Scalability in NLP
The discussion highlights the importance of scalability, noting that more layers, data, and training steps lead to better results. Significant improvements were observed in accuracy across various datasets, particularly with the Lexmert model outperforming previous benchmarks. Additionally, the need for enhanced evaluation methods is emphasized, as current tests may not adequately assess the generalization capabilities of large models.In this clip
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NLP Highlights
107 - Multi-Modal Transformers, with Hao Tan and Mohit Bansal
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