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sr_pln_tesla_dbmu
Tanor/sr_pln_tesla_dbmu
sr_pln_tesla_dbmu 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.
srplntesladbmu is a spaCy model meticulously fine-tuned for Part-of-Speech Tagging, Lemmatization, and Named Entity Recognition in Serbian language texts. This advanced model incorporates a transformer layer based on…
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At a glance
- Task
- Token Classification
- Library
- spacy
- License
- cc-by-sa-3.0
- Access
- Public
- Created
- Feb 1, 2024
- Updated
- Feb 1, 2024
- SHA
- 066a57e1
Model card
From the Hugging Face model README
sr_pln_tesla_dbmu is a spaCy model meticulously fine-tuned for Part-of-Speech Tagging, Lemmatization, and Named Entity Recognition in Serbian language texts. This advanced model incorporates a transformer layer based on distilbert/distilbert-base-multilingual-cased, 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_pln_tesla_dbmu |
| Version | 1.0.0 |
| spaCy | >=3.7.2,<3.8.0 |
| Default Pipeline | transformer, tagger, trainable_lemmatizer, ner |
| Components | transformer, tagger, trainable_lemmatizer, 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 | 98.15 |
LEMMA_ACC | 97.97 |
ENTS_F | 94.86 |
ENTS_P | 94.66 |
ENTS_R | 95.06 |
TRANSFORMER_LOSS | 604959.76 |
TAGGER_LOSS | 359950.85 |
TRAINABLE_LEMMATIZER_LOSS | 466065.88 |
NER_LOSS | 175653.69 |
- Task
- Token Classification
- Library
- spacy
- License
- cc-by-sa-3.0
- Languages
- sr
- Created
- Feb 1, 2024
- Updated
- Feb 1, 2024