XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Sanskrit
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-sa")
model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-sa")
- Downloads last month
- 118
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Dataset used to train wietsedv/xlm-roberta-base-ft-udpos28-sa
Space using wietsedv/xlm-roberta-base-ft-udpos28-sa 1
Evaluation results
- English Test accuracy on Universal Dependencies v2.8self-reported31.400
- Dutch Test accuracy on Universal Dependencies v2.8self-reported28.400
- German Test accuracy on Universal Dependencies v2.8self-reported32.300
- Italian Test accuracy on Universal Dependencies v2.8self-reported28.300
- French Test accuracy on Universal Dependencies v2.8self-reported28.100
- Spanish Test accuracy on Universal Dependencies v2.8self-reported28.500
- Russian Test accuracy on Universal Dependencies v2.8self-reported37.500
- Swedish Test accuracy on Universal Dependencies v2.8self-reported35.700
- Norwegian Test accuracy on Universal Dependencies v2.8self-reported32.000
- Danish Test accuracy on Universal Dependencies v2.8self-reported32.700