Mariia
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README.md
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Our approach is based on a [model pre-trained on general-domain text](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne). In order to leverage large scale additional [Silver Standard data](https://zenodo.org/record/6803567/preview/SocialDisNER_LargeScale_additionaldata.zip#tree_item0) with automatically generated labels provided by task’s organisers we designed a two-stage fine-tuning framework. The figure below illustrated the fine-tuning process:
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# Results
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The model contained in this repository constitutes the fundament of the NER system presented by the SINAI team on SocialDisNER. Enhanced with data [`pysentimiento`](https://github.com/pysentimiento/pysentimiento) pre-processing and rule-based submission post-processing, it obtained encouraging results during the official evaluation, which are summarised in the table below.
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Our approach is based on a [model pre-trained on general-domain text](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne). In order to leverage large scale additional [Silver Standard data](https://zenodo.org/record/6803567/preview/SocialDisNER_LargeScale_additionaldata.zip#tree_item0) with automatically generated labels provided by task’s organisers we designed a two-stage fine-tuning framework. The figure below illustrated the fine-tuning process:
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# Results
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The model contained in this repository constitutes the fundament of the NER system presented by the SINAI team on SocialDisNER. Enhanced with data [`pysentimiento`](https://github.com/pysentimiento/pysentimiento) pre-processing and rule-based submission post-processing, it obtained encouraging results during the official evaluation, which are summarised in the table below.
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