📢Day 20/100: Overcoming Tokenization Challenges
Tokenization is critical for NLP tasks like Named Entity Recognition.
Key steps:
1️⃣ Aligning tokens with Amharic text.
2️⃣ Preserving the relationship between tokens and their labels.
3️⃣ Using model-specific tokenizers (XLM-Roberta, mBERT).
💡 Takeaway: Tokenization errors can significantly impact the accuracy of entity recognition models.
#AI #Tokenization #AmharicNLP #FintechInnovation
Tokenization is critical for NLP tasks like Named Entity Recognition.
Key steps:
1️⃣ Aligning tokens with Amharic text.
2️⃣ Preserving the relationship between tokens and their labels.
3️⃣ Using model-specific tokenizers (XLM-Roberta, mBERT).
💡 Takeaway: Tokenization errors can significantly impact the accuracy of entity recognition models.
#AI #Tokenization #AmharicNLP #FintechInnovation