Protein Engineering

pab1 · Linear

reference_pab1_lr_modulof0_20261104-144644

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
train1.38650.85500.85670.62551755.00000.14753956.00000.5000-0.82650.57270.00000.34220.5400-0.20210.86010.02000.61970.5600-0.14760.86010.06000.67030.5507-0.10630.86010.05800.7015
validation4.3932-0.0873-0.1024-0.1006132.0000-0.0377807.00000.0000-2.3369-0.29610.00000.0000-0.03580.0000-2.6879-0.02770.00000.0000-0.17900.0300-2.66460.19300.03000.0000-0.17750.0000-2.4358-0.29610.00000.0000-0.0735
test3.6748-0.1599-0.1667-0.1439171.00000.0302164.00000.1000-2.65320.74060.10000.0000-0.33130.0200-2.70510.74060.02000.0000-0.40950.0200-2.58680.74060.01000.0000-0.37430.0588-2.80290.74060.05880.0000-0.4132

Loss per epoch

training validation

Config

name: reference_pab1_lr_modulof0
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  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