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. 2023 Apr 14;4(4):100729. doi: 10.1016/j.patter.2023.100729

Table 4.

Comparison of test performance (and standard deviation) on the BIOSSES and BioASQ tasks with major layer-specific adaptation methods, all with BASE models

Pretraining setting Baseline Laye freeze Layerwise decay Layer reinit
BIOSSES

BERT 93.46 (0.96) 92.86 (0.88) 93.35 (0.78) 94.49 (0.88)
BERT (no NSP) 93.12 (1.04) 94.01 (0.99) 93.01 (1.07) 92.89 (0.91)
BERT (no NSP, single seq) 75.50 (3.00) 72.09 (2.86) 74.11 (3.51) 85.04 (2.69)
ELECTRA 80.24 (5.92) 83.06 (3.68) 83.55 (3.25) 88.74 (2.29)

BioASQ

BERT 87.56 (2.43) 90.50 (1.51) 88.29 (2.76) 81.28 (3.72)
BERT (no NSP) 83.57 (3.60) 87.07 (3.15) 86.07 (2.29) 83.64 (3.70)
BERT (no NSP, single seq) 85.64 (2.48) 88.64 (1.76) 88.50 (1.63) 80.79 (2.51)
ELECTRA 88.93 (3.87) 90.00 (4.16) 90.64 (2.60) 88.14 (2.21)

Highest performance for model (row).