Protein Engineering

bgl3 · Graph CNN

reference_bgl3_gcn_modulof2_20261104-163136

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
train1.25690.57210.54670.31253477.00000.1480995.00001.00001.25522.26100.00000.00000.49520.88001.15272.96760.06000.00000.52330.82000.93982.96760.06000.00000.47500.82110.92982.96760.06320.00000.4694
validation1.36350.11110.11990.0111437.0000-0.07621131.00000.1000-0.32290.38470.00000.00000.02920.4000-0.17741.59450.02000.00000.09610.4400-0.19472.31360.07000.00000.10090.3125-0.09741.59450.00000.00000.1076
test1.53860.10150.06690.0019432.0000-0.0462622.00000.2000-0.67081.35810.00000.0000-0.04810.3200-0.37151.69460.02000.00000.06610.2900-0.59741.86900.03000.0000-0.02850.2353-0.45381.35810.00000.00000.0291

Loss per epoch

training validation

Config

name: reference_bgl3_gcn_modulof2
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  graph_threshold: 6
  split_scheme: modulo
  split_fold: 2
model:
  name: gcn
  filters:
  - 32
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7