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# Latin (demo) model for [BabyLemmatizer](https://github.com/asahala/BabyLemmatizer)
This is a demo model for Latin based on [PROIEL data](https://github.com/UniversalDependencies/UD_Latin-PROIEL). Model uses alphabetic tokenization and requires BabyLemmatizer 2.1 or newer.
## Evaluation results
```
Neural Net Evaluation
COMPONENT AVG CI MODEL0
POS-tagger 95.38 ±0.00 95.38
Lemmatizer 96.47 ±0.00 96.47
Combined 94.39 ±0.00 94.39
POS-tagger OOV 87.12 ±0.00 87.12
Lemmatizer OOV 82.70 ±0.00 82.70
Combined OOV 80.28 ±0.00 80.28
-----------------------------------------------
OOV input rate 10.58 10.58
Post-correct Evaluation
COMPONENT AVG CI MODEL0
POS-tagger 95.38 ±0.00 95.38
Lemmatizer 96.49 ±0.00 96.49
Combined 94.42 ±0.00 94.42
POS-tagger OOV 87.12 ±0.00 87.12
Lemmatizer OOV 82.70 ±0.00 82.70
Combined OOV 80.28 ±0.00 80.28
-----------------------------------------------
OOV input rate 10.58 10.58
```
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