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license: openrail
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license: openrail
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language:
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- en
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- es
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- ro
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- fr
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---
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# Fine-Tuned RoBERTa for Multilingual NER
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## Introduction
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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.
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## Capabilities
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The model is currently capable of recognizing:
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- Common names in English, Spanish, French, and Romanian
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- Most commonly used acronyms in these languages
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## Training Data
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The model was fine-tuned using the [`ner_acro_combined`](https://huggingface.co/datasets/eduardem/ner_acro_combined) dataset.
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## Usage
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This fine-tuned model is designed for:
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- Performing NER tasks in multilingual contexts
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- Identifying commonly used names and acronyms in the specified languages
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## Contributing
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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.
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