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README.md
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---
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tags:
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- token-classification
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- sequence-tagger-model
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language: sv
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datasets:
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- suc3_1
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widget:
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- text: "Emil bor i Lönneberga"
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---
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# KB-BERT for NER
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## Cased data
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This model is based on [KB-BERT](https://huggingface.co/KB/bert-base-swedish-cased) and was fine-tuned on the [SUC 3.1](https://huggingface.co/datasets/KBLab/suc3_1) corpus, using the _simple_ tags and cased data.
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For this model we used a variation of the data that did **not** use BIO-encoding to differentiate between the beginnings (B), and insides (I) of named entity tags.
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The model was trained on the training data only, with the best model chosen by its performance on the validation data.
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You find more information about the model and the performance on our blog: https://kb-labb.github.io/posts/2022-02-07-suc31
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