Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_modulof2_20261104-163122

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
train1.80540.52410.51650.01243477.00000.14751717.00000.90001.33242.36370.00000.00000.51920.82000.91202.36370.04000.00000.43890.77000.75622.41130.06000.00000.40680.75790.75732.41130.05260.00000.4056
validation1.37880.02080.01040.0000437.00000.0479909.00000.4000-0.27781.94590.00000.00000.04390.3800-0.32823.04450.06000.00000.03460.3700-0.33363.04450.08000.00000.03670.3750-0.26513.04450.06250.00000.0504
test1.5552-0.0165-0.0364-0.0089432.00000.0414553.00000.1000-1.42851.35810.00000.0000-0.31390.1400-1.22771.86900.02000.0000-0.28270.1700-1.01041.86900.04000.0000-0.21350.0588-1.44441.35810.00000.0000-0.3311

Loss per epoch

training validation

Config

name: reference_bgl3_fc_modulof2
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  split_fold: 2
model:
  name: fcn
  hidden:
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7