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. 2022 Sep 23;11:e75600. doi: 10.7554/eLife.75600

Table 3. Top 10 best performing hyperparameter combinations that advanced to fine-tuning.

See Materials and methods and Table 1 for a detailed description of the hyperparameters.

λ1 λ2 β ρ Activation Learn rate γ Optimizer Loss type Hidden layers Size ratio Decay
0.1 0 0.01 0.01 tanh 1.0*10–4 0 adam CE 4 1 0.95
0.1 0 1 0.5 sigmoid 1.0*10–4 1 adam CE 2 0.9 0.95
0.1 0 5 0.5 sigmoid 1.0*10–1 4 adam CE 2 0.5 0
0.1 0 1 0.005 relu 1.0*10–1 4 adam FL 6 1 0.25
0.1 0 5 0.01 relu 1.0*10–5 5 adam FL 4 1 0.95
0.1 0 0.01 0.1 leakyrelu 1.0*10–5 0 adam FL 8 0.9 0.95
0.1 0 1 0.01 tanh 1.0*10–4 0 adam CE 6 1 0.95
0 1.0*10–8 0.001 0.05 relu 1.0*10–5 4 adam CE 8 0.6 0.95
0.1 0 0 0.01 relu 1.0*10–1 5 adam FL 8 0.9 0
0.1 0 0.01 0.01 tanh 1.0*10–3 5 adam CE 2 1 0.95