🤗 + 📚 dbmdz Turkish ELECTRA model
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources a cased ELECTRA base model for Turkish 🎉
Turkish ELECTRA model
We release a base ELECTRA model for Turkish, that was trained on the same data as BERTurk.
ELECTRA is a new method for self-supervised language representation learning. It can be used to
pre-train transformer networks using relatively little compute. ELECTRA models are trained to
distinguish "real" input tokens vs "fake" input tokens generated by another neural network, similar to
the discriminator of a GAN.
More details about ELECTRA can be found in the
ICLR paper
or in the
official ELECTRA repository on GitHub.
Stats
The current version of the model is trained on a filtered and sentence
segmented version of the Turkish
OSCAR corpus,
a recent Wikipedia dump, various
OPUS corpora and a
special corpus provided by
Kemal Oflazer.
The final training corpus has a size of 35GB and 44,04,976,662 tokens.
Thanks to Google's TensorFlow Research Cloud (TFRC) we could train a cased model
on a TPU v3-8 for 1M steps.
Model weights
Transformers
compatible weights for both PyTorch and TensorFlow are available.
Usage
With Transformers >= 2.8 our ELECTRA base cased model can be loaded like:
1from transformers import AutoModelWithLMHead, AutoTokenizer
2
3tokenizer = AutoTokenizer.from_pretrained("dbmdz/electra-base-turkish-cased-discriminator")
4model = AutoModelWithLMHead.from_pretrained("dbmdz/electra-base-turkish-cased-discriminator")
Results
For results on PoS tagging or NER tasks, please refer to
this repository.
Huggingface model hub
All models are available on the
Huggingface model hub.
Contact (Bugs, Feedback, Contribution and more)
For questions about our ELECTRA models just open an issue
here 🤗
Acknowledgments
Thanks to
Kemal Oflazer for providing us
additional large corpora for Turkish. Many thanks to Reyyan Yeniterzi for providing
us the Turkish NER dataset for evaluation.
Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC).
Thanks for providing access to the TFRC ❤️
Thanks to the generous support from the
Hugging Face team,
it is possible to download both cased and uncased models from their S3 storage 🤗
