Protein Engineering

ube4b · Fully connected

reference_ube4b_fc_s5_20261104-143957

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
test2.12750.65650.62320.43002077.00000.417519.00001.00004.61366.56280.40000.00000.80831.00004.18507.55410.46000.00000.88010.96003.62827.55410.55000.00000.85950.95923.64027.55410.55100.00000.8593
train2.03840.68320.64480.463716805.00000.46142.00001.00006.00179.18450.10000.77091.00005.46889.18450.24000.83651.00005.21199.18450.33000.85620.99753.98889.18450.57410.8899
validation2.18930.65360.61660.42511869.00000.43711.00001.00005.62727.74370.50000.00000.90221.00004.38137.74370.52000.00000.89851.00003.87497.74370.55000.00000.90251.00003.99557.74370.57950.00000.9056

Loss per epoch

training validation

Config

name: reference_ube4b_fc_s5
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: 5