Romanian DistilBERT

This repository contains the uncased Romanian DistilBERT (named Distil-RoBERT-base in the paper). The teacher model used for distillation is: readerbench/RoBERT-base .

The model was introduced in this paper . The adjacent code can be found here .

Usage

from transformers import AutoTokenizer, AutoModel

# load the tokenizer and the model
tokenizer = AutoTokenizer.from_pretrained("racai/distilbert-base-romanian-uncased")
model = AutoModel.from_pretrained("racai/distilbert-base-romanian-uncased")

# tokenize a test sentence
input_ids = tokenizer.encode("aceasta este o propoziție de test.", add_special_tokens=True, return_tensors="pt")

# run the tokens trough the model
outputs = model(input_ids)

print(outputs)

Model Size

It is 35% smaller than its teacher RoBERT-base .

Evaluation

We evaluated the model in comparison with the RoBERT-base on 5 Romanian tasks:

• UPOS : Universal Part of Speech (F1-macro)
• XPOS : Extended Part of Speech (F1-macro)
• NER : Named Entity Recognition (F1-macro)
• SAPN : Sentiment Anlaysis - Positive vs Negative (Accuracy)
• SAR : Sentiment Analysis - Rating (F1-macro)
• DI : Dialect identification (F1-macro)
• STS : Semantic Textual Similarity (Pearson)

BibTeX entry and citation info

@article{avram2021distilling,
  title={Distilling the Knowledge of Romanian BERTs Using Multiple Teachers},
  author={Andrei-Marius Avram and Darius Catrina and Dumitru-Clementin Cercel and Mihai Dascălu and Traian Rebedea and Vasile Păiş and Dan Tufiş},
  journal={ArXiv},
  year={2021},
  volume={abs/2112.12650}
}