BeardedMonster/afriberta-large-masakhaner2-lug

afriberta-large fine-tuned on masakhaner2 (lug)

Fine-tuned from castorini/afriberta_large on masakhaner2, lug protocol, over 1 language(s): lug

setting	value
epochs	50
learning rate	5e-05
batch size	32
max length	256
metric	span_f1
mean score	0.8608

Per-language scores are in metrics.json.

Loading

from transformers import AutoTokenizer, AutoModelForTokenClassification
tok = AutoTokenizer.from_pretrained("BeardedMonster/afriberta-large-masakhaner2-lug")
model = AutoModelForTokenClassification.from_pretrained("BeardedMonster/afriberta-large-masakhaner2-lug")

id2label is set, so predictions decode straight to tag names.

Provenance and limits

Produced by this project's benchmark harness, which reproduces the published MasakhaNER 2.0 baselines to within ~0.25 F1, so these numbers are calibrated rather than ad hoc. Scores come from a single run; the baseline papers average over 5, so treat small differences as noise.

The base model's own licence and terms govern any derivative use — check castorini/afriberta_large before relying on this checkpoint.