metadata

language: multilingual
thumbnail: null

DISTILBERT 🌎 + Typo Detection ✍❌✍✔

distilbert-base-multilingual-cased fine-tuned on GitHub Typo Corpus for typo detection (using NER style)

Details of the downstream task (Typo detection as NER)

Dataset: GitHub Typo Corpus 📚 for 15 languages
Fine-tune script on NER dataset provided by Huggingface 🏋️‍♂️

Metrics on test set 📋

Metric	# score
F1	93.51
Precision	96.08
Recall	91.06

Model in action 🔨

Fast usage with pipelines 🧪

from transformers import pipeline

typo_checker = pipeline(
    "ner",
    model="mrm8488/distilbert-base-multi-cased-finetuned-typo-detection",
    tokenizer="mrm8488/distilbert-base-multi-cased-finetuned-typo-detection"
)

result = typo_checker("Adddd validation midelware")
result[1:-1]

# Output:
[{'entity': 'ok', 'score': 0.7128152847290039, 'word': 'add'},
 {'entity': 'typo', 'score': 0.5388424396514893, 'word': '##dd'},
 {'entity': 'ok', 'score': 0.94792640209198, 'word': 'validation'},
 {'entity': 'typo', 'score': 0.5839331746101379, 'word': 'mid'},
 {'entity': 'ok', 'score': 0.5195121765136719, 'word': '##el'},
 {'entity': 'ok', 'score': 0.7222476601600647, 'word': '##ware'}]

It works🎉! We typed wrong Add and middleware

Created by Manuel Romero/@mrm8488

Made with ♥ in Spain