Protein Engineering

ube4b · Linear

reference_ube4b_lr_s5_20261104-025019

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10tie_share_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50tie_share_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100tie_share_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pcttie_share_at_1pctcaptured_at_1pct
test2.45040.58610.58600.34352077.00000.417834.00000.90003.68146.56280.40000.00000.68340.96003.77997.55410.40000.00000.81650.95003.40047.55410.51000.00000.82070.94903.41257.55410.51020.00000.8206
train2.42550.60170.59410.361816805.00000.45540.10000.76240.18000.74950.29000.76980.50750.8286
validation2.47320.59220.58250.35051869.00000.43972.00001.00005.55887.74370.50000.00000.89350.96003.79237.74370.50000.00000.80740.97003.61217.74370.54000.00000.85780.97733.67877.74370.54550.00000.8527

Loss per epoch

training validation

Config

name: reference_ube4b_lr_s5
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index
  split_dir: ube4b/splits/main
model:
  name: lr
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 5