Protein Engineering

pab1 · Linear

reference_pab1_lr_modulof1_20261104-153821

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
train2.42270.64060.59660.32561937.00000.08862542.00000.3000-0.46030.19550.00000.46960.3600-0.27190.72040.02000.58880.3300-0.28080.72040.04000.61180.2953-0.27850.89080.06710.6292
validation4.1418-0.1970-0.1829-0.1538116.0000-0.0599559.00000.0000-3.1776-0.66900.00000.0000-0.51000.0000-2.7277-0.15930.00000.0000-0.35860.0100-2.92070.12700.01000.0000-0.46850.0000-3.2803-0.66900.00000.0000-0.5620
test4.5300-0.0687-0.0815-0.1348132.0000-0.0559835.00000.0000-2.3369-0.29610.00000.0000-0.03580.0000-2.3465-0.02770.00000.0000-0.04420.0200-2.54080.16660.02000.0000-0.12640.0000-2.4358-0.29610.00000.0000-0.0735

Loss per epoch

training validation

Config

name: reference_pab1_lr_modulof1
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  split_fold: 1
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.001
  patience: 15
  min_delta: 1.0e-05
  seed: 7