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")

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Inference Examples

Token Classification

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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 v2.8
self-reported

77.500
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

80.700
German Test accuracy on Universal Dependencies v2.8
self-reported

79.400
Italian Test accuracy on Universal Dependencies v2.8
self-reported

80.100
French Test accuracy on Universal Dependencies v2.8
self-reported

81.200
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

83.600
Russian Test accuracy on Universal Dependencies v2.8
self-reported

95.300
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

85.900
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

80.000
Danish Test accuracy on Universal Dependencies v2.8
self-reported

84.300

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