Protein Engineering

ube4b · Fully connected

reference_ube4b_fc_modulof2_20261104-163727

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
train2.38640.54480.55540.27865464.00000.25824034.00000.90003.65286.12790.10000.00000.65490.98002.97636.12790.16000.00000.68140.98002.78286.12790.19000.00000.71540.93552.08646.12790.31180.00000.6988
validation3.0411-0.0009-0.0253-0.0041418.00000.06331061.00000.2000-0.98490.36640.00000.00000.06710.2600-1.02892.57210.06000.00000.07460.2000-1.20003.36350.05000.00000.03190.3333-0.71621.99140.00000.00000.1344
test4.9029-0.0966-0.1101-0.0195819.00000.0097270.00000.1000-1.99650.34970.00000.0000-0.12100.1200-2.13143.54410.00000.0000-0.16310.2000-1.66903.54410.01000.0000-0.09720.0625-2.35011.04160.00000.0000-0.1892

Loss per epoch

training validation

Config

name: reference_ube4b_fc_modulof2
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index
  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