Protein Engineering

bgl3 · Graph CNN

reference_bgl3_gcn_plm_randomf4_20261105-041319

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
train1.16260.64610.59200.41436204.00000.20003323.00000.90001.41582.45670.00000.00000.51420.98001.34082.85480.04000.00000.55820.95001.28662.85480.04000.00000.57070.93131.22062.85480.04370.00000.5704
validation1.42420.51810.46330.26332046.00000.08332470.00000.70000.67241.78560.00000.00000.31550.66000.63622.08410.00000.00000.35210.65000.56772.91280.03000.00000.35130.66040.62062.08410.00000.00000.3480
test1.42560.51300.46130.25592018.00000.0990170.00000.80000.95561.78560.00000.00000.40840.70000.53932.65740.02000.00000.31170.72000.64342.96760.03000.00000.37550.69810.53962.65740.01890.00000.3133

Loss per epoch

training validation

Config

name: reference_bgl3_gcn_plm_randomf4
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 6
  split_scheme: random
  split_fold: 4
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