta-ru
language:
- ru
metrics:
- accuracy
base_model:
- deepvk/bert-base-uncased
- deepvk/USER-base
new_version: nesemenpolkov/ruGliner-bookMeta
pipeline_tag: token-classification
library_name: transformers
---
# GLiNER-based Book Metadata Extraction Model

## Model Description

This model is a fine-tuned **GLiNER** (Generalized Linear Named Entity Recognition) model designed for extracting structured metadata from book references and citations. The model is built on top of:

- **GLiNER framework** for zero-shot named entity recognition
- **bert-base-uncased** as the base transformer architecture
- **USER-base** (from deepvk) as an additional pretrained component
- Fine-tuned on the **bookMeta** dataset for book metadata extraction

## Intended Use

The model is specifically designed to extract the following entities from book references and academic citations:

- `authors` - Book authors or editors
- `title` - Book or article title
- `publisher` - Publishing house or organization
- `year` - Publication year
- `pages` - Page numbers or page count

## How to Use

```python
from gliner import GLiNER

# Load the model
model = GLiNER.from_pretrained("nesemenpolkov/ruGliner-bookMeta")

# Example text
text = "Азбука Морзе для чайников // Иванов П.П., Гущина И. А. 1999. 3 с."

# Define target labels
labels = ["authors", "title", "publisher", "year", "pages"]

# Predict entities
entities = model.predict_entities(text, labels)

# Display results
for entity in entities:
    print(f"{entity['text']} => {entity['label']}")
```

## Training Data

The model was fine-tuned on the **bookMeta** dataset containing annotated book references with the following characteristics:

## Training Data

### Dataset Structure
- **Total samples**: 10,000  
- **Train/Test split**: 80%/20%    
- **Average entities per sample**: 4.3  

### Annotation Guidelines
- authors ::= "Иванов А.А., Петров Б.Б."
- title ::= "Введение в машинное обучение"
- publisher ::= "Издательство МГУ" | "Springer"
- year ::= "2020" | "1999 г."
- pages ::= "с. 123-145" | "pp. 45-67"