Protein Engineering

ube4b · Linear

reference_ube4b_lr_modulof1_20261104-153902

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
train2.44250.53510.54840.25334756.00000.2513141.00000.90003.38726.12790.10000.64830.92002.56476.12790.12000.64490.92002.38926.12790.20000.67460.91451.92747.38210.27780.6735
validation5.1252-0.1245-0.1158-0.0657819.0000-0.09923109.00000.2000-1.51521.01460.00000.0000-0.05370.1600-1.56622.74940.00000.0000-0.07100.2000-1.55352.74940.00000.0000-0.07630.1875-1.64022.74940.00000.0000-0.0791
test3.8187-0.1278-0.1344-0.2538571.0000-0.02792009.00000.1000-2.26370.09410.00000.0000-0.14900.0600-2.53350.92230.00000.0000-0.26060.1200-2.05081.65060.04000.0000-0.16210.0645-2.56370.19360.00000.0000-0.2424

Loss per epoch

training validation

Config

name: reference_ube4b_lr_modulof1
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  split_fold: 1
model:
  name: lr
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7