H-Z-Ning/Senti-RoBERTa-Mini is a lightweight Chinese RoBERTa model fine-tuned specifically for assigning 1-to-5-star sentiment ratings to Chinese movie short reviews. Built on the HFL-Tencent hfl/chinese-roberta-wwm-ext checkpoint, it retains a small footprint and fast inference, making it ideal for resource-constrained deployments.

2. Model Facts

Item	Details
Task	Chinese text classification (sentiment / star rating)
Labels	5 classes (1 star – 5 stars)
Base model	hfl/chinese-roberta-wwm-ext
Dataset	Kaggle: Douban Movie Short Comments (2000 K)
Training framework	🤗 transformers + Trainer
Language	Simplified Chinese
Parameters	≈ 102 M (same as base model)

3. Quick Start

3.1 Install Dependencies

pip install transformers torch

3.2 One-Line Inference

python

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

repo = "H-Z-Ning/Senti-RoBERTa-Mini"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForSequenceClassification.from_pretrained(repo)

text = "这个导演真厉害。"
inputs = tok(text, return_tensors="pt", truncation=True, max_length=256)
with torch.no_grad():
    logits = model(**inputs).logits
pred = int(torch.argmax(logits, dim=-1).item()) + 1  # 1..5
print("predicted rating:", pred)

4.Training source code

senti-roberta-mini training source code

5. Training Details

Hyper-parameter	Value
Base model	hfl/chinese-roberta-wwm-ext
Training framework	🤗 transformers `Trainer`
Training set	150 000 samples (randomly drawn from 2000 K)
Validation set	15 000 samples (same random draw)
Test set	full original test set
Max sequence length	256
Training epochs	3
Batch size	32 (train) / 64 (eval)
Learning rate	2e-5
Optimizer	AdamW
Weight decay	0.01
Scheduler	linear warmup (warmup_ratio=0.1)
Precision	FP16
Best-model criterion	QWK (↑)
Training time	≈ 120 min on single P100 (FP16)
Logging interval	every 10 steps

6. Citation

bibtex

@misc{senti-roberta-mini-2025,
  title={Senti-RoBERTa-Mini: A Mini Chinese RoBERTa for Movie Review Rating},
  author={H-Z-Ning},
  year={2025},
  howpublished={\url{https://huggingface.co/H-Z-Ning/Senti-RoBERTa-Mini}}
}

7. License

This model is released under Apache-2.0. The base model hfl/chinese-roberta-wwm-ext is also Apache-2.0.

Community contributions and feedback are welcome! If you encounter any issues, please open an Issue or email the author.