Protein Engineering

bgl3 · Graph CNN

reference_bgl3_gcn_s4_20261104-130331

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
test1.28970.56690.51020.32131036.00000.1747191.00000.80001.06971.69460.00000.00000.48450.78000.83672.31360.06000.00000.46340.77000.76632.31360.05000.00000.47010.81480.95402.20540.07410.00000.4810
train1.18900.63120.59830.39548299.00000.21040.00000.46880.04000.54210.03000.53350.06020.5749
validation1.39190.54430.49710.2959933.00000.06381460.00000.90001.07081.69460.00000.00000.48230.76000.80442.85480.04000.00000.45090.74000.69772.85480.05000.00000.44070.95831.19301.86900.00000.00000.5640

Loss per epoch

training validation

Config

name: reference_bgl3_gcn_s4
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: bgl3/splits/main
  graph_threshold: 6
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: 4