language: ro
bert-base-romanian-cased-v1
The BERT base, cased model for Romanian, trained on a 15GB corpus, version
How to use
from transformers import AutoTokenizer, AutoModel
import torch
# load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("dumitrescustefan/bert-base-romanian-cased-v1")
model = AutoModel.from_pretrained("dumitrescustefan/bert-base-romanian-cased-v1")
# tokenize a sentence and run through the model
input_ids = torch.tensor(tokenizer.encode("Acesta este un test.", add_special_tokens=True)).unsqueeze(0) # Batch size 1
outputs = model(input_ids)
# get encoding
last_hidden_states = outputs[0] # The last hidden-state is the first element of the output tuple
Evaluation
Evaluation is performed on Universal Dependencies Romanian RRT UPOS, XPOS and LAS, and on a NER task based on RONEC. Details, as well as more in-depth tests not shown here, are given in the dedicated evaluation page.
The baseline is the Multilingual BERT model bert-base-multilingual-(un)cased, as at the time of writing it was the only available BERT model that works on Romanian.
| Model | UPOS | XPOS | NER | LAS |
|---|---|---|---|---|
| bert-base-multilingual-cased | 97.87 | 96.16 | 84.13 | 88.04 |
| bert-base-romanian-cased-v1 | 98.00 | 96.46 | 85.88 | 89.69 |
Corpus
The model is trained on the following corpora (stats in the table below are after cleaning):
| Corpus | Lines(M) | Words(M) | Chars(B) | Size(GB) | |----------- |:--------: |:--------: |:--------: |:--------: | | OPUS | 55.05 | 635.04 | 4.045 | 3.8 | | OSCAR | 33.56 | 1725.82 | 11.411 | 11 | | Wikipedia | 1.54 | 60.47 | 0.411 | 0.4 | | Total | 90.15 | 2421.33 | 15.867 | 15.2 |
Acknowledgements
- We'd like to thank Sampo Pyysalo from TurkuNLP for helping us out with the compute needed to pretrain the v1.0 BERT models. He's awesome!