File size: 1,449 Bytes
f565181 ae10e58 f565181 ae10e58 f565181 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | ---
language: luo
license: apache-2.0
tags:
- pos-tagging
- token-classification
- dholuo
- afroxlmr
- masakhane
datasets:
- kencorpus
model-index:
- name: Dholuo POS Tagger (AfroXLM-R)
results:
- task:
type: token-classification
name: POS Tagging
dataset:
name: KenCorpus (Dholuo)
type: kencorpus
split: test
metrics:
- name: Accuracy
type: accuracy
value: 0.7167
- name: Macro F1
type: f1
value: 0.5338
- name: Weighted F1
type: f1
value: 0.7248
---
# Dholuo POS Tagger (AfroXLM-R)
This model is a fine-tuned version of `masakhane/luo-pos-tagger-afroxlmr`
trained on KenCorpus POS-tagged Dholuo data.
## Evaluation Results
The model was evaluated on the KenCorpus Dholuo POS test set.
| Metric | Value |
|---------------|-------|
| Accuracy | 0.7167 |
| Macro F1 | 0.5338 |
| Weighted F1 | 0.7248 |
### Per-tag Performance (Test Set)
- Strong performance on **NOUN (F1 ≈ 0.86)** and **VERB (F1 ≈ 0.84)**
- Moderate performance on function words (ADP, PRON, DET)
- Rare tags (INTJ, PART, PUNCT) have near-zero scores due to very low support
## Usage
```python
from transformers import AutoTokenizer, AutoModelForTokenClassification
model = AutoModelForTokenClassification.from_pretrained(
"Omballa/dholuo-pos-afroxlmr-finetuned"
)
tokenizer = AutoTokenizer.from_pretrained(
"Omballa/dholuo-pos-afroxlmr-finetuned"
)
|