Protein Engineering

bgl3 · Linear

reference_bgl3_lr_plm_randomf3_20261105-035154

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
train1.19770.63150.59400.39386140.00000.21054962.00001.00001.33051.94590.00000.00000.47930.96001.38272.45670.02000.00000.56560.94001.29652.45670.04000.00000.57130.92501.23592.85480.07500.00000.5745
validation1.40970.51670.47290.26422018.00000.132164.00000.90001.04361.78560.00000.00000.43640.80000.77992.31360.02000.00000.39810.75000.77213.11600.06000.00000.42530.81130.78952.31360.03770.00000.4036
test1.39840.53760.49850.28612110.00000.1317130.00000.90001.17551.78560.00000.00000.49350.74000.78552.08410.00000.00000.40560.72000.69662.26100.04000.00000.39260.75470.80352.08410.00000.00000.4143

Loss per epoch

training validation

Config

name: reference_bgl3_lr_plm_randomf3
task: dms
data:
  dataset: bgl3
  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: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7