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 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.