Fine-tuning a small six-head Nepali BERT on a mixed news and social media corpus improved average intrinsic purity from 0.65 to 0.78 and downstream F1 from 0.74 to 0.81, while still trailing the larger NepaliBERT model.
Dependency-based word embeddings
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Fine-Tuning Small Embeddings for Elevated Performance
Fine-tuning a small six-head Nepali BERT on a mixed news and social media corpus improved average intrinsic purity from 0.65 to 0.78 and downstream F1 from 0.74 to 0.81, while still trailing the larger NepaliBERT model.