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

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

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Token Classification

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

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

Evaluation results

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

67.400
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

61.500
German Test accuracy on Universal Dependencies v2.8
self-reported

66.900
Italian Test accuracy on Universal Dependencies v2.8
self-reported

64.800
French Test accuracy on Universal Dependencies v2.8
self-reported

61.700
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

60.100
Russian Test accuracy on Universal Dependencies v2.8
self-reported

68.100
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

68.400
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

64.100
Danish Test accuracy on Universal Dependencies v2.8
self-reported

66.400

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