namisan/mt-dnn
Multi-Task Deep Neural Networks for Natural Language Understanding
Built on BERT with shared encoder layers across multiple NLU tasks, the framework enables joint training on diverse datasets (GLUE, SQuAD, NER) while supporting adversarial training techniques like SMART and f-divergence regularization for improved robustness. Supports knowledge distillation, domain adaptation, sequence labeling, and question answering tasks with optimizations including gradient accumulation and FP16 training for efficient GPU utilization.
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