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sr_pner_tesla_bcx
Tanor/sr_pner_tesla_bcx
sr_pner_tesla_bcx is a token classification model from Tanor. Use it when you need labels on individual words, such as names. It is set up for spacy. The card lists the license as cc-by-sa-3.0.
srpnerteslabcx is a spaCy model meticulously fine-tuned for Part-of-Speech Tagging and Named Entity Recognition in Serbian language texts. This advanced model incorporates a transformer layer based on XLM-R-BERTić, en…
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At a glance
- Task
- Token Classification
- Library
- spacy
- License
- cc-by-sa-3.0
- Access
- Public
- Created
- Jan 30, 2024
- Updated
- Jan 30, 2024
- SHA
- 7589a4d0
Model card
From the Hugging Face model README
sr_pner_tesla_bcx is a spaCy model meticulously fine-tuned for Part-of-Speech Tagging and Named Entity Recognition in Serbian language texts. This advanced model incorporates a transformer layer based on XLM-R-BERTić, enhancing its analytical capabilities. It is proficient in identifying 7 distinct categories of entities: PERS (persons), ROLE (professions), DEMO (demonyms), ORG (organizations), LOC (locations), WORK (artworks), and EVENT (events). Detailed information about these categories is available in the accompanying table. The development of this model has been made possible through the support of the Science Fund of the Republic of Serbia, under grant #7276, for the project 'Text Embeddings - Serbian Language Applications - TESLA'.
| Feature | Description |
|---|---|
| Name | sr_pner_tesla_bcx |
| Version | 1.0.0 |
| spaCy | >=3.7.2,<3.8.0 |
| Default Pipeline | transformer, tagger, ner |
| Components | transformer, tagger, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | CC BY-SA 3.0 |
| Author | Milica Ikonić Nešić, Saša Petalinkar, Mihailo Škorić, Ranka Stanković |
Label Scheme
<details> <summary>View label scheme (23 labels for 2 components)</summary>| Component | Labels |
|---|---|
tagger | ADJ, ADP, ADV, AUX, CCONJ, DET, INTJ, NOUN, NUM, PART, PRON, PROPN, PUNCT, SCONJ, VERB, X |
ner | DEMO, EVENT, LOC, ORG, PERS, ROLE, WORK |
Accuracy
| Type | Score |
|---|---|
TAG_ACC | 98.53 |
ENTS_F | 96.04 |
ENTS_P | 95.68 |
ENTS_R | 96.40 |
TRANSFORMER_LOSS | 38869.84 |
TAGGER_LOSS | 56268.63 |
NER_LOSS | 33269.80 |
- Task
- Token Classification
- Library
- spacy
- License
- cc-by-sa-3.0
- Languages
- sr
- Created
- Jan 30, 2024
- Updated
- Jan 30, 2024