Benchmark
MultiBERTs
A collection of BERT models trained with multiple different random seeds, used to study the influence of random seeds on model performance.
Timeline (last 90 days)
Oct 19
Case studies on the thousand-seed CIFAR-10 model library and MultiBERTs validated the formula with real seed distributions, with error within 0.05 in that range.
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