Protein Engineering

ube4b · Linear

reference_ube4b_lr_plm_randomf3_20261105-035657

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
train2.42320.59970.59790.359412385.00000.44053.00001.00005.87299.18450.20000.00000.77051.00005.00439.18450.24000.00000.79480.98004.63919.18450.38000.00000.80360.96613.67449.18450.52880.00000.8399
validation2.46090.60010.59740.36004163.00000.463731.00001.00004.95127.74370.20000.00000.76400.94003.97369.15370.26000.00000.75040.96003.89699.15370.42000.00000.80060.95943.57849.15370.51270.00000.8231
test2.41240.60160.59800.36194203.00000.441410.00001.00005.67786.93280.40000.00000.89601.00004.46836.93280.40000.00000.83550.98004.00876.93280.48000.00000.83370.98983.67016.93280.50250.00000.8518

Loss per epoch

training validation

Config

name: reference_ube4b_lr_plm_randomf3
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  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