Protein Engineering

ube4b · Linear

reference_ube4b_lr_s4_20261104-023825

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
test2.44580.58740.58800.34472077.00000.418633.00000.90003.68146.56280.40000.00000.68340.96003.77957.55410.40000.00000.81640.95003.40227.55410.51000.00000.82100.95923.43287.55410.50000.00000.8241
train2.41790.60330.59680.363916805.00000.45550.10000.76240.18000.75330.29000.77740.51010.8284
validation2.46670.59350.58500.35221869.00000.43962.00001.00005.55887.74370.50000.00000.89350.96003.85787.74370.50000.00000.81750.97003.61527.74370.54000.00000.85830.97733.66507.74370.53410.00000.8504

Loss per epoch

training validation

Config

name: reference_ube4b_lr_s4
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: 4