yordep

Kola9INE/yordep

yordep is a machine learning model from Kola9INE. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

Downloads · 30 days

Access

Public

Updated Oct 19, 2025

Repo size

449 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

Other217 MB · 64%

At a glance

License: apache-2.0
Access: Public
Created: Oct 13, 2025
Updated: Oct 19, 2025
SHA: 1d31a484

Datasets

universal-dependencies/universal_dependencies

Model card

From the Hugging Face model README

Feature	Description
Name	`yo_yordep`
Version	`0.1.0`
spaCy	`>=3.8.7,<3.9.0`
Default Pipeline	`tok2vec`, `tagger`, `parser`, `morphologizer`
Components	`tok2vec`, `tagger`, `parser`, `morphologizer`
Vectors	151125 keys, 151125 unique vectors (300 dimensions)
Sources	`Dataset: https://github.com/UniversalDependencies/UD_Yoruba-YTB` `Embeddings: [FastText](https://fasttext.cc/docs/en/crawl-vectors.html)`
License	`apache-2.0`
Author	`Kolawole Lawal`

Label Scheme

<details> <summary>View label scheme (154 labels for 3 components)</summary>

Component	Labels
`tagger`	`ADJ`, `ADJ__Case=Acc\|Number=Sing\|Person=1\|PronType=Prs`, `ADJ__Case=Nom\|Number=Sing\|Person=3\|PronType=Prs`, `ADJ__NumType=Ord`, `ADJ__Typo=Yes`, `ADP`, `ADP__Case=Acc\|Number=Sing\|Person=1\|PronType=Prs`, `ADP__NumType=Card`, `ADP__Typo=Yes`, `ADV`, `ADV__Typo=Yes`, `AUX`, `AUX__Case=Nom\|Number=Plur\|Person=1\|PronType=Prs`, `AUX__Case=Nom\|Number=Sing\|Person=1\|PronType=Prs`, `AUX__Case=Nom\|Number=Sing\|Person=3\|PronType=Prs`, `AUX__Typo=Yes`, `CCONJ`, `CCONJ__Case=Acc\|Number=Sing\|Person=1\|PronType=Prs`, `CCONJ__PronType=Ind`, `CCONJ__Typo=Yes`, `DET`, `DET__Number=Plur\|PronType=Dem`, `NOUN`, `NOUN__Case=Acc\|Number=Sing\|Person=1\|PronType=Prs`, `NOUN__Case=Nom\|Number=Sing\|Person=1\|PronType=Prs`, `NOUN__Typo=Yes`, `NUM__Case=Acc\|Number=Sing\|Person=1\|PronType=Prs`, `NUM__NumType=Card`, `PART`, `PART__Typo=Yes`, `PRON`, `PRON__Case=Acc\|Number=Plur\|Person=1\|PronType=Prs`, `PRON__Case=Acc\|Number=Plur\|Person=2\|PronType=Prs`, `PRON__Case=Acc\|Number=Plur\|Person=3\|PronType=Prs`, `PRON__Case=Acc\|Number=Sing\|Person=1\|PronType=Prs`, `PRON__Case=Acc\|Number=Sing\|Person=2\|PronType=Prs`, `PRON__Case=Acc\|Number=Sing\|Person=3\|PronType=Prs`, `PRON__Case=Gen\|Number=Plur\|Person=2\|PronType=Prs`, `PRON__Case=Gen\|Number=Plur\|Person=3\|PronType=Prs`, `PRON__Case=Gen\|Number=Sing\|Person=2\|PronType=Prs`, `PRON__Case=Gen\|Number=Sing\|Person=2\|PronType=Prs\|Typo=Yes`, `PRON__Case=Gen\|Number=Sing\|Person=3\|PronType=Prs`, `PRON__Case=Nom\|Number=Plur\|Person=1\|PronType=Prs`, `PRON__Case=Nom\|Number=Plur\|Person=2\|PronType=Prs`, `PRON__Case=Nom\|Number=Plur\|Person=3\|PronType=Prs`, `PRON__Case=Nom\|Number=Sing\|Person=1\|PronType=Prs`, `PRON__Case=Nom\|Number=Sing\|Person=2\|PronType=Prs`, `PRON__Case=Nom\|Number=Sing\|Person=3\|PronType=Prs`, `PRON__PronType=Dem`, `PRON__PronType=Emp`, `PRON__PronType=Ind`, `PRON__PronType=Int`, `PRON__PronType=Int\|Typo=Yes`, `PRON__PronType=Rel`, `PRON__PronType=Rel\|Typo=Yes`, `PROPN`, `PROPN__Case=Nom\|Number=Plur\|Person=1\|PronType=Prs`, `PROPN__Typo=Yes`, `PUNCT`, `SCONJ`, `SCONJ__Typo=Yes`, `SYM`, `VERB`, `VERB__Typo=Yes`, `X`
`parser`	`ROOT`, `acl`, `advcl`, `advmod`, `amod`, `aux`, `case`, `cc`, `ccomp`, `compound`, `compound:svc`, `conj`, `cop`, `dep`, `det`, `expl`, `fixed`, `mark`, `nmod`, `nsubj`, `obj`, `obl`, `parataxis`, `punct`
`morphologizer`	`POS=ADP`, `POS=NOUN`, `POS=DET`, `POS=VERB`, `Number=Plur\|POS=DET\|PronType=Dem`, `POS=CCONJ`, `POS=PUNCT`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `POS=ADJ`, `POS=AUX`, `POS=SCONJ`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `POS=ADV`, `NumType=Ord\|POS=ADJ`, `POS=PRON\|PronType=Rel`, `POS=PRON`, `Case=Gen\|Number=Sing\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Nom\|Number=Sing\|POS=AUX\|Person=3\|PronType=Prs`, `NumType=Card\|POS=NUM`, `Case=Gen\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=3\|PronType=Prs`, `POS=PART`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Nom\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `POS=PRON\|PronType=Emp`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `Case=Gen\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `POS=PRON\|PronType=Ind`, `POS=NOUN\|Typo=Yes`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `POS=PROPN`, `Case=Acc\|Number=Sing\|POS=PRON\|Person=1\|PronType=Prs`, `POS=PRON\|PronType=Int`, `Case=Gen\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `POS=X`, `Case=Nom\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs`, `POS=ADP\|Typo=Yes`, `POS=PRON\|PronType=Dem`, `Case=Acc\|Number=Plur\|POS=PRON\|Person=2\|PronType=Prs`, `POS=PROPN\|Typo=Yes`, `POS=AUX\|Typo=Yes`, `POS=ADJ\|Typo=Yes`, `Case=Gen\|Number=Sing\|POS=PRON\|Person=2\|PronType=Prs\|Typo=Yes`, `POS=CCONJ\|Typo=Yes`, `POS=ADV\|Typo=Yes`, `POS=PRON\|PronType=Rel\|Typo=Yes`, `POS=SCONJ\|Typo=Yes`, `POS=VERB\|Typo=Yes`, `POS=CCONJ\|PronType=Ind`, `POS=PRON\|PronType=Int\|Typo=Yes`, `POS=PART\|Typo=Yes`, `Case=Nom\|Number=Plur\|POS=AUX\|Person=1\|PronType=Prs`, `Case=Nom\|Number=Sing\|POS=ADJ\|Person=3\|PronType=Prs`, `NumType=Card\|POS=ADP`, `Case=Nom\|Number=Sing\|POS=NOUN\|Person=1\|PronType=Prs`, `Case=Acc\|Number=Sing\|POS=ADP\|Person=1\|PronType=Prs`, `Case=Acc\|Number=Sing\|POS=NOUN\|Person=1\|PronType=Prs`, `Case=Nom\|Number=Plur\|POS=PROPN\|Person=1\|PronType=Prs`, `Case=Nom\|Number=Sing\|POS=AUX\|Person=1\|PronType=Prs`, `POS=SYM`, `Case=Acc\|Number=Sing\|POS=NUM\|Person=1\|PronType=Prs`, `Case=Acc\|Number=Sing\|POS=ADJ\|Person=1\|PronType=Prs`, `Case=Acc\|Number=Sing\|POS=CCONJ\|Person=1\|PronType=Prs`

</details>

METRICS

These metrics were gotten using the spacy evaluate CLI

Type	Score
`TAG_ACC`	88.51
`POS_ACC`	89.84
`TAG_MICRO_P`	0.00
`TAG_MICRO_R`	0.00
`TAG_MICRO_F`	0.00
`DEP_UAS`	70.61
`DEP_LAS`	59.17
`SENTS_P`	82.86
`SENTS_R`	91.58
`SENTS_F`	87.00
`MORPH_ACC`	96.46
`TOK2VEC_LOSS`	94585.70
`TAGGER_LOSS`	5570.00
`PARSER_LOSS`	63924.84
`MORPHOLOGIZER_LOSS`	5570.00

NOTE:

This model was trained using the dataset referenced above which consists of 318 sentences, although incorporated with the FastText.
https://yordepan.streamlit.app/
Future development will include lemmatizer.

USAGE:

Download with pip install https://huggingface.co/Kola9INE/yordep/resolve/main/yo_yordep-0.1.0.tar.gz into your virtual environment.
import spacy.
Load model with yor_nlp = spacy.load("yo_yordep")

CAVEAT!!!

This model was initialized in the following pipelines as displayed in the Components or Default Pipelines. It is not trained in the lemmatizer pipeline and therefore cannot lemmatize!

License: apache-2.0
Languages: yo
Created: Oct 13, 2025
Updated: Oct 19, 2025