flair-uk-ner
Model description
flair-uk-ner is a Flair model that is ready to use for Named Entity Recognition. It is based on flair embeddings, that I've trained for Ukrainian language (available here and here) and has nice performance and a very small size (just 72mb!).
It has been trained to recognize four types of entities: location (LOC), organizations (ORG), person (PERS) and Miscellaneous (MISC).
Results:
- F-score (micro) 0.8605
- F-score (macro) 0.7472
- Accuracy 0.8033
| by class | precision | recall | f1-score | support |
|---|---|---|---|---|
| PERS | 0.9305 | 0.9422 | 0.9363 | 1678 |
| LOC | 0.8150 | 0.8678 | 0.8406 | 401 |
| ORG | 0.6653 | 0.6092 | 0.6360 | 261 |
| MISC | 0.6202 | 0.5375 | 0.5759 | 240 |
| micro avg | 0.8616 | 0.8593 | 0.8605 | 2580 |
| macro avg | 0.7577 | 0.7392 | 0.7472 | 2580 |
| weighted avg | 0.8569 | 0.8593 | 0.8575 | 2580 |
The model was fine-tuned on the NER-UK dataset, released by the lang-uk. Training code is also available here.
Copyright: Dmytro Chaplynskyi, lang-uk project, 2022