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metadata
language:
- fa
tags:
- persian
- sentence-completion
- text-classification
- bert
license: mit
datasets:
- MohammadJRanjbar/PersianPunc
metrics:
- f1
- accuracy
base_model:
- HooshvareLab/bert-base-parsbert-uncased
pipeline_tag: text-classification
Persian Sentence Completion Classifier
A BERT-based classifier that determines whether a Persian sentence is Complete or Incomplete.
Designed for use in ASR post-processing pipelines (e.g. after speech-to-text).
Usage
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
MODEL_ID = "MohammadJRanjbar/persian-sentence-completion"
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForSequenceClassification.from_pretrained(MODEL_ID)
model.eval()
label_map = {0: "Incomplete", 1: "Complete"}
def classify_sentences(sentences, batch_size=16):
results = []
for i in range(0, len(sentences), batch_size):
batch = sentences[i:i+batch_size]
inputs = tokenizer(batch, return_tensors="pt", padding=True,
truncation=True, max_length=128)
with torch.no_grad():
outputs = model(**inputs)
preds = torch.argmax(outputs.logits, dim=-1)
results.extend([label_map[p.item()] for p in preds])
return results
# Example
texts = ["امروز هوا خیلی عالی", "امروز هوا خیلی عالی است."]
print(classify_sentences(texts))
# → ['Incomplete', 'Complete']
Citation
If you use this model, please cite the following works:
@misc{kalahroodi2026persianpunclargescaledatasetbertbased,
title={PersianPunc: A Large-Scale Dataset and BERT-Based Approach for Persian Punctuation Restoration},
author={Mohammad Javad Ranjbar Kalahroodi and Heshaam Faili and Azadeh Shakery},
year={2026},
eprint={2603.05314},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2603.05314},
}
@misc{kalahroodi2025parsvoicelargescalemultispeakerpersian,
title = {ParsVoice: A Large-Scale Multi-Speaker Persian Speech Corpus for Text-to-Speech Synthesis},
author = {Mohammad Javad Ranjbar Kalahroodi and Heshaam Faili and Azadeh Shakery},
year = {2025},
eprint = {2510.10774},
archivePrefix = {arXiv},
primaryClass = {cs.SD},
url = {https://arxiv.org/abs/2510.10774},
}