XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Belarusian
This model is part of our paper called:
- Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages
Check the Space for more details.
Usage
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-be")
model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-be")
- Downloads last month
- 118
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Dataset used to train wietsedv/xlm-roberta-base-ft-udpos28-be
Space using wietsedv/xlm-roberta-base-ft-udpos28-be 1
Evaluation results
- English Test accuracy on Universal Dependencies v2.8self-reported77.500
- Dutch Test accuracy on Universal Dependencies v2.8self-reported80.700
- German Test accuracy on Universal Dependencies v2.8self-reported79.400
- Italian Test accuracy on Universal Dependencies v2.8self-reported80.100
- French Test accuracy on Universal Dependencies v2.8self-reported81.200
- Spanish Test accuracy on Universal Dependencies v2.8self-reported83.600
- Russian Test accuracy on Universal Dependencies v2.8self-reported95.300
- Swedish Test accuracy on Universal Dependencies v2.8self-reported85.900
- Norwegian Test accuracy on Universal Dependencies v2.8self-reported80.000
- Danish Test accuracy on Universal Dependencies v2.8self-reported84.300