Text Classification
Transformers
Safetensors
Vietnamese
xlm-roberta
vietnamese
vihsd
transfer
eacl-2027
hate-speech-detection
offensive-language
social-media
Instructions to use BaoNhan/cafebert-ViHSD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BaoNhan/cafebert-ViHSD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BaoNhan/cafebert-ViHSD")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BaoNhan/cafebert-ViHSD") model = AutoModelForSequenceClassification.from_pretrained("BaoNhan/cafebert-ViHSD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "CLEAN": { | |
| "precision": 0.9282169443459766, | |
| "recall": 0.943943763518385, | |
| "f1-score": 0.9360142984807864, | |
| "support": 5548.0 | |
| }, | |
| "OFFENSIVE": { | |
| "precision": 0.468, | |
| "recall": 0.2635135135135135, | |
| "f1-score": 0.3371757925072046, | |
| "support": 444.0 | |
| }, | |
| "HATE": { | |
| "precision": 0.550761421319797, | |
| "recall": 0.6308139534883721, | |
| "f1-score": 0.5880758807588076, | |
| "support": 688.0 | |
| }, | |
| "accuracy": 0.8664670658682635, | |
| "macro avg": { | |
| "precision": 0.6489927885552579, | |
| "recall": 0.6127570768400902, | |
| "f1-score": 0.6204219905822662, | |
| "support": 6680.0 | |
| }, | |
| "weighted avg": { | |
| "precision": 0.8587520157334578, | |
| "recall": 0.8664670658682635, | |
| "f1-score": 0.8603756864980032, | |
| "support": 6680.0 | |
| } | |
| } |