metadata
language: it
tags:
- bert
- sarcasm-detection
- text-classification
widget:
- text: Auto, stop a diesel e benzina dal 2035. Ecco cosa cambia per i consumatori
Italian Sarcasm Detector
Italian Sarcasm Detector is a text classification model built to detect sarcasm from news article titles. It is fine-tuned on dbmdz/bert-base-italian-uncased and the training data consists of scraped data from Italian non-sarcastic newspaper (Il Giornale) and sarcastic newspaper (Lercio).
Labels: 0 -> Not Sarcastic; 1 -> Sarcastic
Training Data
Scraped data:
- Italian non-sarcastic news from Il Giornale
- Italian sarcastic news from Lercio
Codebase:
- Git Repo: Official repository
Example of classification
from transformers import AutoModelForSequenceClassification
from transformers import AutoTokenizer
import string
def preprocess_data(text: str) -> str:
return text.lower().translate(str.maketrans("", "", string.punctuation)).strip()
MODEL_PATH = "helinivan/italian-sarcasm-detector"
tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
model = AutoModelForSequenceClassification.from_pretrained(MODEL_PATH)
text = "Auto, stop a diesel e benzina dal 2035. Ecco cosa cambia per i consumatori"
tokenized_text = tokenizer([preprocess_data(text)], padding=True, truncation=True, max_length=512, return_tensors="pt")
output = model(**tokenized_text)
probs = output.logits.softmax(dim=-1).tolist()[0]
confidence = max(probs)
prediction = probs.index(confidence)
results = {"is_sarcastic": prediction, "confidence": confidence}
Output:
{'is_sarcastic': 1, 'confidence': 0.9999909400939941}
Performance
Model-Name | F1 | Precision | Recall | Accuracy |
---|---|---|---|---|
helinivan/english-sarcasm-detector | 94.48 | 94.46 | 94.51 | 94.48 |
helinivan/italian-sarcasm-detector | 92.99 | 92.77 | 93.24 | 93.42 |
helinivan/multilingual-sarcasm-detector | 90.91 | 91.51 | 90.44 | 91.55 |
helinivan/dutch-sarcasm-detector | 89.04 | 90.16 | 88.09 | 91.43 |