XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Chinese
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-zh")
model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-zh")
- Downloads last month
- 9
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-zh
Space using wietsedv/xlm-roberta-base-ft-udpos28-zh 1
Evaluation results
- English Test accuracy on Universal Dependencies v2.8self-reported60.200
- Dutch Test accuracy on Universal Dependencies v2.8self-reported56.900
- German Test accuracy on Universal Dependencies v2.8self-reported57.500
- Italian Test accuracy on Universal Dependencies v2.8self-reported57.300
- French Test accuracy on Universal Dependencies v2.8self-reported54.100
- Spanish Test accuracy on Universal Dependencies v2.8self-reported54.400
- Russian Test accuracy on Universal Dependencies v2.8self-reported69.600
- Swedish Test accuracy on Universal Dependencies v2.8self-reported61.800
- Norwegian Test accuracy on Universal Dependencies v2.8self-reported60.300
- Danish Test accuracy on Universal Dependencies v2.8self-reported62.600