Description
xlm_roberta_base_finetuned_luganda is a ** Luganda RoBERTa** model obtained by fine-tuning xlm-roberta-base model on Luganda language texts. It provides better performance than the XLM-RoBERTa on named entity recognition datasets.
Specifically, this model is an xlm-roberta-base model that was fine-tuned on the Luganda corpus.
Predicted Entities
How to use
embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_luganda", "lg") \
.setInputCols("sentence", "token") \
.setOutputCol("embeddings")
val embeddings = XlmRoBertaEmbeddings.pretrained("xlm_roberta_base_finetuned_luganda", "lg")
.setInputCols("sentence", "token")
.setOutputCol("embeddings")
import nlu
nlu.load("lg.embed.xlm_roberta").predict("""Put your text here.""")
Model Information
| Model Name: | xlm_roberta_base_finetuned_luganda |
| Compatibility: | Spark NLP 3.3.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [token, sentence] |
| Output Labels: | [embeddings] |
| Language: | lg |
| Case sensitive: | true |
Data Source
https://huggingface.co/Davlan/xlm-roberta-base-finetuned-luganda
Benchmarking
## Eval results on Test set (F-score, average over 5 runs)
Dataset| XLM-R F1 | lg_roberta F1
-|-|-
[MasakhaNER](https://github.com/masakhane-io/masakhane-ner) | 79.69 | 84.70