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---
license: mit
language:
- la
base_model:
- latincy/la_core_web_lg
model-index:
- name: la_core_web_lg_3.7.4
results:
- task:
type: NER
dataset:
name: Herodotos_dataset
type: Herodotos_dataset
metrics:
- name: macro F1
type: macro F1
value: 58
source:
name: SEFLAG
url: https://bibbase.org/network/publication/schulz-deichsler-seflagsystematicevaluationframeworkfornlpmodelsanddatasetsinlatinandancientgreek-2024
- task:
type: lemmatization
dataset:
name: UD-Latin
type: UD-Latin
metrics:
- name: accuracy
type: accuracy
value: 88
source:
name: SEFLAG
url: https://bibbase.org/network/publication/schulz-deichsler-seflagsystematicevaluationframeworkfornlpmodelsanddatasetsinlatinandancientgreek-2024
---
**la_core_web_lg**
- **Person or organization developing model**: [Patrick J. Burns; with
Nora Bernhardt \[ner\], Tim Geelhaar \[tagger, morphologizer, parser,
ner\], Vincent Koch \[ner\]](https://diyclassics.github.io/)
- **Model date**: May 2023
- **Model version: 3.7.4**
- **Model type:** spaCy
- **Information about training algorithms, parameters, fairness
constraints or other applied approaches, and features:** For information on the training workflow see p.4-5 of LatinCy: Synthetic Trained Pipelines for Latin NLP
(https://arxiv.org/pdf/2305.04365v1)
- **Paper or other resource for more information:** *Burns, P.J. 2023.
"LatinCy: Synthetic Trained Pipelines for Latin NLP." arXiv:2305.04365
\[cs.CL\]. http://arxiv.org/abs/2305.04365.*
- **License:** *MIT*
- **Where to send questions or comments about the model:**
https://diyclassics.github.io/
Intended Use
- Primary intended uses: Morphological analysis, POS-Tagging,
Lemmatizing, Parsing, NER
- Primary intended users: Classical Scholars
- Out-of-scope use cases: unknown
Data, Limitations, and Recommendations
- Data selection for training: Training data consists of latin
UD-Treebanks, Wikipedia and OSCAR sentence data, the CC-100 Latin
dataset and the Herodotos Project NER dataset
- Data selection for evaluation: Evaluation was done according to the
spaCy workflow and is documented in the meta.json file found in the
repository
(https://huggingface.co./latincy/la_core_web_lg/blob/main/meta.json)
- Limitations: unknown |