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---
tags:
- autotrain
- token-classification
- arxiv:2104.09617
- mlx
base_model: NbAiLab/nb-bert-base
datasets:
- ltgoslo/norne
license: apache-2.0
language:
- 'no'
- nb
- nn
pipeline_tag: token-classification
library_name: transformers
inference:
parameters:
aggregation_strategy: first
widget:
- text: >-
Trond Giske har bekreftet på spørsmål fra Adresseavisen at Hansen leide et
rom i hans leilighet i Trondheim.
model-index:
- name: NbAiLab/nb-bert-base-pos
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: ltgoslo/norne
type: ltgoslo/norne
args: bokmaal
metrics:
- name: Test Loss
type: loss
value: 0.0650700181722641
- name: Test Precision
type: precision
value: 0.985085078075765
- name: Test Recall
type: recall
value: 0.9877826148012919
- name: Test F1
type: f1
value: 0.9864320022438031
- name: Test Accuracy
type: accuracy
value: 0.9861949007001629
metrics:
- accuracy
- f1
- precision
- recall
---
**Release 1.0** (November 6, 2024)
# nb-bert-base-pos
## Description
NB-Bert base model fine-tuned on the Part of Speech task using the [NorNE dataset](https://huggingface.co/datasets/ltgoslo/norne).
## Usage
```python
from transformers import pipeline
pos = pipeline("token-classification", "NbAiLab/nb-bert-base-pos")
example = "Jeg heter Kjell og bor i Oslo."
pos_results = pos(example)
print(ner_results)
```
More on https://arxiv.org/abs/2104.09617 |