Protein Engineering

ube4b · Fully connected

reference_ube4b_fc_plm_modulof0_20261104-175310

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
train2.19900.70150.66030.45835520.00000.518564.00001.00005.64647.82590.20000.00000.82641.00004.96187.82590.28000.00000.85151.00004.72418.62460.48000.00000.87661.00004.24788.62460.59180.00000.8987
validation2.66930.35290.36560.1236571.00000.03811359.00000.3000-0.38010.44100.00000.00000.20890.4000-0.27871.57620.00000.00000.29690.3500-0.41391.81510.05000.00000.30220.3226-0.36311.57620.00000.00000.2495
test2.89260.34010.34220.1136645.0000-0.0145191.00000.5000-0.20880.87170.00000.00000.17890.2800-0.53081.64000.00000.00000.15330.2700-0.65882.10100.01000.00000.14320.2143-0.82270.87170.00000.00000.0815

Loss per epoch

training validation

Config

name: reference_ube4b_fc_plm_modulof0
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  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