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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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