---
license: openrail
language:
- en
- es
- ro
- fr
---

# Fine-Tuned RoBERTa for Multilingual NER

## Introduction

This model is a fine-tuned version of the RoBERTa base model, specialized for Named Entity Recognition (NER) tasks in English, Spanish, French, and Romanian.

## Capabilities

The model is currently capable of recognizing:
- Common names in English, Spanish, French, and Romanian
- Most commonly used acronyms in these languages

## Training Data

The model was fine-tuned using the [`ner_acro_combined`](https://huggingface.co./datasets/eduardem/ner_acro_combined) dataset.

## Usage

This fine-tuned model is designed for:
- Performing NER tasks in multilingual contexts
- Identifying commonly used names and acronyms in the specified languages

## Contributing

If you have suggestions for improvements or bug reports related to this model, please feel free to open an issue or submit a pull request.