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--- |
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language: |
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- hr |
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- bs |
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- sr |
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- cnr |
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- hbs |
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widget: |
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- text: "Zovem se Marko i živim u Zagrebu. Studirao sam u Beogradu na Filozofskom fakultetu. Obožavam album Moanin." |
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license: apache-2.0 |
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--- |
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# The [BERTić](https://huggingface.co/classla/bcms-bertic)* [bert-ich] /bɜrtitʃ/ model fine-tuned for the task of named entity recognition in Bosnian, Croatian, Montenegrin and Serbian (BCMS) |
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* The name should resemble the facts (1) that the model was trained in Zagreb, Croatia, where diminutives ending in -ić (as in fotić, smajlić, hengić etc.) are very popular, and (2) that most surnames in the countries where these languages are spoken end in -ić (with diminutive etymology as well). |
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This is a fine-tuned version of the [BERTić](https://huggingface.co/classla/bcms-bertic) model for the task of named entity recognition (PER, LOC, ORG, MISC). The fine-tuning was performed on the following datasets: |
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- the [hr500k](http://hdl.handle.net/11356/1183) dataset, 500 thousand tokens in size, standard Croatian |
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- the [SETimes.SR](http://hdl.handle.net/11356/1200) dataset, 87 thousand tokens in size, standard Serbian |
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- the [ReLDI-hr](http://hdl.handle.net/11356/1241) dataset, 89 thousand tokens in size, Internet (Twitter) Croatian |
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- the [ReLDI-sr](http://hdl.handle.net/11356/1240) dataset, 92 thousand tokens in size, Internet (Twitter) Serbian |
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The data was augmented with missing diacritics and standard data was additionally over-represented. The F1 obtained on dev data (train and test was merged into train) is 91.38. For a more detailed per-dataset evaluation of the BERTić model on the NER task have a look at the [main model page](https://huggingface.co/classla/bcms-bertic). |
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If you use this fine-tuned model, please cite the following paper: |
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``` |
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@inproceedings{ljubesic-lauc-2021-bertic, |
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title = "{BERT}i{\'c} - The Transformer Language Model for {B}osnian, {C}roatian, {M}ontenegrin and {S}erbian", |
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author = "Ljube{\v{s}}i{\'c}, Nikola and Lauc, Davor", |
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booktitle = "Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing", |
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month = apr, |
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year = "2021", |
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address = "Kiyv, Ukraine", |
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publisher = "Association for Computational Linguistics", |
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url = "https://www.aclweb.org/anthology/2021.bsnlp-1.5", |
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pages = "37--42", |
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} |
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``` |
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When running the model in `simpletransformers`, the order of labels has to be set as well. |
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``` |
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from simpletransformers.ner import NERModel, NERArgs |
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model_args = NERArgs() |
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model_args.labels_list = ['B-LOC','B-MISC','B-ORG','B-PER','I-LOC','I-MISC','I-ORG','I-PER','O'] |
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model = NERModel('electra', 'classla/bcms-bertic-ner', args=model_args) |
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``` |
