Protein Engineering

ube4b · Linear

reference_ube4b_lr_modulof3_20261104-161658

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
train3.06740.52250.46770.22407842.00000.4589604.00001.00004.71796.57580.00000.67170.86003.29366.77780.18000.59640.87003.02516.77780.19000.60210.89632.89058.62460.31410.6779
validation3.7294-0.0523-0.0500-0.0775318.0000-0.06241149.00000.0000-2.5414-0.45030.00000.0000-0.16560.0400-2.37171.30610.00000.0000-0.18500.0800-2.19942.04160.04000.0000-0.16880.0000-2.4728-0.32100.00000.0000-0.1716
test3.2503-0.0130-0.0117-0.0732418.0000-0.0273519.00000.1000-1.36530.23420.00000.0000-0.01410.2800-1.20343.01670.02000.00000.02650.2000-1.38503.01670.07000.0000-0.02760.1667-1.44871.51550.00000.0000-0.0345

Loss per epoch

training validation

Config

name: reference_ube4b_lr_modulof3
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  split_fold: 3
model:
  name: lr
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7