Architecture:
Utilizes a transformer encoder, optimized for capturing
context
and relationships
within the text.
Focus:
Tailored for Hindi language medical text classification,
addressing the need for
processing regional language data in medical applications.
Features:
Leverages pre-trained language models (e.g., BERT,
RoBERTa)
fine-tuned for the
specific classification task.
Tools:
Python, TensorFlow/Keras, Hugging Face
Transformers.
