Protein Engineering

ube4b · Linear

reference_ube4b_lr_s2_20261104-021621

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
test2.45880.58460.58340.34122077.00000.419834.00000.90003.68146.56280.40000.00000.68340.96003.77997.55410.42000.00000.81650.94003.33087.55410.51000.00000.80880.95923.44397.55410.51020.00000.8260
train2.43200.60040.59180.360116805.00000.45530.10000.76240.18000.73950.28000.76690.50380.8243
validation2.47620.59160.58120.34971869.00000.44082.00001.00005.50487.74370.50000.00000.88650.96003.80367.74370.50000.00000.80910.97003.60567.74370.54000.00000.85670.97733.69127.74370.54550.00000.8548

Loss per epoch

training validation

Config

name: reference_ube4b_lr_s2
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: 2