roberta-large-finnish-v2 / train_tokenizer.py
aapot
Add tokenizer
0b21f29
from datasets import load_from_disk
from tokenizers import trainers, Tokenizer, normalizers, ByteLevelBPETokenizer
from transformers import AutoConfig, AutoTokenizer
model_dir = "./"
# load roberta-large config
config = AutoConfig.from_pretrained("roberta-large")
config.save_pretrained(model_dir)
# load dataset
dataset = load_from_disk("/researchdisk/training_dataset_full")
dataset = dataset["train"]
# Instantiate tokenizer
tokenizer = ByteLevelBPETokenizer()
def batch_iterator(batch_size=1000):
for i in range(0, len(dataset), batch_size):
yield dataset[i: i + batch_size]["text"]
# Customized training
tokenizer.train_from_iterator(batch_iterator(), vocab_size=config.vocab_size, min_frequency=2, special_tokens=[
"<s>",
"<pad>",
"</s>",
"<unk>",
"<mask>",
])
# Save files to disk
tokenizer.save(f"{model_dir}/tokenizer.json")
tokenizer = AutoTokenizer.from_pretrained(model_dir)
tokenizer.save_pretrained(model_dir)