Protein Engineering

ube4b · Fully connected

reference_ube4b_fc_s4_20261104-135640

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
test2.12300.65700.62300.43122077.00000.411616.00001.00004.69106.56280.40000.00000.81861.00004.17287.55410.44000.00000.87820.97003.62937.55410.55000.00000.85970.96943.63617.55410.54080.00000.8586
train2.02540.68360.64610.467116805.00000.46361.00001.00006.54959.18450.20000.82781.00005.56059.18450.28000.84761.00005.24059.18450.33000.85991.00004.00459.18450.58040.8925
validation2.18010.65420.61840.42751869.00000.43931.00001.00005.56457.74370.50000.00000.89421.00004.37517.74370.56000.00000.89751.00003.89087.74370.57000.00000.90531.00003.95607.74370.55680.00000.8990

Loss per epoch

training validation

Config

name: reference_ube4b_fc_s4
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index
  split_dir: ube4b/splits/main
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: 4