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

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

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Safetensors

Model size

277M params

Tensor type

I64

F32

Inference Providers NEW

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-ru

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

Evaluation results

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

86.300
Dutch Test accuracy on Universal Dependencies v2.8
self-reported

85.700
German Test accuracy on Universal Dependencies v2.8
self-reported

81.400
Italian Test accuracy on Universal Dependencies v2.8
self-reported

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

85.300
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

87.800
Russian Test accuracy on Universal Dependencies v2.8
self-reported

97.800
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

88.900
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

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

87.200

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