Protein Engineering

bgl3 · Linear

reference_bgl3_lr_randomf1_20261104-150329

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
train1.12920.65090.62480.41686174.00000.24915895.00001.00001.62883.11600.10000.58341.00001.43623.11600.06000.58710.99001.32873.11600.03000.58340.98751.30923.11600.04370.5990
validation1.42910.54460.50400.29652044.00000.13441938.00000.80000.69301.48330.00000.00000.33660.90001.12252.50020.02000.00000.53430.81000.86012.50020.05000.00000.46860.86791.07892.50020.01890.00000.5213
test1.36470.55350.50190.30472050.00000.10401803.00001.00001.41562.36370.00000.00000.53560.80000.95842.36370.04000.00000.46730.77000.83812.36370.05000.00000.45860.81130.98972.36370.03770.00000.4818

Loss per epoch

training validation

Config

name: reference_bgl3_lr_randomf1
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 1
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7