XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Serbian

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-sr")
model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-sr")

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Inference Examples

Token Classification

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Dataset used to train wietsedv/xlm-roberta-base-ft-udpos28-sr

Space using wietsedv/xlm-roberta-base-ft-udpos28-sr 1

Evaluation results

English Test accuracy on Universal Dependencies v2.8
self-reported

82.900
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

84.000
German Test accuracy on Universal Dependencies v2.8
self-reported

82.700
Italian Test accuracy on Universal Dependencies v2.8
self-reported

82.600
French Test accuracy on Universal Dependencies v2.8
self-reported

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

87.300
Russian Test accuracy on Universal Dependencies v2.8
self-reported

90.600
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

85.500
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

79.000
Danish Test accuracy on Universal Dependencies v2.8
self-reported

84.100

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