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---
language:
- tr
tags:
- roberta
license: cc-by-nc-sa-4.0
datasets:
- oscar
---
# RoBERTa Turkish medium Character-level (uncased)
Pretrained model on Turkish language using a masked language modeling (MLM) objective. The model is uncased.
The pretrained corpus is OSCAR's Turkish split, but it is further filtered and cleaned.
Model architecture is similar to bert-medium (8 layers, 8 heads, and 512 hidden size). Tokenization algorithm is Character-level, which means that text is split by individual characters. Vocabulary size is 384.
The details and performance comparisons can be found at this paper:
https://arxiv.org/abs/2204.08832
## Note that this model does not include a tokenizer file, because it uses ByT5Tokenizer. The following code can be used for model loading and tokenization, example max length(1024) can be changed:
```
model = AutoModel.from_pretrained([model_path])
#for sequence classification:
#model = AutoModelForSequenceClassification.from_pretrained([model_path], num_labels=[num_classes])
tokenizer = ByT5Tokenizer.from_pretrained("google/byt5-small")
tokenizer.mask_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][0]
tokenizer.cls_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][1]
tokenizer.bos_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][1]
tokenizer.sep_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][2]
tokenizer.eos_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][2]
tokenizer.pad_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][3]
tokenizer.unk_token = tokenizer.special_tokens_map_extended['additional_special_tokens'][3]
tokenizer.model_max_length = 1024
```
### BibTeX entry and citation info
```bibtex
@misc{https://doi.org/10.48550/arxiv.2204.08832,
doi = {10.48550/ARXIV.2204.08832},
url = {https://arxiv.org/abs/2204.08832},
author = {Toraman, Cagri and Yilmaz, Eyup Halit and Şahinuç, Furkan and Ozcelik, Oguzhan},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Impact of Tokenization on Language Models: An Analysis for Turkish},
publisher = {arXiv},
year = {2022},
copyright = {Creative Commons Attribution Non Commercial Share Alike 4.0 International}
}
``` |