Protein Engineering

ube4b · Fully connected

reference_ube4b_fc_plm_randomf2_20261104-183147

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
train1.98860.69010.65360.475412472.00000.460766.00001.00005.55137.74370.20000.00000.75891.00005.32328.62460.28000.00000.84821.00005.07609.15370.39000.00000.86760.99664.01419.15370.58980.00000.8982
validation2.08850.66930.63430.44764203.00000.4372101.00001.00005.39896.71530.30000.00000.86081.00004.71136.71530.40000.00000.87011.00004.43836.77780.57000.00000.89981.00003.84676.93280.53300.00000.8814
test2.14300.66270.62150.43914076.00000.44561.00001.00005.68739.18450.20000.00000.80161.00004.85909.18450.42000.00000.86041.00004.47509.18450.46000.00000.87820.99493.99069.18450.57360.00000.8845

Loss per epoch

training validation

Config

name: reference_ube4b_fc_plm_randomf2
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  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