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