XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Arabic
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-ar")
model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-ar")
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Dataset used to train wietsedv/xlm-roberta-base-ft-udpos28-ar
Space using wietsedv/xlm-roberta-base-ft-udpos28-ar 1
Evaluation results
- English Test accuracy on Universal Dependencies v2.8self-reported62.800
- Dutch Test accuracy on Universal Dependencies v2.8self-reported63.500
- German Test accuracy on Universal Dependencies v2.8self-reported63.800
- Italian Test accuracy on Universal Dependencies v2.8self-reported60.200
- French Test accuracy on Universal Dependencies v2.8self-reported58.500
- Spanish Test accuracy on Universal Dependencies v2.8self-reported64.900
- Russian Test accuracy on Universal Dependencies v2.8self-reported77.200
- Swedish Test accuracy on Universal Dependencies v2.8self-reported68.500
- Norwegian Test accuracy on Universal Dependencies v2.8self-reported64.600
- Danish Test accuracy on Universal Dependencies v2.8self-reported66.100