---
license: apache-2.0
language:
- ro
base_model: EvanD/xlm-roberta-base-romanian-ner-ronec
tags:
- token-classification
- named-entity-recognition
- pii-detection
- romanian
- moldova
- financial-pii
- banking
- fintech
---

# Finguys/acta-anonymizer-financial

Acta Anonymizer Financial Adapter

This model is a fine-tuned adapter for Romanian financial text anonymization. 
It's based on XLM-RoBERTa and trained specifically for detecting and anonymizing 
PII in Romanian financial documents from Moldova.

Key features:
- Romanian language support
- Financial domain specialization
- GDPR compliance focused
- High accuracy PII detection

Use cases:
- Banking document anonymization
- Financial report processing
- Compliance data handling


**Current Version**: 20250914_103007

## Key Features

- Romanian language support
- GDPR compliance focused
- High accuracy PII detection
- Domain-specific fine-tuning

## Use Cases

- Banking document anonymization
- Financial report processing
- Compliance data handling

## Training Data

This model was trained on synthetic Moldovan PII data for financial domain anonymization.

## Usage

```python
from peft import PeftModel
from transformers import AutoModelForTokenClassification, AutoTokenizer, pipeline

# Load base model
model = AutoModelForTokenClassification.from_pretrained("EvanD/xlm-roberta-base-romanian-ner-ronec")
tokenizer = AutoTokenizer.from_pretrained("EvanD/xlm-roberta-base-romanian-ner-ronec")

# Load adapter
model = PeftModel.from_pretrained(model, "Finguys/acta-anonymizer-financial")

# Create pipeline
ner_pipeline = pipeline(
    "token-classification",
    model=model,
    tokenizer=tokenizer,
    aggregation_strategy="simple"
)

# Example usage
text = "Ion Popescu are un cont la Banca Transilvania cu IBAN RO49AAAA1B310075938400000."
entities = ner_pipeline(text)
print(entities)
```

## Training

This model was trained using LoRA (Low-Rank Adaptation) on synthetic Moldovan PII data.

## Versions

- **Latest**: Root level contains the most recent version
- **Archived**: Previous versions are stored in `versions/` folder
- **Version Index**: See `version_history.yaml` for complete version history