Protein Engineering

gb1 · Linear

reference_gb1_lr_modulof3_20261104-161328

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pctcaptured_at_1pct
train0.96840.90630.93670.820629512.00000.50102014.00001.00000.86881.11690.00000.81240.98000.86711.38160.04000.86130.99000.82221.38160.03000.86730.98740.68681.76940.27840.9188
validation4.86280.02650.0563-0.05243230.00000.2022841.00000.0000-3.2620-0.33780.00000.0000-0.25930.0400-3.14640.49390.00000.0000-0.23780.0400-2.72930.49390.00000.0000-0.12700.0498-2.90980.62370.00000.0000-0.1821
test4.83630.05310.0462-0.10274705.0000-0.370315652.00000.4000-1.27190.33130.00000.00000.15940.3600-1.04280.86630.00000.00000.23210.3600-1.04280.86630.00000.00000.23800.3950-0.93990.86630.00000.00000.2745

Loss per epoch

training validation

Config

name: reference_gb1_lr_modulof3
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  split_fold: 3
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7