Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_modulof3_20261104-161050

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pctcaptured_at_1pct
train0.48200.95470.94280.910729512.00000.510811929.00000.90000.47140.74820.00000.71970.96000.69701.26360.00000.81920.98000.73441.42230.05000.84520.98370.67711.45260.27740.9161
validation2.07950.74590.74140.54993230.0000-0.01075162.00000.70000.34231.20350.00000.00000.68580.2800-0.21921.20350.00000.00000.55930.2300-0.33441.20350.01000.00000.53960.2587-0.35841.22470.02490.00000.5475
test4.12210.55690.55390.06024705.0000-0.167911105.00000.4000-0.25091.68780.00000.00000.41370.5000-0.04241.68780.00000.00000.49930.4900-0.05141.68780.02000.00000.50950.4350-0.18591.68780.06000.00000.4875

Loss per epoch

training validation

Config

name: reference_gb1_gcn_modulof3
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  graph_threshold: 7
  split_scheme: modulo
  split_fold: 3
model:
  name: gcn
  filters:
  - 128
  - 128
  - 128
  - 128
  - 128
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7