Protein Engineering

ube4b · Fully connected

reference_ube4b_fc_randomf0_20261104-143439

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
train1.99060.69320.65830.478312442.00000.47511.00001.00006.41429.18450.30000.83901.00005.46659.18450.32000.85921.00005.18189.18450.42000.87991.00004.05459.18450.59830.9039
validation2.17720.65230.61130.42534135.00000.4481192.00001.00005.44766.57580.10000.00000.84841.00004.38246.57580.38000.00000.81290.99004.18426.57580.46000.00000.84960.97463.75937.62880.52790.00000.8580
test2.17890.64600.60790.41724174.00000.422212.00001.00004.67867.82590.10000.00000.72101.00004.83888.62460.40000.00000.86660.99004.40588.62460.53000.00000.88080.98483.83498.62460.58880.00000.8704

Loss per epoch

training validation

Config

name: reference_ube4b_fc_randomf0
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 0
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