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Swedish-NER
RecordedFuture/Swedish-NER
Swedish-NER is a token classification model from RecordedFuture. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
Recorded Future together with AI Sweden releases a Named Entity Recognition(NER) model for entety detection in Swedish. The model is based on KB/bert-base-swedish-cased and finetuned on data collected from various int…
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- May 24, 2021
- SHA
- 436f9d59
Model card
From the Hugging Face model README
Swedish BERT models for sentiment analysis, Sentiment targets.
Recorded Future together with AI Sweden releases a Named Entity Recognition(NER) model for entety detection in Swedish. The model is based on KB/bert-base-swedish-cased and finetuned on data collected from various internet sources and forums.
The model has been trained on Swedish data and only supports inference of Swedish input texts. The models inference metrics for all non-Swedish inputs are not defined, these inputs are considered as out of domain data.
The current models are supported at Transformers version >= 4.3.3 and Torch version 1.8.0, compatibility with older versions are not verified.
Available tags
- Location
- Organization
- Person
- Religion
- Title
Evaluation metrics
The model had the following metrics when evaluated on test data originating from the same domain as the training data.
F1-score
| Loc | Org | Per | Nat | Rel | Tit | Total |
|---|---|---|---|---|---|---|
| 0.91 | 0.88 | 0.96 | 0.95 | 0.91 | 0.84 | 0.92 |
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- sv
- Created
- Mar 2, 2022
- Updated
- May 24, 2021