---
language: "nl"
tags:
- bert
- sarcasm-detection
- text-classification
widget:
- text: "We deden een man een nacht in een vat met cola en nu is hij dood"
---

# Dutch Sarcasm Detector

Dutch Sarcasm Detector is a text classification model built to detect sarcasm from news article titles. It is fine-tuned on [GroNLP/bert-base-dutch-cased](https://huggingface.co/GroNLP/bert-base-dutch-cased) and the training data consists of ready-made dataset available on Kaggle as well as scraped data from Dutch sarcastic newspaper (De Speld).


<b>Labels</b>: 
0 -> Not Sarcastic;
1 -> Sarcastic

## Source Data
	  
Datasets:
- Dutch non-sarcastic data: [Kaggle: Dutch News Articles](https://www.kaggle.com/datasets/maxscheijen/dutch-news-articles)

Scraped data:
- Dutch sarcastic news from [De Speld](https://speld.nl)


## Training Dataset
- [helinivan/sarcasm_headlines_multilingual](https://huggingface.co/datasets/helinivan/sarcasm_headlines_multilingual)

## Codebase:
- Git Repo: [Official repository](https://github.com/helinivan/multilingual-sarcasm-detector)

---

## Example of classification

```python
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/dutch-sarcasm-detector"

tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
model = AutoModelForSequenceClassification.from_pretrained(MODEL_PATH)

text = "We deden een man een nacht in een vat met cola en nu is hij dood"
tokenized_text = tokenizer([preprocess_data(text)], padding=True, truncation=True, max_length=256, 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': 0.8915400505065918}
```

## Performance
| Model-Name | F1 | Precision | Recall | Accuracy 
| ------------- |:-------------| -----| -----| ----| 
| [helinivan/english-sarcasm-detector ](https://huggingface.co/helinivan/english-sarcasm-detector)| 92.38 | 92.75 | 92.38 | 92.42
| [helinivan/italian-sarcasm-detector ](https://huggingface.co/helinivan/italian-sarcasm-detector) | 88.26 | 87.66 | 89.66 | 88.69
| [helinivan/multilingual-sarcasm-detector ](https://huggingface.co/helinivan/multilingual-sarcasm-detector) | 87.23 | 88.65 | 86.33 | 88.30
| [helinivan/dutch-sarcasm-detector ](https://huggingface.co/helinivan/dutch-sarcasm-detector) | **83.02** | 84.27 | 82.01 | 86.81