Protein Engineering

ube4b · Fully connected

reference_ube4b_fc_plm_modulof2_20261104-184250

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
train2.21120.60280.60800.33165464.00000.23833888.00000.90003.75976.12790.10000.00000.66860.98003.14216.12790.18000.00000.70680.98002.81056.12790.19000.00000.72000.96422.27956.12790.31900.00000.7366
validation2.68790.33560.34850.1125418.0000-0.12931734.00000.4000-0.42310.98710.00000.00000.18690.3600-0.46992.05870.02000.00000.22900.3900-0.45233.99860.06000.00000.27220.5000-0.49980.98710.00000.00000.1843
test4.47330.31460.33800.0699819.0000-0.07352829.00000.2000-0.88311.19360.00000.00000.03460.3200-0.67112.25020.00000.00000.07490.3500-0.55583.15840.00000.00000.10390.3750-0.54902.25020.00000.00000.0903

Loss per epoch

training validation

Config

name: reference_ube4b_fc_plm_modulof2
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 2
model:
  name: fcn
  hidden:
  - 100
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7