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

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

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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-te

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

Evaluation results

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

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

68.000
German Test accuracy on Universal Dependencies v2.8
self-reported

67.000
Italian Test accuracy on Universal Dependencies v2.8
self-reported

63.300
French Test accuracy on Universal Dependencies v2.8
self-reported

62.100
Spanish Test accuracy on Universal Dependencies v2.8
self-reported

63.100
Russian Test accuracy on Universal Dependencies v2.8
self-reported

71.000
Swedish Test accuracy on Universal Dependencies v2.8
self-reported

66.400
Norwegian Test accuracy on Universal Dependencies v2.8
self-reported

62.100
Danish Test accuracy on Universal Dependencies v2.8
self-reported

67.500

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