Protein Engineering

pab1 · Linear

reference_pab1_lr_plm_modulof0_20261104-175221

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
train0.69310.91000.91250.81281755.00000.0913302.00001.00000.19310.51660.00000.00000.70960.74000.12270.73310.02000.00000.74760.69000.11310.89080.07000.00000.77750.68840.11880.89080.10870.00000.7960
validation1.94870.71590.72470.5118132.0000-0.2596520.00000.3000-0.30210.03640.00000.00000.67660.1600-0.30610.12810.00000.00000.76180.1500-0.31860.29770.09000.00000.79100.2353-0.26270.09190.00000.00000.7206
test2.58660.71190.71800.1948171.00000.0792208.00000.1000-0.34350.10460.00000.00000.58760.2200-0.28820.38430.04000.00000.70920.2500-0.27360.90330.18000.00000.75540.2353-0.33700.15670.00000.00000.6239

Loss per epoch

training validation

Config

name: reference_pab1_lr_plm_modulof0
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 0
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.001
  patience: 15
  min_delta: 1.0e-05
  seed: 7