Protein Engineering

bgl3 · Graph CNN

reference_bgl3_gcn_plm_randomf0_20261104-174442

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
train1.17310.63820.59220.40436172.00000.2020182.00001.00001.37821.94590.00000.00000.52100.96001.38732.54190.04000.00000.57610.94001.29942.54190.05000.00000.57470.91871.21542.96760.06250.00000.5662
validation1.39020.54210.47520.29162050.00000.09641494.00000.3000-0.59921.21500.00000.0000-0.08070.68000.50622.26100.02000.00000.30400.68000.56352.85480.05000.00000.35130.69810.56352.45670.03770.00000.3268
test1.41350.52230.47030.26882046.00000.10531708.00000.80000.82741.86900.00000.00000.36430.70000.82822.91280.04000.00000.42200.68000.63822.91280.04000.00000.37890.69810.80122.91280.03770.00000.4141

Loss per epoch

training validation

Config

name: reference_bgl3_gcn_plm_randomf0
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 6
  split_scheme: random
  split_fold: 0
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