Protein Engineering

bgl3 · Graph CNN

reference_bgl3_gcn_plm_modulof0_20261104-175045

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
train1.54030.40050.35880.14323841.00000.00011507.00000.50000.18511.69460.00000.00000.16830.48000.18232.20540.00000.00000.18810.53000.29942.50020.04000.00000.24050.51820.27812.50020.03640.00000.2348
validation1.35900.37710.30420.1319424.0000-0.1202632.00000.4000-0.15071.35810.00000.00000.09890.36000.00961.78560.02000.00000.18100.2900-0.13751.78560.04000.00000.13660.4000-0.04741.35810.00000.00000.1388
test1.33060.34550.33390.1166338.0000-0.22971049.00000.3000-0.08351.35810.00000.00000.17610.50000.11291.86900.04000.00000.28850.43000.01052.36370.11000.00000.27070.2308-0.11681.35810.00000.00000.1671

Loss per epoch

training validation

Config

name: reference_bgl3_gcn_plm_modulof0
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 6
  split_scheme: modulo
  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