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

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

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Token Classification

This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

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

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

Evaluation results

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

77.200
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

75.200
German Test accuracy on Universal Dependencies v2.8
self-reported

73.200
Italian Test accuracy on Universal Dependencies v2.8
self-reported

68.900
French Test accuracy on Universal Dependencies v2.8
self-reported

74.000
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

75.100
Russian Test accuracy on Universal Dependencies v2.8
self-reported

70.300
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

78.900
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

74.300
Danish Test accuracy on Universal Dependencies v2.8
self-reported

73.400

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